As part of decentralized finance (→DeFi), this →cryptocurrency is used to coordinate transactions on a decentralized lending marketplace. Aave allows to make loans (→crowdlending) and to form lending pools with various other →cryptocurrencies (e.g., →ETH, →DAI), as well as to conduct asset (→digital asset) and collateral exchanges. Aave’s →liquidity →token is based on →Ethereum’s →ERC-20 token and has also been used to establish other decentralized exchanges (→DEX) such as →Uniswap.

Describes a initiative that comprises several stages that support or “accelerate” →startup companies over several months in their early business development. Similar to →regulatory sandboxes, selected →startup companies receive benefits from an organization known as accelerator or →incubator. Among the examples are the provision of premises (→co-working spaces), technical equipment, or access to networks and coaching seminars. In return, accelerators receive future profit sharing, pre-emption rights or minority shares from the →startup companies they have supported.

Third-party (→TTP) access to payment services that has become a →business model of many →fintech companies. It is used, for example, to process financial transactions and to analyze customer-specific transaction data. In most cases this also refers to access to customer accounts, which banks need to grant third parties in connection with →PSD2. From a technological side, the European Banking Authority (→EBA) is responsible for the development of standards (so-called regulatory technical standards, RTS) regarding security, authentication and communication. In the →four-corner model, this gives rise to account information service providers (→AISP) and payment initiation service providers (→PISP), who have direct access to transacting parties (see Fig. 1). These service providers penetrate the previously closed system of banks and thus open the way to →multi-bank services.

Fig. 1
Access-to-account approach in PSD2

Account information services, as defined in the EU’s second payment services directive (→PSD2), provide users with an overview of their financial situation. They consolidate information from one or more →payment service user accounts (→PSP). AIS providers (→AISP) are mainly →fintech companies, but also primary or house banks. With the consent of the account holder, it is possible to combine accounts of different banks on the →online banking platform or on personal finance management solutions (→PFM, →multi-bank).

Providers of account information services (→AIS) yield access to payment accounts (→XSTA) and are involved in the execution of →electronic payments as defined by the EC’s Payment Services Directive (→PSD2).

In the →four-corner model, the acquiring bank enables the merchant to accept card payments at the point of sale (→PoS). Acquirers act as financial service providers in the credit card environment, offering acquiring services to retail companies on behalf of the credit card companies. Based on cooperation agreements with card providers (→EMV), acquirers ensure the acceptance and processing of transactions on behalf of the merchant by forwarding commercial and technical data to the participating banks or financial institutions and the card providers. They establish a connection to their bank (→issuer) and authorize the payment. If the acquirer and →issuer are the same institution, these are so-called →on-us transactions. Besides supporting the accepting activities within card-related transactions, they often also provide the necessary hardware equipment and software at the merchant’s →POS. Acquirers may also act as →integrators and offer other payment methods (e.g., invoice, PayPal, →cryptocurrency). In the past, the scale-elastic market of acquirers has experienced a strong concentration in recent years, resulting in two dominant companies, the Danish Nets Group and the French Worldline.

With symmetric encryption methods (→cryptography) such as AES, the keys used for encryption and decryption are identical in contrast to →asymmetric encryption methods (→RSA). AES encrypts and decrypts data block by block using a key whose length can be 128 (AES-128), 192 (AES-192), or 256 (AES-256) bits. Compared to the previously used data encryption standard (DES), which is limited to 56 bits, AES offers higher security and is therefore often applied in the financial industry (e.g., →MAC).

In the banking context, this term is used for representatives or agents of financial service providers (e.g., a clearing agent for →CSMs, a paying agent for imprest accounts, or a bank agent for banks in general). In a technological sense, the term also refers to intelligent software agents, which denote software with some form of autonomous activity. For example, →chatbots with artificial intelligence (→AI) functionalities support customer advice, and agents are also used on →electronic markets to identify and compare offers and to negotiate with providers (e.g., regarding price, delivery terms, payment conditions).

Intermediary →business model (→intermediation) based on the bundling of services, which is present in many →fintech solutions. Similar to the →broker model, an aggregator mediates between providers of competing and/or complementary services on the one hand and clients on the other. In contrast to brokers, aggregators take possession of the transacted offerings and they are also responsible for setting prices. The aggregator model is found with →e-commerce platforms such as Amazon or banks that provide services of cooperating insurance companies (→bancassurance). If these digital services are also linked to digitized physical resources (→smart product), such as →electronic payment services for vehicle parking services, then the term →smart service or →mobility service is also used.

An agile organization features a high degree of maturity regarding →digitalization as well as transformation management and is a core characteristic of →startup or →fintech companies. →Agility should increase the ability to react on changing conditions in the business environment, as they result from new customer demand, new competitors or new technologies. The aim is being able to quickly develop measures that contribute to →customer experiences, improved business processes or →business models on the one hand, and to establish agile change structures and processes on the other hand. The latter should sustain explorative approaches, fast learning processes as well as self-control and organization in the sense of an “agile mindset”.

Known from the literature on lean management, agility has spread to other domains, in particular software development. It denotes a procedure in development projects, which aims at attaining results iteratively in smaller chunks. Agile principles have established themselves especially in the development of →IT applications (e.g., →front-end- and →back-end applications) and is present in concepts such as →Scrum or Kanban. As shown in Fig. 2, the agile approach conceives costs and time as stable and adapts project goals and quality accordingly. In contrast, classical development approaches like the waterfall procedure consider goals to be stable and are often linked with exceeding cost and time budgets. This has often been the case with the introduction of complex →core banking systems. →Fintech businesses have typically adopted agile development methods, but had the advantage of a “greenfield approach”, i.e., non-existing legacy structures and systems (→legacy system).

Fig. 2
Target values for classic and agile approach

As a general purpose technology, artificial intelligence (→AI) may be applied to many use cases. To structure potential application areas in the financial industry, a periodic table known from chemistry has been suggested (see Fig. 3). The x-axis shows the abilities that determine intelligent behavior (→AI) and the y-axis shows the complexity levels. It starts with applications that support the visual or acoustic perception of the world, e.g., for the recognition of images, speech or faces. In the case of visual perception, neuronal networks store characteristic features, such as eyes, nose and mouth, in order to recognize them as faces in other images. An example from the financial sector is the know-your-customer process (→KYC), which supports the identification of “high risk individuals”. Areas of application with the functional scope of processing focus on the conclusive processing of the perceptions. Natural language processing (→NLP) allows to recognize words with their meaning and, if the system is specified accordingly, also the mood of the text from the different word combinations, which might be valuable in oral or written conversations (→sentiment analysis) with customers. Action comprises applications that involve actions to achieve specific goals. The simplest field is “control”, which refers to the control of software or hardware depending on defined measured variables. These could be automated →AI systems for financial investments, which maximize the value of investment portfolios in predefined asset classes. If the →AI system decides to buy or sell a security based on the preferences defined by the investor and the current market situation, it executes this transaction on an →electronic exchange and adjusts the portfolio accordingly (→robo advisory). In contrast, the field of application collaborative robotics is more complex, since (physical) →robots are ultimately supposed to independently conduct actions that make sense in a given situation. An example is the (meanwhile discontinued) humanoid →robot Pepper, developed by the Japanese technology company SoftBank Robotics for customer advisory services in bank branches. This robot was programmed to pre-select the products relevant to the customer while the customer was waiting for a conversation with the (real) customer advisor. The learning cluster enhances the areas of perception, processing and action. Intelligent agents may generate new knowledge about their environment during perception and processing as well as during the execution of actions. Category learning, for example, aims to learn combinations of characteristic values and thus to categorize them. Pepper, for instance, could categorize faces according to their mood (e.g., does the new visitor in a bank branch appear safe or unsafe because of his behavior?) and learn new subcategories from the category of “unsafe visitors” (e.g., visitors who appear to be looking for something and visitors who Pepper would classify as potential bank robbers). The application area of relationship learning goes beyond learning categories, in that the →robot learns reactions to the respective category and assigns them to the categories (e.g., whether the customer is waiting for his appointment and might be happy about a first interaction with the expert robot). The →robot could identify the faces of customers and analyze their social media contacts to determine other friends of the customer who have also recently visited the store. Customers in a corresponding network could receive individual benefits for referring friends. These responses could be supplemented by other interaction possibilities (e.g., Pepper could learn that he only has to show some visitors the way to the water dispenser if they are categorized to look uncomfortable in the summer), whereby the usefulness of such scenarios or their cost-benefit-risk ratio requires critical validation in each case.

Fig. 3
Application areas of AI in the financial sector by complexity and intelligence (see Dietzmann & Alt, 2020)

In analogy to helicopter money, Airdrop refers to give away →coins of existing or new →cryptocurrencies for free. This may occur to retain active customers, to acquire new customers and, in the course of marketing campaigns, upon the introduction of new →cryptocurrencies or after a →fork.

Describes a procedure or a regulation for solving complex problems or a class of problems, which are sufficiently formalized to be processed by an artificial system. Algorithms are mathematical calculation rules or logical rules anchored in program code that determine the calculation and/or evaluation of data (e.g., if-then conditions). Algorithms are often present in solutions based on artificial intelligence (→AI) and allow a high degree of automation in standardized or low-complexity financial processes, which are often typical for →fintech solutions. The application of algorithms in a specific setting is referred to as →algorithmization.

Use of artificial intelligence methods (→AI) to support or execute banking processes. This includes, for example, →robo advisory or the credit assessment of an applicant with the help of →algorithms and social media activities (→social data). In some cases, no historical data of the applicant is necessary for the decision-making process.

A method of →AI-based →agents that have been used in the banking sector since the →digitalization of stock exchanges (→electronic exchange) from the 1980s onwards. Automated trading systems manage larger portfolios and place orders depending on rules and price developments on the exchange. Algorithmic trading systems lead to high frequency trading (→HFT) when they place buy and sell orders in quick succession to realize (small) arbitrage.

Describes the use of →algorithms in business processes. As shown in Fig. 4, existing processes are supported by information technology (→IT) and deliver data that is subject to analytics (→business analytics). The information gained on this basis yields the ability to adapt or learn independently and improve decisions. If, for example, an “intelligent” vehicle is involved in an accident, it can transfer the previously acquired data (n in Fig. 4) to the manufacturer’s network and suggest to other vehicles that they should brake earlier in this situation in future. This would lead to new insights and data, i.e., n + 1 in Fig. 4, which in turn are labeled to make them amenable for machine processing. Similarly, →algorithms are used in credit allocation or complaint management processes.

Fig. 4
Algorithmization for business processes

Chinese provider of a →mobile payment system, who has experienced numerous expansions from a pure online →payment system to become a dominant →mobile payment system. Founded in 2004, Alipay meanwhile comprises a large user base of over one billion active users and over 80 million merchants, making it the largest →mobile payment system worldwide. Since 2014, the service is part of the Chinese Ant Group, a subsidiary of the Alibaba Group, which still holds a 30% stake in the company. Alipay features a →mobile wallet and is used on →e-commerce platforms (especially those of Alibaba such as Taobao and TMall) as well as for car sharing, food or →mobility services. Payments are supported by credit card, direct debit or →P2P. If this is done between Alipay users, no classical financial service provider is required. In addition, Alipay acts as an intermediary (→intermediation) to providers of insurances as well as investment and credit products (→microfinance), which consumers may use to finance the goods purchased via numerous platforms (→e-commerce). In addition to the large user base, the procedure for assessing creditworthiness based on artificial intelligence (→AI) and →big data is considered a competitive advantage. A main competitor of Alipay is →WeChat Pay of the Chinese Tencent Group.

Alternative →coins are →alternative currencies in the →cryptocurrency environment, which often originate from splits (→blockchain split) of existing →cryptocurrencies like →Bitcoin. Although these new →cryptocurrencies differ from “original currencies” like →Bitcoin, they typically feature many similarities regarding the →mining algorithm or the →wallet functionality. Well-known altcoins are →Bitcoin Cash, →Eos, →Iota, →Monero or →Xrp. One of the main motivations for the emergence of altcoins are higher levels of privacy and anonymity in →electronic payments based on →cryptocurrencies, for which the term →privacy coins has emerged. For example, Altcoins derive from →Bitcoins may be generated (“mined”), stored in virtual →wallets and traded via corresponding exchanges (→crypto exchange), much like →Bitcoin.

Refers to the use of publicly available consumer information to create reliable risk profiles of credit applicants. While traditional credit scoring is based on data from payment history, current debt, the length of credit history or the credit utilization ratio, alternative approaches also include additional data sources. Among the examples is Fico, which draws personal data from social networks (→social data) or online profiles, transaction-related data from past purchases, outstanding payments, cell phone payments, income or bank information. It enables customers without bank accounts to qualify for loans.

Currencies that are neither issued nor regulated by national banks of individual countries and are not recognized as official means of payment. The latter might change with →cryptocurrencies that are officially accepted (e.g., →Bitcoin in El Salvador) or launched by official institutions, in particular, by central banks (→CBDC). Among the examples for alternative or complementary currencies are →Ethereum Coins, →Ripple Coins and →Bitcoins, but also currencies that are present in regional communities. At least many of the electronic alternative currencies (e.g., →Bitcoin, →Diem, →Ether) are expected to face increasing regulation.

While traditional financing opportunities include banks, stock exchanges or over-the-counter (→OTC) capital markets, alternative financing instruments have emerged for specific purposes. For example, these focus on projects or transactions with a lower capital volume for financing innovative or creative projects, which often comprise a large number of small investors. Well-known forms of this segment of →fintech services are →crowdfunding and →crowdinvesting.

With →digitalization, →digital platforms have emerged as alternatives to traditional forms of financing that bring together lenders and donors. This is particularly relevant for small and medium-sized enterprises (→SME), people with low incomes (e.g., student loans) or lenders in emerging markets without access to the banking system. Alternative lending may be divided into the segments →crowdlending (for companies) and →P2P lending (for private persons).

Similar to electronic stock exchanges (→electronic exchange), alternative trading platforms bring together buyers and sellers of securities or assets to settle transactions. As privately operated markets, they define the trading and price-setting rules and are often less democratic in yielding transparency on the market action for all parties alike. Although they are less regulated than official exchanges, they are still subject to national regulatory authorities, such as the SEC (U.S. Securities and Exchange Commission) in the case of alternative securities platforms in the US. While in the US the term alternative trading system (ATS) is often used synonymously for ATP, it is multilateral trading facility (→MTF) in Europe. Among the established ATPs are the systems of large banks (e.g., Credit Suisse, Deutsche Bank, J.P. Morgan, Goldman Sachs or UBS) but also those of service providers such as Dealerweb or Instinet. Similarly, the more recent →cryptocurrency trading platforms (→crypto exchange) are considered ATPs, which still await regulation.

Similar to →pervasive computing, environmental intelligence assumes a widespread or ubiquitous presence of information technology (→IT). This includes mobile technologies and →wearables as well as small computing devices in physical objects (→IoT), which are present in various assistance scenarios (e.g., assisted living, personal trainer, smart home) or sales scenarios (e.g., personalized advertising in bank branches). Such scenarios often include digital services (→smart service), which are charged on a per-usage basis (→PAYU).

The prevention of money laundering is a key activity in financial systems and comprises checks on deposits or transfers of sums of money above a certain amount. The goal is to determine the origin of the assets as well as the identification of the owners of the assets (→KYC). Regulations are enacted by the European Union (EU) as well as by individual countries. In Germany, for example, the money laundering act (GwG) implements the EU'’s money laundering directive. According to this directive, cash payments are limited to an amount of 2000 € since 2020 without being subject to a money laundering audit and cross-border cash amounts in excess of 10,000 € require a declaration within the EU. With the amendment of the fourth EU money laundering directive (Directive EU 2018/843), the regulations also apply to →crypto custody transactions, which makes →digital currencies such as →Bitcoin also subject to money laundering checks. Financial service providers have traditionally implemented such →compliance checks in their internal →application systems, but external service providers with service offerings in this →regtech segment (e.g., the Estonian provider Salv) have recently emerged.

Describes the use of application interfaces (→API) for coupling digital services among service providers in and with the financial sector. It aims at connecting modular →application systems is based on the concepts of →open banking and →platform banking to enable efficient networking and →sourcing strategies among businesses in the financial industry. In a broader sense, API banking allows the connection of actors in the primary value creation process (i.e., an automotive manufacturer like in Fig. 5) with providers in the secondary value creation process (i.e., financial service providers like the →PSP in Fig. 5) in the sense of embedded finance (→EFI). Figure 5 shows the example of an automobile manufacturer, which links various →payment services to a platform via →API to process master and transaction data. It can also be interpreted as a form of →outsourcing of financial functions of the car manufacturer.

Fig. 5
API connection of financial services at a car manufacturer

Generic term to denote use of →applications (“apps”) within the economic environment. It includes the orientation and construction of these →ecosystems, the →business models within these →ecosystems as well as the value creation logic (e.g., →network effect). Since apps use →digital platforms such as →app stores for distribution, the term “platform economy” (→platform) is often used in a similar sense.

Short form for a digital distribution platform for application software or →applications (“apps”). Typically, an application or app store comprises a →digital platform with an electronic catalog, which includes a large number of apps from various providers that may be searched, ordered and downloaded by users on their devices. Since app stores bring together many providers and many users, they may be regarded as →digital marketplaces. In the financial industry, the app store principle is increasingly present in the concepts of →core banking systems that follow the idea of →open banking.

The abbreviation “app” for application has established itself as a term for application software (→application system) in the domain of desktop computers and mobile devices. The latter, i.e., smartphones or tablets, also use the term mobile apps, which are often limited in their range of functions and are related to or individualized for the respective user. If the functional logic of the application is mainly located on the server (instead as on the client device), it is referred to as a web application.

Application-specific circuits is computing hardware that comprises a set of instructions that is specific for certain application purposes (e.g., graphics, file handling, computing operations). Compared to central processing units (CPUs) that may serve a broad range of application purposes, ASICs are less universally applicable, but they are more powerful in their field and tend to be more cost-effective by omitting functions that are not required for them. The ASIC approach dates back to the concept of reduced instruction set computers (RISC) from the 1960s and has recently gained importance with the spread of →artificial intelligence (e.g., for →deep learning) and cryptographic calculations (e.g., for →consensus mechanisms such as →PoW). In particular, →miners and →mining pools rely on ASIC hardware, while alternative →consensus mechanisms such as →proof-of-stake have emerged that claim to be ASIC-resistant.

Denotes an interface of an application software (→application system), which comprises the specification of an input and an output. It allows application programs to exchange data directly or without media discontinuities (→media break) and are the basis for →real-time processing in distributed environments. In contrast to a data interface, which yields access to a database, APIs are function interfaces where the input consist of commands with corresponding parameters that is needed to trigger functions in the target application. The concept has long been known in the modularization and integration of →application systems, as it reduces the complexity of large (so-called monolithic) systems on the one hand and creates the possibility of flexibly integrating specialized systems inside and outside the company on the other. In the financial industry, APIs are key in the current developments towards →API banking, →banking-as-a-service, →platform banking or →open banking. The connectivity that is embedded in these initiatives is also driven by regulations such as →PSD2, which requires banks to offer standardized APIs for accessing accounts on a non-discriminatory basis. Thus, they enable financial service providers such as →fintech companies to access banking systems to read transaction data and to derive their own services (e.g., →multi-bank functionalities) on this basis. In principle, all market participants may offer APIs, but in the financial sector approval is often required regulating authorities (e.g., →BaFin in Germany). An example of an API implemented using the →REST technology is shown in Fig. 6 for querying an exchange rate of 100 USD in Euros at the →neo- or →smartphone bank Revolut. It contains the function call (request/input) and the individual transferred data fields with their descriptions. The feedback (response/output) is displayed in →JSON format.

Fig. 6
Example of an API of the smartphone bank Revolut for an exchange rate query (see Revolut, 2020)

Part of an information system (IS) consisting of a hardware and a software system (see Fig. 7). The latter comprises the basic software such as the →operating system and the utilities (e.g., compilers, device drivers) as well as the application software, which contains functionalities for various application purposes. These refer to general functions such as e-mail or web browsers as well as industry- or sector-specific application functions, such as →core banking systems. The aim of business application systems is to achieve high degrees of business process automation and integration between an organization’s functional areas. For example, this is the case when securities are purchased electronically at →electronic exchanges via digital brokerage systems or payments are effects without manual intervention (→electronic payment). Although information systems may be seen as application systems with strong user interaction, the terms information system, →application and application are often used synonymously. From an infrastructural perspective, application systems may be operated either →on-premise or virtually (→virtualization) in the form of →cloud computing on a →platform or decentralized on a distributed infrastructure (→DLT). In the latter case, the notion of decentralized applications (→DApp) has spread for →applications may be executed on the more recent →blockchain frameworks (→Blockchain x.0).

Fig. 7
Classification of an application system (see Alpar et al., 2019, p. 26)

Based on the →enterprise architecture concepts, the notion “4.0” emerged to denote the elements of digitalized businesses. Following →digital transformation, architecture 4.0 combines innovative technologies like →IoT and →AI with →application and information systems within an architectural setting, i.e., a framework that structures and aligns all constituting elements. Architecture 4.0 is also linked with the transformation whereas →Fintech businesses define themselves more as technology than financial businesses. This leads to increased importance of →information technology in these companies, which have turned the operation from a support function to a central and strategically relevant corporate function. Drivers are →innovation, new →information technologies such as →Big Data, →Blockchain, →IoT and →AI form the cornerstones of the →digital transformation. From the →enterprise architecture perspective, this means that internal structures and resources (e.g., →application systems like →ERP and →core banking systems) are stronger linked to external resources and that new →business models need to be considered. Examples include →data-driven products and services. Architecture 4.0 approaches build on existing →artefacts and tools of business informatics (→business information systems) and aim, among other things, at a coordinated design of technological (e.g., →application systems, infrastructures such as →DLT), organizational (e.g., cross-company business processes) and strategic (e.g., →ecosystems, →business models) aspects.

An artifact (lat. “artificial structure”) describes a model produced with a specific tool. In the context of →digitalization, numerous (mostly immaterial) artefacts exist that represent the results of design-oriented work or research (e.g., business, process and architecture models or software code). For the creation and the development of models, a variety of modeling languages has emerged (e.g., BPMN for business processes, UML for information systems), which may be used with graphical modeling tools like ARIS, Signavio or Visio. Due to their formalization, the models may be used in workflow and →RPA technologies, which enable digitalized processes.

In the middle of the twentieth century, the field of artificial intelligence (AI) emerged to denote activities that strive for realizing human intelligence by machines. Following neuroscience, intelligence is based on abilities regarding perception, processing, action and learning. Already in the 1980s rule-based (expert) systems were developed, which allowed to analyze tasks following if-then rules and suggested possible decisions or recommendations. Today, the broad availability of data (→big data) and advances in computing power, have enabled AI to extract patterns from complex unstructured data sets (input) and to learn from them or to adapt their future behavior based on past events (output). As shown in Fig. 8, AI concepts (or methods) may be subdivided in various categories with machine learning (→ML) being an important area that applies artificial neural networks whose complexity (i.e., the number of input and output layers used) leads to →deep learning (i.e., two or more hidden layers). Neural networks process predefined (so-called supervised learning) or observed (so-called unsupervised learning) input data and store the results in a network of nodes (or neurons), which calculate transition probabilities for an output or recommended action and optimize them with each iteration. Although the depth of these networks tends to improve the quality of decisions, the number of hidden layers makes the decisions of the artificial neural networks less transparent and comprehensible for humans. A general field of application is natural language processing (→NLP), where neuronal networks store correlations of words and then use them for voice recognition. Depending on the form of learning and the complexity of the application, a variety of application areas exist in the financial sector (→AI application areas).

Fig. 8
Categories of artificial intelligence

An encryption method (→cryptography) where the sender and receiver are using different keys. While both sides are using the same keys in symmetric encryption methods like the advanced encryption standard (→AES), asymmetric methods are based on a combination of public (→public key) and private (→private key) keys. The established method is →RSA, which is considered secure in the currently known computer architectures and has therefore reached broad adoption. More recently, other asymmetric methods have emerged in for →blockchain networks, in particular →ECDSA. In parallel, other recent developments such as →quantum computing are endangering existing cryptographic solutions, since these technologies are expected to solve complex prime number calculations within substantially shorter processing times.

In the →cryptocurrency environment, swaps refer to the direct transfer of →coins between users (“wallet-to-wallet”) according to the peer-to-peer model (→P2P), i.e., without the use of intermediaries (→intermediation) such as →crypto exchanges. The procedure requires a high degree of →interoperability of →DLT technologies and is considered to be disruptive (→disruption) for payment transactions.

Technologies in the field of AR expand the perception of reality by enriching or overlaying the real environment with user-specific information. Among the examples are visualizations in head-up displays (HUD) or by special interactive glasses (→wearable), which, for instance, show the product price or additional product information (such as financing information or the development of the account balance for an assumed purchase of the product). Many banks and especially →big tech companies have launched AR projects (→metaverse) since they expect large potential in the financial industry due to the high level of interaction and immateriality.

In this method of →identity verification (→KYC) users provide personal data that allow providers to verify that a person is actually the person he or she claims to be. Common authentication methods are passwords or identification numbers (PIN), identity documents or devices (e.g., smartcards, →token, badges) or biometric features (e.g., fingerprints, iris scans). Typically, the data provided by the user are validated with the data in the provider’s systems. →Identity management services have emerged to support customers in the process of signing up (→onboarding) with service providers.

Also known as →legitimation, this is the second level of →identity verification after →authentication. Here, the service provider checks whether the person is authorized to use the services (e.g., to order securities). A subsequent check in the financial sector is often the credit rating. If limits are exceeded, the authorization will typically be denied. Service providers such as the European Banking Authority (→EBA) with myBank have developed solutions for electronic authorization.

Electronic network for clearing payment orders (e.g., direct debits, credit transfers) between service providers in the domain of national and/or international payment transactions. Clearing comprises the electronic exchange (→EDI) and the net settlement of payments. The clearing of orders is typically not carried out in real time (→real-time processing), but at certain defined points in time (e.g., several times a day) and differs from the gross settlement procedure (→RTGS). Originally, the ACH term was associated with the electronic processing of checks in the US, which required 3–4 days for the clearing and settlement of a payment order. Today the term is also used globally and the systems have become more efficient (typically payment processing until the next day, t + 1). An example of ACH payment are →SEPA payments in Europe via the Step2 system, which uses the central bank accounts of the participating financial service providers in the TARGET settlement system. Providers of →payment services in the →fintech area access the services of an ACH via electronic interfaces (→API) from their national ACH systems. In German-speaking countries, the German Central Bank, Swiss Interbank Clearing (→SIC) and the Austrian National Bank, among others, operate as ACH. In Great Britain it is →BACS and in the US, among others, the Federal Reserve Bank. Compared to the ACH approach with networked national hubs, more recent decentralized approaches based on distributed ledger technology (→DLT such as →Ripple) promise more real-time and less costly transactions. However, they still fall short in terms of scalability and feature substantially lower transaction rates (→TPS).

Term used in decentralized financial systems (→DeFi) for the providers of →liquidity (→liquidity pool). Similar to securities traders or market makers in traditional stock exchange trading, AMMs offer →tokens, which are →smart contract bundles and automatically execute when there is a corresponding demand. AMMs may thus be conceived as an alternative to the →order books familiar to centralized stock exchange trading.

In the 60 years of their existence, cash machines have become important contact points for customers. They evolved from pure cash dispensers to comprehensive →self-service stations. However, they are increasingly displaced in the course of the substitution of cash with →electronic money and with the rise of other self-service solutions, in particular →e-banking and →mobile banking. At the same time, →fintech companies have launched ATMs for →cryptocurrencies (for list of →Bitcoin ATMs see https://coinatmradar.com).

This metric (→KPI) is key in →business cases of →fintech business models (→business model) and in particular of →platform-based business models, which aim at attaining large user bases to generate →network effects.

Initiative by 21 companies from the insurance sector (e.g., Aegon, Allianz, Generali, Swiss Re, Zurich) for developing the use of →blockchain technologies. Since its launch in 2016, the initiative has grown to 40 participants in 2021, among them also software and consulting companies such as MSG and TCS. The first application B3i Re involves the mapping of catastrophe loss contracts (known as excess of loss reinsurance or catastrophe excess of losses, Cat XoL) between insurance and reinsurance companies. A second use case has been announced in the field of claims management. From a technological perspective, B3i’s Fluidity platform is based on →Corda.

Describes the logic for the execution of technical functionalities and complements the →front-end, which focuses on user interaction. Among the examples are the transaction-oriented functionalities of →core banking systems as well as the distributed ledger functionalities of many →cryptocurrencies (→DLT). Back-ends are typically used via interfaces (→API).

Describes the business processes of financial service providers “behind” the →front- and the →middle-office. As back-office processes like opening accounts or processing transactions occur repeatedly along a defined and reliable workflow, the goal is to achieve high efficiencies through scale and standardization. To automate back-office operations, →core banking (or core insurance) systems have emerged since the 1960s and since the 2000s the area has also seen many attempts to outsource tasks to →third-party providers, which have the ability to achieve higher scale than individual banks (or insurances). Among the →sourcing models are in particular →transaction banks.

The Federal Financial Supervisory Authority (Bundesanstalt für Finanzdienstleistungsaufsicht in German) supervises banks, financial service providers, insurers and securities trading in Germany. It is an independent institution under public law and subordinate to the Federal Ministry of Finance. Among others, BaFin grants the licenses to conduct commercial financial activities, in particular in the field of payments and loans, and receives fees and contributions from the supervised institutions and companies. Depending on their structure, the various →fintech business models may require a →bank license from BaFin, e.g., in payments, funding or portfolio management. Although BaFin has published several statements on →fintech business models and the application of emerging technologies (e.g., →blockchain, →robo advisory, →mining services), a final assessment often requires an individual case-by-case examination.

An alternative term used in →proof-of-stake based systems for the validation and addition of data blocks in a →blockchain. It corresponds to the →mining activity in →PoW-based →cryptocurrencies. For example, each participant in the →Tezos system may act as a baker, who owns more than 10,000 XTZ, but is more likely to be selected (and paid) for it, the more →coins he possesses.

Refers to services that bundle banking and insurance services. The concept is based on a holistic view of the financial industry (so-called one-stop financial services) and assumes synergies between the two service areas. For example, customers could also opt for a property or household insurance policy or integrate life insurance into their investment portfolio when deciding on mortgage financing. Bancassurance solutions have emerged in the 1990s and have resulted in partnerships, joint ventures and mergers between banks and insurance companies. In 1997, for example, Credit Suisse took over Winterthur Insurance in Switzerland, but sold it to the French Axa insurance group in 2006 due to its unprofitable bancassurance strategy. The reasons for the failure of these early bancassurance concepts include the unwillingness of clients to entrust all financial services to one institution as well as the separate →back-end processes and systems. With the transition to more technologically affine →generations of customers and with more modular →application systems (→API banking), bancassurance approaches have experienced a second “wave” with the →fintech evolution. Today, there are partnerships in Switzerland between UBS and Swiss Re for life insurance for real estate owners, between the Raiffeisen Bank and Mobiliar Insurance for real estate ownership services, or between →fintech companies, such as the insurance →startup company Smile and the →smartphone bank Neon. In contrast, the German →neo bank N26 and the →robo advisory service Clark ended their cooperation in mid-2020 after 3 years. The different frequency of customer contact has been recognized as an important motive for bancassurance: while customers often check their bank account via →online banking, contacts with the insurance company usually only occur in the event of a loss or a claim. By cooperating with a bank, insurers may benefit from higher customer interaction frequencies, while they are depending stronger from the bank or the →digital platform used. This strategic downside has led insurance companies to launch their own multi-provider solutions (→PFM).

Identification number for banks and credit institutions in Germany that was initiated in 1970 by the German central bank. Referred to as BLZ (German for “Bankleitzahl”), it consists of eight numeric digits in Germany and a variant with five numeric digits in Austria. Since the introduction of →SEPA, the bank code has been part of the →IBAN. The first three digits of the BLZ shown in Fig. 9 identify the location number with a regional identifier in the eight clearing areas in Germany that are organized by federal states. The fourth digit specifies the affiliation with a particular banking group (e.g., central bank as well as savings, cooperative and private banks), and the remaining four digits denote the respective individual institutions. Figure 9 shows the code for Deutsche Bank headquartered in the county of Hessen (clearing area 500 for Frankfurt am Main) and the banking group (7 for Deutsche Bank and subsidiaries).

Domain-specific part within the scientific discipline of →business information systems, which features the analysis and the design of information and →application systems in the banking industry.

Certification from federal institutions (i.e., regulatory agencies like →BaFin in Germany) that awards permissions to conduct commercial financial activities. While full banking licenses cover the execution of all banking transactions, partial bank licenses focus on certain activities such as securities trading or payment processing. Depending on the services offered, the regulatory agencies assess whether a →fintech company requires a license for their →business model. The license to operate a deposit-taking credit institution is granted by the European Central Bank (ECB), in coordination with national supervisory authorities. In Germany this is →BaFin on the basis of paragraphs 32 and 33 of the German Banking Act (KWG) in conjunction with article 4 (1) of the SSM Regulation (Single Supervisory Mechanism). →Fintech providers such as Revolut illustrate the international character, as the →smartphone bank has its headquarters in Great Britain and a bank license from Lithuania. In addition, some countries have developed dedicated licenses for →startup companies in the →fintech sector that provide for simplified requirements (e.g., the so-called →fintech license issued by the Swiss →Finma). Further regulations exist for →cryptocurrencies (e.g., the application of the money laundering directive to →digital currencies or →crypto custody transactions in Germany since 2020) or →electronic money (e.g., the EU’s →e-money directive).

The →reference model presents a concise overview on all processes and functional areas of a bank. With an emphasis on universal and private banks (investment banks differ in certain areas), it structures the main business areas of a bank (payments, investments and loans) in the horizontal dimension and the main business processes (management, distribution, execution, support) in the vertical dimension (see Fig. 10). The core operational processes are reflected in the areas of sales processes on the one hand and transaction processes on the other, whereby the latter can be further subdivided into the processing of individual transactions itself and activities that are related to a specific transaction and to multiple transactions (cross-transaction). Particularly in transaction processing and transaction-related processes, there are differences along the horizontal business areas, resulting in process variants, which may be detailed further in (reference) process specifications (e.g., process diagrams in BPMN notation). In the payments area, for example, the processes differ according to the variants of →electronic payments, i.e., whether it is a card payment or a credit transfer or direct debit. Similarly, the investment area contains process variants for the various investment instruments, such as funds, derivatives or foreign exchange. →Fintech companies may use the bank model for several purposes: (1) to define their own services in the market, (2) to align their (often standardized and limited) own offering with partners in the network (→ecosystem), (3) to compare or benchmark their own services with competing services in the market, (4) to develop process variants on the basis of more detailed reference processes and (5) as a functional basis to evaluate and assign →application systems or →apps within an overall architecture framework (→core banking system, →architecture 4.0). A similar banking model is the M4Bank model developed by →BIAN.

Fig. 10
Reference bank model (see Alt & Zerndt, 2020, p. 234)

A term often used synonymously with →platform banking to denote providers of →open banking solutions (e.g., the →startup companies Mambu and Banksapi). The concept is recognized as an important enabler for embedded finance strategies (→EFI).

Automated clearing house (→ACH) in the United Kingdom (UK). The system includes the processing, clearing and settlement of payments, including the automated UK Bacs Direct Credit, to initialize and receive payments by electronic transfer.

Term that reflects the changing banking business with →digital transformation based on channel integration (→omni-channel), artificial intelligence (→AI) and data-driven solutions (→data-driven approach, →algorithmization). Banking 2.0 also captures the emergence of →fintech companies an →platform solutions (→open banking, →platform banking) in the banking sector. An example of Banking 2.0 that covers all customer groups and distinguishes the four main subject areas, online and offline channels, →smart processes and data is shown in Fig. 11.

Founded in 2008, this non-profit association of banks, software providers and academic institutions aims at definitions for banking modules that foster the networking among service providers in the banking industry. In 2018, the organization comprised 60 members in 2018, who collaborated in the development of two →artefacts. The main model is the BIAN service landscape, which presents a framework and specifications for linking services of multiple providers. By means of agreed service interfaces (→API), application functionalities of different software manufacturers and service providers (→TPP) should be designed as interoperable (→open banking) functional modules (→web service). The BIAN service landscape is currently available in its ninth version (per October 28, 2020) and comprises modules in the business areas of reference data, sales and service, operations and execution, risk and compliance, and business support. The second model is called M4Bank and summarizes the service domains of the service landscape along a value chain visualization (→bank model) with the main building blocks being business direction, finance and risk management (with operations, products, customers, channels), resource management and business development.

With the emergence of →cloud computing, many providers of →core banking systems as well as →fintech businesses have started offering →SaaS solutions for banks as well as for →non-banks. The concept is closely related to →API banking and →open finance, but emphasizes the classical approach of standard software whereas the main functionalities of a bank may be sourced from one provider. Similar to the claim of →cloud computing providers, banking-as-service relies on configuration rather than comprehensive customization to enable a quick time to market.

Refers to →innovations in the banking sector and may be interpreted as a harbinger of →fintech. In contrast to the →fintech term, the focus is on the different facets of →innovation (i.e., technological, organizational, cultural innovation in the various banking functions, see →bank model) and less on the →startup nature of the companies that are driving the →innovation. Along the design levels that are established in the →business information systems discipline, banking innovations may be structured along the levels strategy, organization and technology. An overview with examples of banking innovations is shown in Table 4 under the keyword →innovation.

To denote the application of →IoT technologies in banking processes and in →fintech →business models, BoT has emerged as a domain-specific version of internet of things. For example, smart machines (e.g., →ATMs, →smart products) might directly order their spare or maintenance parts in predictive maintenance scenarios. The embedded functionalities for ordering and payment allow banks to also provide services for the management of the machines (e.g., calculation of the replacement point, depreciation). Similar services are also conceivable in the consumer sector with the spread of →wearables and could, for example, lead to the →collaboration between banks and healthcare providers (→e-health). Other strategic business areas are also possible, such as in the area of secure storage of personal data (→IDM) for banks.

Data coding that defines the framework for an international account number. It is country-specific with up to 30 digits and it is used both at European level in the →IBAN as well as globally in the →SWIFT system. Typical components are an identifier for the bank with branches and an account number at these institutions.

Denotes a mode of executing input (e.g., function calls for processing payment order) in and between →application systems. The collection of several orders in batches may be traced back to punch card-based systems, which queued calculation orders and processed the entire batch at a certain point in time (e.g., at the end of a business day or a business month). This implied that the data in the respective →application system was only updated with a time delay and that the execution of orders required longer periods of time (e.g., payments are executed on the following day, t + 1, or even later as in the case of cross-border payments). Although digital media have replaced punched cards, batch processing still occurs, particularly in the case of interfaces between →application systems. In the area of →electronic payments, a change from batch processing to →real-time processing only occurred with the rise of real-time credit transfer systems (→RTP, →RTGS). Batch processing features are also present in →cryptocurrencies such as →Bitcoin, where →miners bundle transactions and only write the transactions after generating a new block (→Bitcoin transaction).

Abbreviation for Baidu, Alibaba, Tencent and Xiaomi, that designates the largest digital economy companies in China. Their →digital platforms include Alibaba with →Alipay, Baidu with Baidu Wallet and Tencent with →WeChat Pay and TenPay, which all comprise advanced financial service offerings. For example, →WeChat features a strong integration of the payment functionalities with the →e-commerce services offered on the →platform and →Alipay offers credits, insurances as well as wealth management services (→wealthtech) besides its (mobile) payment function.

These small computing devices may be attributed to the field of →IoT technologies and use Bluetooth low-energy technology (→BLE) for wireless communication. They open numerous use cases for location-based services (→LBS). For example, they may be placed in a bank branch office and send offers to the customers’ end device when they enter the location. PayPal also uses the technology for contactless automated payments in shops.

Describes the use of several independent applications in →application architectures (→architecture 4.0), which often originate from different providers. In contrast to an integrated →core banking system from one manufacturer, the best-of-breed approach aims at linking individual products, which are often more specialized and feature a more comprehensive functionality compared to the broader →core banking products. For example, a bank may use a →front-end application from a different provider than the →back-end application(s). The latter may differ depending on their functional scope (e.g., payment transactions, investment and lending business). Initiatives like →BIAN and →open banking may be conceived as enablers of best-of-breed architectures since they foster standardized modules and interfaces.

The term refers to →application systems that feature a large amount of structured, semi-structured and unstructured data. With the ubiquitous presence of computing devices, data has become available at an almost exponential pace. The logic of big data is to collect as many data as possible and to have it available for potential use at a later stage. Although data may initially lack a specific use case, big data systems and strategies aim to unlock the availability with potential future use cases. For example, data may serve to evaluate customer behavior and satisfaction or to detect developments in the market. The main challenge of big data is to extract and prepare the data necessary for the respective purpose from the large number (“volume”) of heterogeneous data (“variety”), which accumulate in rapid succession (“velocity”). For this reason, big data systems consist of high-performance data storage (so-called data-lakes), procedures for evaluation (→business analytics) as well as organizational regulations (e.g., dedicated big data teams, guidelines to manage big data). In the financial sector, big data has proved valuable in numerous fields of application, such as the detection of fraud, the evaluation of customer opinions or risk assessment in lending. In addition, big data strategies have to safeguard data privacy, which requires that the use of data is limited to a specific purpose and that users have agreed that their data may be used for analytical purposes (→opt-in).

Refers to the providers of →digital platforms that mainly originate from China (→BATX) and the US (→GAFA), which have developed comprehensive and widespread digital infrastructures as the basis for electronic →services in various industries. With the rise of →digitalization, these companies have moved to the most valuable companies worldwide (in terms of market capitalization), which mainly results from the cross-industry nature of their platform services. For example, the Amazon platform initially evolved from a virtual bookseller to include other products (e.g., electronics, healthcare, building supplies), whereby parts of this infrastructure have given rise to their Amazon Web Services →cloud computing services branch, which is cross-industry in nature. Likewise, Facebook has been using its social media platform as a →platform for →e-commerce (so-called Facebook Shops) for several years now. The financial industry is another application domain for the use of big tech infrastructures and most big tech companies have meanwhile embarked on offering financial services (e.g., in →mobile banking with Amazon Pay, Apple Pay, Facebook Pay and Google Pay as well as credit cards like the Apple Card). They successively penetrate into other financial services, such as investments, credits and insurances, or seek cooperation with existing providers (→incumbent). An important competitive advantage of big tech platform providers is their large user base (→network externalities), the →ecosystem of complementary devices and →services as well as their experience in offering customer-centric solutions.

These agreements exist in card payments between an issuing (→issuer) and an acquiring bank (→acquirer). An alternative are multilateral interchange fees (→MIF), which a card →scheme sets for charges from the →acquirer to the →issuer.

→Cryptocurrency founded in 2017 that is based on the →Ethereum →blockchain to handle electronic payment transactions on the →crypto exchange Binance. With the abbreviation BNB, these →tokens are also used on other →platforms. Meanwhile the →ERC-20 →token has been replaced with a native →coin on the Binance chain (BEP2).

Biometric processes that capture and record unique physical characteristics, such as face, eyes or fingerprints, and/or behavioral characteristics, such as signature, speech pattern or typing, of a person for →identity verification from an electronic device.

Specifications defined by the Institute for Process Optimization (BiPRO) in Germany regarding procedures in the insurance sector. So far, the standards are available in two releases. The first refers to basic data and process models in the field of property, accident and liability insurance (PAL) and the second to pricing, offer and application of PAL, life, motor vehicle and health insurance. The BiPRO standards are used for the structuring of documents for →electronic data exchange and for the definition of processes with corresponding electronic modules or →web services.

Provider of a global loan brokerage service for self-employed and small businesses based on →blockchain technology. The transactions are settled in →Bitcoin.

Bitcoin has become the most important application of →blockchain technology and the most valuable →cryptocurrency in terms of capitalization. The system was created in 2008 to enable electronic transactions securely and anonymously directly between trading partners without a central node. The main idea is that each participant within the network is able to view all transactions occurring in the network and holds a synchronized instance of the database on their devices. To add new transactions to this append-only database, →mining nodes with high computing power compete by solving complex mathematical equations. The successful →miners are then allowed to write the transactions in the database and receive →Bitcoins as remuneration in return. Due to the limitation to a maximum of 21 million Bitcoins, the →coins are a scarce commodity (18.77 million were already “skimmed” by July 2021) and have established themselves primarily as an object of speculation. Despite the termin “currency” suggests the availability of a means of payment, the classic functions of money (payment, value retention and value assessment) are only partially fulfilled by Bitcoins (→virtual currency). Although Bitcoins were accepted by 23,009 merchants worldwide as a means of payment (https://coinmap.org, as of August 09, 2021), Bitcoin is of little significance compared to established payment methods such as Visa, Mastercard or PayPal and can therefore only fulfill the payment function to a limited extent. However, since 2020, there has been a significant improvement in the use of Bitcoins as a payment method since major →cryptocurrencies such as Bitcoin and →Ether were included as means of payment in →payment services such as PayPal and Klarna. Due to the high volatility of the Bitcoin—the value increased from 9500 € on February 16, 2020 to almost 60,000 € on November 10, 2021 with intermediate ratings of 52,000 € in April 2021 and 25,000 € in July 2021—Bitcoin also lacks a stable retention of value. Regarding the value assessment function, values are not expressed in Bitcoin but rather on the basis of other (established) currencies, which has led to the concept of →stable coins. Further criticism of the Bitcoin system has been caused by the high energy consumption due to the →PoW →consensus mechanism, which is necessary to create and add transactions to the distributed database, and to the low performance in terms of the possible transaction volume per second (→TPS). Further developments have been addressed via →forks and have, for example, led to suggestions as defined in the Bitcoin improvement proposal (→BIP). According to the Cambridge Bitcoin Electricity Consumption Index (https://cbeci.org), the annual electricity consumption of the Bitcoin network is an estimated 112.83 TWh (as of November 29, 2021), which corresponds to around one fifth of the total electricity consumption in Germany from 2020 (approx. 545 TWh according to the German Federal Statistical Office). Other enhancements referred to the strong wearing of the →mining hardware due to high load as well as to more flexible forms of governance and higher levels in privacy.

→Hard fork of the →cryptocurrency →Bitcoin as per August 01, 2017. In March 2020 Bitcoin Cash was the fifth largest →cryptocurrency after →Bitcoin and →Ethereum, →Xrp and →Tether, but has given way to younger →cryptocurrencies (e.g., →Polkadot, →USD Coin) by August 2021 where it ranged in twelfth place (see appendix). A main reason for the →fork to Bitcoin Cash was to increase the block size from 1 MB to 8 MB and later to 32 MB.

Describes the procedure for potential improvements of the →Bitcoin system. These may comprise suggestions for changes to the →protocol or the communication rules and the software (→forks) as well as changes to the BIP process itself. Like in other →open source software projects, suggestions from developers reach the communities, which then discuss, develop and decide on them. For example, the introduction of the →Mempool was included in BIP 35 and significant parts of the →Lightning network were included in BIP 112, while the Taproot extension, which aims to speed up the consensus process and improve data protection, represents a more recent BIP.

→Hard fork of the →cryptocurrency →Bitcoin that exists since November 15, 2018. In view of the →Bitcoin Cash →fork, the main goal of Bitcoin SV (“SV” for “Satoshi vision” following the anonymous founder of →Bitcoin, Satoshi Nakamoto) was to return to the original →Bitcoin protocol with the exception that the possible size of the blocks in the database (previously 1 MB) has increased to 128 MB.

Since the first transaction on January 12, 2009, transactions of →Bitcoins have grown substantially. Following the decentralized idea of →Bitcoin, transactions occur directly between users (→P2P) without a central institution (typically a commercial or central bank) being involved. This represent an important difference to existing forms of electronic transactions and payments, which involve banks, networks (e.g., →SWIFT, →EMV) or credit card organizations (→scheme) as intermediaries (→intermediation). The decentralized architecture is enabled by →asymmetric encryption methods which assign each network participant an address that corresponds to a traditional account number or personal identification. In the →Bitcoin system this consists of a →public key, which needs to match a →private key. A transaction is then signed using the →private key and verified using the →public key. An example illustrates the process of a →Bitcoin transaction (see Fig. 12):

1.
User 1 uses his →wallet to generate an address to which user 2 should transfer →Bitcoins in the amount of the purchase price. When a new address is created, a →public key and a →private key are created that are mathematically linked to each other (→asymmetric encryption). The private key is only known to user 1 (like a PIN), whereas the →public key is used both as an address and to verify a transaction.
2.
User 2 receives the address in the form of a →QR code, scans the code with a mobile phone and agrees to transfer →Bitcoins to the →wallet of user 1. User 2 confirms the entry with her own →private key.
3.
Computer →nodes distribute the transactions via the network and use the →public key to verify that user 2 is entitled to carry out the transaction, i.e., whether sufficient funds are available to complete the transaction and to avoid →double spending.
4.
→Miners, as specialized computer nodes, transform the transaction into a →hash function, which they connect along with other transactions into a block. One block contains about 1000 transactions (the limit is 1 MB) and takes about ten minutes to be built. As per August 09, 2021, the →Bitcoin blockchain comprised 694,957 blocks (see https://www.bitinfocharts.com/bitcoin).
5.
The →miner, who is successful in the →PoW, adds a new block to the existing →blockchain and is awarded a compensation (→block reward of currently 25 new Bitcoins, which is halved every 210,000 blocks, →halving) as well as a transaction fee from the users.
6.
The →nodes store the updated version of the →blockchain, thus completing the transaction. Despite not being full real-time (due to the transaction time of ten minutes), Bitcoin transactions are significantly faster than most established →payment systems. For example, a transaction in the Euro zone currently requires one day and even several days for transactions outside of the Euro zone.

Fig. 12
Example of a Bitcoin transaction in six steps (based on Capgemini, 2020)

The Bittorrent protocol describes a data access or file sharing procedure on the basis of internet transmission →protocols (i.e., TCP/IP). Due to its efficiency in handling large amounts of data, it is used for up- and downloading large files. Bittorrent is based on the peer-to-peer principle (→P2P), i.e., the contents are not stored on servers, but rather on decentralized clients. Although there is a transparency of participants based on their internet addresses, these may be influenced by technologies such as virtual private networks (VPN). Besides being used for the distribution of large software files, Bittorrent is also known for numerous cases of illegal distribution of content. With the rise of →tokenization, Bittorrent software clients are expected to include functionality to buy and generate →tokens (e.g., the →cryptocurrency →Tron, which purchased Bittorrent in 2018).

Manifestation of a →DAG that is based on the graph-based networking of blocks.

Refers to the remuneration paid to →miners for newly created →coins in →cryptocurrency systems with the proof-of-work →consensus mechanism (→PoW). For example, in the →Bitcoin system successful →miners receive a defined amount of →Bitcoins for successfully calculating a new block, which is halved every 210,000 blocks (→halving). Depending on the current valuation of the →Bitcoin, the remuneration, also referred as →bounty, may increase to several hundred thousand Euros. This provides the economic justification for the considerable investments in the computing infrastructure of the →mining farms.

Besides directed acyclic graphs (→DAG), blockchain technology has become the most important decentralized distributed database technology (→DLT). It is linked with the rise of the →cryptocurrency →Bitcoin since 2008 and is based on the idea that transactions among users are bundled in blocks, which are distributed among all →nodes in a network. The system uses a →consensus mechanism that ensures the consistency of data stored in all →nodes. A copy of the database is stored at each →node of the network, which the database management system keeps up-to-date or synchronized. The name “blockchain” points at the →data structure, where blocks are linked. As shown in Fig. 13, a block contains several transactions that are encrypted using cryptographic methods (→cryptography) and stored permanently and publicly visible in the database. Starting from the first block (→genesis block), each block refers to its predecessor and the latter to its predecessor. For each block a →hash value is calculated, which is composed of the →hash value of the previous block, a time stamp, the →hash value of the →merkle tree and the →nonce. Depending on the respective blockchain system (e.g., →Ethereum, →Hyperledger, →Tezos), different blockchain designs have emerged regarding openness (→public/private blockchains), functionality (with →smart contracts, →side chains, →master node), →consensus mechanism (e.g., →PoW, →PoS) and block sizes (e.g., 1 MB in the original →Bitcoin system and 128 MB in the →Bitcoin SV system). In the original →Bitcoin setup, the blockchain enables payment processes without additional actors (i.e., a bank or card provider, →intermediation) directly between the interacting parties. Since payers and payees are visible only with their →hash addresses, →blockchain payments are transparent and anonymous (see →cybercrime) in the public blockchain setup at the same time. As soon as a new payment transaction takes place between two persons, the database is updated at all other participants with these new transactions, even if these participants were not directly involved in the transaction. As a result, transactions are transparent at all times throughout the payment network of all involved parties. Meanwhile, a variety of →blockchain frameworks has emerged, which differ, among other things, with respect to the →consensus mechanism, the participants (→permissioned blockchain, →public blockchain), the data organization (→data structure) or the degree of decentralization (→master node).

Fig. 13
Chaining of data blocks in the blockchain (based on Hellwig et al., 2020, p. 17)

→Blockchain infrastructure provided for a fee according to the principles of →cloud computing and software-as-a-service (→SaaS). BaaS comprises the technical infrastructure for operating a →blockchain solution as well as the software of a →blockchain or →DLT framework (e.g., →Ethereum). It relieves users from implementation or licensing issues and can immediately implement →blockchain solutions “out-of-the-box”. Providers of BaaS solutions are Alibaba, Amazon, IBM, Microsoft, Oracle, SAP or →R3.

Describes the architecture of a particular →blockchain technology, which consists of various aligned components (e.g., →consensus mechanism, data storage, →authentication, →development environment). Compared to the term →cryptocurrency, the framework term is broader than using a →blockchain or →DLT technology as a →virtual currency, as an infrastructure for →digital platforms or for →identity management. Following the model of standard software, advanced frameworks allows the development of customized solutions, especially in the context of →enterprise blockchains. →Cryptocurrencies that are considered blockchain frameworks besides →Bitcoin and →Ethereum are →Cardano, →Corda, →Eos, →Hyperledger, →Iota, →Nem or →Ripple.

→Sharding refers to separation of database contents in order to distribute the requirements of space or computing resources on multiple instances. In the environment of →blockchain technologies, →Ethereum, for example, pursues this technique with Ethereum Shards that distribute computing tasks among the →nodes to reduce the load for each →node and to increase the performance of the overall system.

Due to its →open source character, the original →blockchain technology for →Bitcoin’s →distributed ledger has experienced numerous extensions that are based on the requirements of the respective application purposes. This has resulted in so-called →altcoins and →forks, whereby the latter may be divided into →soft forks and →hard forks.

The version number of →blockchain frameworks denotes a growing range of functionalities and configuration features as well as use cases. Depending on the authors, the numbering and the respective functionalities may differ. The starting point for Blockchain 1.0 was the original →Bitcoin framework, which included a distributed database (→distributed ledger), a →cryptocurrency and a related →consensus mechanism (e.g., →PoW). With Blockchain 2.0, the enhanced functionality provided by →smart contracts and →DApps has been extended to non-financial applications. Best known examples are →→Ethereum and →Corda. Finally, Blockchain 3.0 is characterized by a variety of different distributed ledger technologies (→DLT) and enhanced abilities of virtualization, integration (e.g., →BaaS, →interoperability) and →tokenization. Examples include →Cardano, →Hyperledger, →Iota or →Tezos. Further developments of →Ethereum (e.g., →EEA, →ERC-20 →tokens) may also be attributed to the Blockchain 3.0 stage. In some cases, further version numbers (e.g., Blockchain 4.0) indicate the expansion into business applications (e.g., higher →TPS, more powerful →DApps) for →core banking applications and →ecosystems such as in the →open banking environment.

Pre-designed (out-of-the-box) modular program blocks stored in libraries for the efficient development of →DApps. While they accelerate the creation of →blockchain-based →applications, the →interoperability of blocklets is often restricted to a specific →blockchain framework. Due to this focus on specific →DLT platforms, the →interoperability of blocklets is limited.

Radio technology for data transmission over short distances (<10 m). Since BLE is built into numerous smartphones by Apple or Samsung it has achieved widespread diffusion. The advantage of BLE compared to the classic Bluetooth technology is the lower energy consumption, for example due to shorter transfer distances. BLE is often regarded as an alternative to →NFC and is used as a communication technology with →beacons, which can trigger location- and event-specific messages (e.g., actions, directions) on the respective mobile device.

While bootstrapping in computer science describes a process in which one software initiates the start of another software, in the →startup scene it describes a type of financing for establishing a business, which is based on self-financing instead of external financing. The term refers to the story of the Baron von Münchhausen, who in one of his tales pulled himself out of a swamp by his own hair. Accordingly, the company is built up from its own resources, without outside capital.

Describes a →robot to automate tasks or process steps that users have previously performed manually. A well-known form are →chatbots, where a computer system conducts dialogs with users. To “robotize” individual steps of a business process (e.g., in after sales service, →robotization), most existing bots require the definition of workflows (→RPA), but bots based on unsupervised learning (i.e. that learn their actions from past actions) are believed to rise with the advancement of artificial intelligence technologies (→AI).

A term used in →cryptocurrencies that refers to compensation for the successful generation of data fields (→mining) as a →block reward. The term is also present in the context of incentive programs, such as →crypto exchanges (e.g., →Binance), as compensation for an active use of their offerings.

Interim financing of a privately-owned company until the company goes public. This is often a short-term form of financing, which builds a “bridge” to longer-term financing that is not yet available. Providers are traditional banks as well as →crowdlending companies.

Business model of an intermediary (→intermediation), who mediates between buyers and sellers. While →aggregators act as independent traders, brokers do not take the →services into their own books but charge a commission for their →services. Brokers are established actors on financial exchanges (→electronic exchange) where they execute orders from customers. With →digitalization, online brokers have become established (e.g., Consorsbank, Onvista) as well as →electronic markets with brokerage functions, which enable performance comparison between competing providers (e.g., Check24, Verivox).

Term from the insurance field, whereby customers mandate a →broker to assist them in finding suitable offers and prices. The broker’s mandate forms the contractual basis for the rights and obligations as well as for the remuneration of the →broker (→intermediation). The revenue model may be commission-based (the intermediary calculates a commission based on the transaction value) or advice-based (the customer pays a consulting fee), whereby the latter variant ensures greater neutrality vis-à-vis the providers. The broker’s mandate often remains after the insurance contract has been signed, allowing the broker to suggest contract alternatives and improvements. While insurance brokers such as MLP exist for some time already, →digital insurance brokers have emerged with →digitalization.

Describes the use of →IT for decision support and includes methods for analyzing data as well as technologies used for this purpose. Three generic methods may be distinguished: methods for descriptive analytics, which examine historical data, methods for predictive analytics to predict future events, and methods for prescriptive analytics, which determine an optimal or best solution from various available alternatives based on known parameters (see Fig. 14). On the technological side, business analytics comprises technologies for data storage and processing (→big data), for data analysis (e.g., data mining) and for data visualization (e.g., cockpits, dashboards). In some cases, the descriptive procedures are also considered as part of the term business intelligence, which has been used for a long time. Despite this offers a convincing distinction, business analytics and business intelligence are often used synonymously. In the →fintech context, many →fintech companies have applied business analytics as a primary or supporting component of their →business model. Among the examples are credit assessments and the analysis of account data in personal finance management (→PFM).

Fig. 14
Forms of business analytics (see Gluchowski, 2016, p. 277)

Natural or legal person investing in a →startup or →fintech business. In general, these investors tend to provide small amounts of money in →seed or →startup phases, but rarely in stages of higher maturity. Compared to →venture capitalists, business angels are likely to be less interested in profitability, especially if they are friends or family members.

Being an important part of a →business plan, a business case allows investors to assess the profitability of a business project by detailing the costs and revenues over several periods (e.g., 3–5 years). Typical quantitative elements are the anticipated development of costs, revenues and efficiency gains, as well as non-monetary elements such as benefits, risk and potentials. These are also linked with assumptions for different scenarios (e.g., “best-case”, “realistic case”, “worst case”). Common metrics in business cases for →fintech companies are the number of active users, the average revenue per user (→ARPU), the revenue sources (e.g., from advertising and transaction fees) and the costs of operation (e.g., personnel, software development, →IT operations, →CIR) and advertising.

BIC is an identification data standard introduced by →SWIFT for participating banks also referred to as “SWIFT code. It was initially known as →bank identifier code and renamed to business identifier code” as it became an →ISO standard 9362 in 2008. Today, the two versions 2009 and 2014 exist. As uniform worldwide accepted code it is used in international payment transactions via the →SWIFT network and supplements other numbering systems such as →IBAN for international payments outside the →SEPA area and even replaces them in some countries. BIC is structured in eight to eleven alphanumeric digits, depending on whether the optional branch identifier is included or not (see Fig. 15).

Scientific discipline that is also referred to as business informatics or (management) information systems. It is concerned with understanding and designing information technology (→IT) as well as their implementation with engineering methods and the economic and sociological assessment of →digitalization measures. As shown in Fig. 16, BIS combines knowledge from three scientific domains. First, computer science provides the technological foundations in the area of hardware and software (e.g., →AI, →big data, →blockchain, →IoT), second, engineering science provides content for the systematic construction of systems (e.g., architectures, development methods) and, third, economics provides the link to the application domain (e.g., finance). The BIS field has evolved since the 1970s and is now seen as an independent scientific field that understands and designs information systems as socio-technical systems. This includes the effects on new business processes, products and →business models, the design of business →application systems, the analysis of costs and benefits as well as organizational questions (e.g., the organization of the IT domain).

Fig. 16
Positioning and topics of business information systems

Describes the development, positioning and sustainability of a business solution in the market. Business models are typically derived from a more general business strategy and decompose a new business concept along several dimensions to make it amenable for being designed. Among the important elements are the value proposition (i.e., what differentiates the solution in the market?), the revenue model (i.e., how does the company make money?) as well as the core architectural elements and resources (i.e., what are partners, channels, customer segments). An established model for structuring the elements of business models is the →business model canvas, which has also spread in the field of →fintech →startup businesses.

A model to structure →business models according to nine dimensions (customer segments, value proposition, channels, customer relationships, key resources, core activities, key partnerships, revenue sources, cost structure). Companies include the business model canvas in their →business plans and complete these dimensions mostly in verbal form. The template is used in the →startup phase as well as for regular reviews to reassess a chosen →business model. Figure 17 illustrates the BMC using the example of the German →neo bank N26. Since the development of the BMC with the dissertation of Alexander Osterwalder in 2004, numerous developments of the BMC have taken place. These include supporting tools such as Strategyzer and instantiations for →smart services or →data-driven services with the service model canvas as well as the data-driven business canvas (DDBC) model.

Fig. 17
Business model canvas for neo bank N26 (Sources: LumosBusiness, 2019, Strategyzer.com)

The networking among companies is inherently linked with the division of labor and may be organized via market, hierarchical or hybrid (i.e., cooperative) forms of governance. In contrast to the atomistic and competitive nature of market mechanisms, business networks are based on the medium to long-term cooperation (→collaborative business, →sourcing) between two or more legally independent organizations. In the financial industry, the vertical disintegration (→unbundling) has increased the importance of business networks and may be found in the form of →outsourcing partnerships as well as in the concepts of →open banking or →ecosystems. In reality, business networks exist in various forms, from bilateral to multilateral solutions or from business networks with one dominant partner (so-called focal networks with an →integrator) to networks that are more democratically controlled by several partners or completely decentrally organized networks (e.g., →DAO). As a result of the increasing cooperation between classical financial service providers (→incumbent) and →fintech companies, networking opens up advantages for young innovative companies such as access to additional knowledge, to larger target groups or to economies of scale via the pooling of resources with other organizations.

Compared to the →business model, a business plan not only shows the idea and the main elements, but also describes how a →business model is implemented. It includes the presentation of the business idea and business goals, as well as specifications regarding a market analysis and a marketing, production, personnel and sales plan. Usually the business plan also includes the →business case in terms of the finance plan. The business model canvas (→BMC) is often a helpful tool for deriving and structuring business plans on a higher level.

Denotes the →outsourcing of a comprehensive business function to a service provider (→TPP). In the BPO model the responsibility and execution of entire operational functions like the scanning of physical documents, the processing of transactions (→transaction bank) or administrative processes such as purchasing, accounting, real estate management or payroll, are transferred to service providers, who define their core competencies in these areas. Typically, BPO services include the software and the hardware that is necessary for executing the respective business function. Technological concepts, such as service-oriented architectures (→SOA) and →APIs that aim at modularity have supported the emergence of BPO ecosystems (→open banking) with shared infrastructures being a potential enabler (→DLT). As an infrastructure for cooperation between several players (→collaboration), →DLT technologies may be expected to contribute to the efficiency of BPO relationships and enable new, more decentralized and distributed cooperation models.

Process variant in economic transactions that decouples the purchase and the payment. Typically this applies to purchases on account, credit card payments as well as credit financing. BNPL services (e.g., Afterpay) are increasingly included in →e-commerce presences to provide comprehensive coverage of →customer journeys.

The concept of reaching →consensus among distributed actors is based on the history of the Byzantine generals, who had to agree on a common course of action but had to assume to have traitors in their own ranks. An →algorithm was conceived to ensure that the decision was based on loyal actors and that disloyal generals could not influence the decision. This situation has found its way into secure communication in multi-agent systems (e.g., business or computer networks) and led to the →PBFT algorithm. According to it, the procedure tolerates up to one third of untrustworthy (or faulty) network participants among a defined number of participants, who communicate among each other before reaching the decision. This leads to a large volume of communication (→gossiping), in particular if many participants are involved. The runtime increases quadratically with each additional participant. In the →blockchain or →DLT environment, →consensus mechanisms such as →PoW or →proof-of-stake have therefore become more widespread for solving the Byzantine agreement problem than →PBFT.

Refers to the observation of (price) developments on various markets (stocks, foreign exchange, →cryptocurrencies, etc.). The aim is to identify a time (or level) to buy (call) or sell (put) products on the respective market.

Cardano is a →cryptocurrency that aims to avoid many disadvantages of existing →cryptocurrencies (e.g., interoperability, security, →scalability) and may be allocated to the blockchain 3.0 technologies (→blockchain x.0). It pursues an open approach (→open source), which is intended to ensure transparency for participants and regulators. The →coin used is ADA.

CAVE is a three-dimensional virtual space consisting of projected walls, floors and ceilings. Users move in this virtual space and may individually control their activities by means of electronic input (e.g., joystick or data glove) and three-dimensional visualizations via VR glasses or head-up displays (HUD). CAVE systems have been used for some time for construction processes (e.g., in the automotive and construction industries) and are attributed ample potential for virtual communication (e.g., conferences, product presentations) that could in particular benefit service businesses like →fintech.

These →virtual currencies issued by central banks have received increased attention with the rise of →cryptocurrencies. Two major forms may be distinguished: on the one hand, a CBDC is used among financial service providers (banks and →non-banks, so-called Wholesale CBDC) and on the other hand among banks as well as private households (so-called Retail CBDC). Although CBDCs could also be implemented with other (e.g., more centralized) technologies, the concept has spread with the use of →blockchain or distributed ledger technologies (→DLT). As digital →fiat currencies, such →govcoins should improve the efficiency of cross-border payments, the prevention of money laundering (→AML), and the implementation of automated solutions in the environment of →smart products and devices (→IoT) through →smart contracts (e.g., →tokenization). Several initiatives have been initiated by central banks worldwide, e.g., the Retail CBDCs with the E-Yuan of the People’s Bank of China, the E-Euro of the ECB (→Euro-on-Ledger) or the Wholesale CBDC “Project Helvetia” of the Swiss National Bank. In contrast to CBDC, there are private initiatives for →electronic money such as →Diem.

→Cryptocurrency →protocol based on →Ethereum, which aims at linking data (e.g., documents, events, certificates) held outside of a →blockchain system (→off-chain) to the →blockchain system (e.g., via so-called →oracle services). Chainlink uses its →token LINK to clear payments between network →nodes and applies →smart contracts to analyze data from →oracles. The →protocol has become the basis for other →cryptocurrencies such as →Aave and →Polkadot.

Refers to a small, often only recently founded retail bank (hence the sometimes synonymously used term →neo bank) that challenges established banks (→incumbent) starting with a focused range of services. The →innovation of challenger banks lies in the use of innovative, often disruptive →information technology (→disruption), for example, an online-only strategy (→smartphone bank) or the use of artificial intelligence (→AI) in the form of →chatbots. Like many →fintech businesses, challenger banks combine their limited service offering with the claim of a reduced complexity of their solutions compared to traditional banks and aim at achieving process efficiencies via process standardization. Examples of challenger banks are Fidor or N26 in Germany and Monzo or Atom in the UK.

Refund of a payment amount by the credit card company to the credit card holder as a result of an allegedly incorrect charge. The reasons for an incorrect debit may vary from suspected fraud to the reclaim of the payment by the cardholder. The identification of these risks and the handling of the associated processes has become a business segment of →fintech (e.g., Square, Signifyd) and credit card companies (e.g., Accertifi, Verifi).

This form of →crowdfunding focuses on the collection of both small and large payments (donations) from private and institutional donors for a charitable purpose (→crowddonating).

These information systems support interactions between a user and an →application system via natural language interfaces. This may occur either by entering free text in a conversation window of a web page, or by (oral) speech input via the microphone of a terminal device. Chatbots offer two key potentials: on the one hand, they present a low-threshold interaction without the need of being familiar with an →application system and its navigation and command structure, and on the other hand, the user input can trigger or automate further business processes (→robot, →bot) by means of automated language processing (→NLP). A basic distinction is made between application-specific chatbots that refer to a domain (for example, the banking sector) and generic chatbots that provide access to a large number of domains through programmed interaction routines (so-called skills). The latter include the well-known assistance systems of Amazon (Alexa), Apple (Siri), Google (Assistant) and Microsoft (Cortana).

A CDO is an organizational role with responsibility for leveraging and coordinating →digitalization potentials in a company. CDOs often complement the more technically oriented IT manager as or chief information officers (CIO) and rather pursue a more business-oriented perspective. The tasks may include the →digital transformation of traditional (banking) business as well as the development of new business areas in the →fintech sector. In →fintech companies, the role of the CDO often falls directly to the CEO (chief executive officer). In addition to advising the executive board, powerful CDOs are able to exert influence via a hierarchical position as line managers with own budgets and, if possible, even as member of the executive board.

A payment transaction via →ATM or →POS systems requires a merchant bank that clears the transaction using a direct debit from the buyer’s account and credits the amount to the seller’s account. In the case of →on-us transactions, payments may be processed bilaterally between the seller and the merchant bank (garage clearing) or via a centralized interface within a group bank (e.g., DZ Bank in Germany for the cooperative banking sector). More commonly, however, payment settlement occurs via a central interface as an →off-us transaction (e.g., via garage clearing, a central bank or an →ACH).

Computer architecture that distinguishes between the two roles of a resource provider (server) and a resource consumer (client). The client-server principle has replaced the centralized mainframe architecture principle and is today present in corporate →application systems (for example, →core banking system, →ERP). It is also found in the non-P2P (→P2P) forms of distributed ledger technology (→DLT), i.e., if this technology has centralized computing resources (such as a central registry), which is often the case with →enterprise blockchains.

In contrast to traditional locally implemented computer systems (→on-premise), cloud computing refers to digital services that are hosted (centrally) on a server. Users typically access the resources of the cloud computing service provider via a network and use them for a fee. For the user, this initially means that the remote services replace their own IT resources and that fixed costs are “variabilized”. The so-called cloud computing stack distinguishes between three types: At the lower hardware level, infrastructure-as-a-service (IaaS) services comprise storage and/or computing resources, platform-as-a-services (PaaS) extend IaaS with developer resources (e.g., Elinvar in private banking), and software-as-a-service (→SaaS) solutions include the “higher” or more application-oriented functionalities (→applications). Dominant third party service providers (→TPP) like Amazon Web Services, Google or Microsoft Azure cover several of these categories on a transaction or volume basis and/or offer subscription models. Due to their ability to scale even for large amounts of transactions as well as due to their economies of scale, they are also considered hyperscalers (→hyperscaling). Despite concerns of data privacy and data security have delayed the adoption in the financial sector, many offerings of →core banking systems have become cloud-based and solutions such as blockchain-as-a-service (→BaaS) and →bank-as-a-service have appeared. The latter allow financial service providers and in particular →startup companies in the →fintech sector to establish their own solutions in a short time. For financial service providers, in particular, the location of the provider’s data centers is relevant since national jurisdiction applies.

Describes the provision of workplaces and infrastructure by a service provider (→TPP). The rented office space includes, for example, internet access, meeting or catering rooms as well as the use of office supplies and technical infrastructure (e.g., beamers, large screens, audio/video systems). The usage conditions are variable and thus suitable for pay-as-you-use scenarios (→PAYU). Furthermore, the shared use of resources (→sharing economy) allows →startup companies to quickly establish office presences and to obtain access to a →startup ecosystem (e.g., legal advice, developer resources, →investors, other →startup businesses).

Similar to the term →unicorn, a cockroach is a →startup that has reached an estimated market capitalization of one billion US dollars or more. The term refers to a venture capital (→VC) investment strategy that values a stable over an above-average growth. This often implies a rather slow, steady and sustainable growth of the company.

Cognitive data processing refers to the use of artificial intelligence (→AI) technologies (e.g., →machine learning, →deep learning, data mining) to simulate the way humans learn and think. The aim is to enable systems to learn independently on the basis of experience and large amounts of data (→big data). As shown in Fig. 18, cognitive computing describes the highest level of learning ability after (1) →desktop automation (→RDA), (2) robotic process automation (→RPA) and (3) →virtual assistants. Fields of application in the financial sector are speech and face recognition (e.g., →identity verification), →sentiment analysis or risk assessment as well as fraud detection.

Fig. 18
Development stages of cognitive computing (examples of systems shown in italics)

Coins are exchange objects and units of account within traditional as well as within →cryptocurrencies. The analogy to a coin underlines the intended use of →virtual currencies for payment transactions or other functions. Although (electronic or cyber) coins are often used synonymously with →tokens, they refer to a native →cryptocurrency whereas →tokens enhance these coins. For example, the →ERC-20-token is built on the →cryptocurrency →Ethereum and being used for payment, security or other purposes (→payment tokens, security tokens, →utility tokens).

Term used in →cryptocurrencies to withdraw →coins from circulation and thereby reduce the total amount of available →coins. The procedure triggers a so-called burn function (e.g., via →smart contracts), which irrevocably deletes →coins at defined points in time (e.g., quarterly), with the number depending on the volume of transactions carried out in the quarter in question. The concept of burning coins is present in the proof-of-burn →consensus mechanism (→PoB).

Refers to the offline storage of →coins or →tokens, i.e., either on paper via printed hashes (→hash value) or on devices that are not connected to the internet (e.g., USB sticks). In contrast to →hot storage, such offline solutions are considered to be safer against →cybercrime (if held in a secure physical location), but often less user-friendly since they only support a small variety of →cryptocurrencies.

In contrast to the (negative) connotation as cooperation with the enemy, in a more positive sense collaboration aims at the coaction, bundling or alignment of several resources, activities and/or actors to achieve joint or higher-level objectives. Among the examples are the shared use of goods or services (→sharing economy), as well as the execution of a business process that coordinates the resources of the parties involved to achieve the best possible result (e.g., in terms of time and costs), or the collaboration of several service providers within a →business model (→sourcing, →ecosystem). Collaborative processes often feature a higher degree of interactivity among the participating partners and thus create higher →transaction costs, which in turn may be contained with information technology (→IT). Since →digitalization improves coordination (i.e., the management of dependencies) and tends to reduce →transaction costs, it favors the emergence of collaborative processes and →business models (→collaborative business). A recent example is the concept of embedded finance (→EFI).

Describes the cooperation of multiple organizational units along a value chain, both horizontally (competitors) and vertically (suppliers and customers). Ideally, in such networked →business models (e.g., →open finance) the participating organizations bring in their respective core competencies and the →collaboration takes place on the one hand in various →sourcing models between the individual organizations and on the other hand in a larger →business network or →ecosystem. For →fintech companies, collaborative processes and →business models are key since they enhance the resource base (e.g., market reach, customer base, service portfolio, economies of scope). At the same time, they require the management of these dependencies with external partners (e.g., via network governance structures).

Refers to the sharing of resources or goods within a group. An essential aspect is the sharing of the cost risk when purchasing the goods or →services, as this risk is spread over a larger group. Amortization is achieved through sharing, for example via a predetermined internal accounting model. Another motivation is to contribute to the sustainable use of scarce resources. A typical example is the shared use of vehicles or real estate, such as office space in →co-working spaces (→sharing economy).

Refers to the cooperation of individuals or teams, often from different organizations, on a topic or within a project. It is irrelevant whether the persons or teams know each other or not. Working in cross-functional as well as in cross-organizational teams has become an important aspect of agile approaches like →Scrum and are typical for →startup and →fintech businesses.

Describes a form of community financing where financial transactions are carried out directly between individuals (→P2P), without the intervention of a traditional financial institution or an intermediary (→intermediation). Due to this direct →collaboration between lender and debtor, credit transactions are more personalized (→personalization) compared to traditional bank loans and more flexible regarding the purpose of the credit, interest rates, security requirements, terms and debt rescheduling. Since credit risk checks are more important for classical financial institutions, collaborative finance instruments are often more appropriate for higher risks since they emphasize the credit’s purpose.

Collective intelligence, also referred to as group or swarm intelligence, is based on the aggregation and processing of large amounts of data (→big data). It describes a research area of artificial intelligence (→AI) and is based on the →crowdsourcing approaches known in the →fintech area. An example in the area of →crowdinvesting is the Sentifi, who derives investment recommendations from social media data.

Based on the →cryptocurrency →Bitcoin, colored coins were created to represent assets such as real estate or securities. Examples are the →ERC-20 in the →Ethereum →cryptocurrency, which serve as fungible tokens to identify a class of goods (→utility token). Colored coins may be understood as predecessors of →token for non-fungible goods (→NFT).

A data center operation strategy, which refers to the consolidated operation of physical →IT resources (e.g., data servers, application servers) in a data center. In contrast to →cloud computing providers, colocation service providers offer physical space in racks or cabinets for hardware that remains the property of the customer and also corresponding services for migration and maintenance. Among the advantages are economic and ecological benefits as well as the possibility to maintain high levels in data security and high bandwidth network links (e.g., to systems of →electronic exchanges). Large financial service providers as well as →fintech businesses, which operate their own hardware due to sensitive data, have increasingly adopted colocation concepts for their own (often leased) hardware. Among the providers of colocation services are Cyxtera, Equinix and Interxion.

Measures against terrorist financing aim to prevent financial transactions that support political, religious or ideological objectives through violence and/or the threat of violence against civilians. The identification of such financial transactions and their sources should help to improve law enforcement and prevent possible terrorist activities. CFT is a core component of the payment functionality in →core banking systems and is part of →business models in the →regtech segment.

This key performance metric (→KPI) is widespread in the non-life insurance sector and shows the relationship between claims payments and administrative costs on the one hand and insurance premiums received (without investment incomes) on the other (see Fig. 19). Similar to the cost-income ratio (→CIR) for banks, a value below 100 indicates a profit and a value above 100 that more money is paid for claims than being received via premiums. In 2018, German property insurers had an average combined ratio of approximately 94.1% (GDV, 2020).

Fig. 19
Calculation of the combined ratio

Founded in the 1960s as part of the American Bankers Association, the CUSIP code has become the most important identification system for securities in the US and Canada. Today, it forms the →NSIN in this geographic region and is thus a component of the →ISIN for securities and financial instruments listed there. CUSIP consists of nine alphanumeric digits and can be converted into the →ISIN as a national securities number (→NSIN). Figure 20 shows this for the Bank of America share.

Fig. 20
Structure of CUSIP (left) and transfer to ISIN (right)

Denotes the concept of “banking among friends”, which includes: (1) financial transactions between customers (→P2P) who are familiar with each other (e.g., via chat), (2) offering incentives to customers who are actively involved (e.g., via their reports or reviews of financing possibilities) to create transparency and (3) financial transactions of customers with other (previously unknown) customers within the community. Community banking differs from traditional banking since community banks provide debtors with funds that the local community has collected or generated itself. This enables individuals in a neighborhood or group to have more control over the origin and use of funds and thus influence goals such as sustainability. An example of community banking is Fidor Bank, which has introduced the concept where customers advise customers. Community approaches have also appeared in the insurance industry with Lemonade in the US or Friendsurance in Germany.

Describes the tasks to ensure compliance with legal regulations, internal company guidelines or voluntary rules. For businesses in the financial sector, compliance obligations result in particular from the national →banking or insurance license. In the context of technological change, regulations for compliance are known to occur only with a delay. This has become visible with many →fintech segments where existing regulations were initially not applicable to new services like →robo advisory, →crowdlending or →crypto exchanges.

Achieving consensus is key in environments where multiple distributed actors aim to obtain a single source of truth (→SPoT) on events, property rights, transactions and other data. Mechanisms to attain such consensus (→consensus mechanism) have become widespread with distributed database systems, which strive for consistency of data that is decentrally stored at multiple locations. Although the concept of distributed databases has a long tradition, it has received large attention with the emergence of →blockchain and distributed ledger technologies (→DLT). In certain →blockchain applications (e.g., →Bitcoin and →Ethereum), the network →nodes have to agree on different versions of the respective →ledger database. To attain this consensus on the current state of the →blockchain, they use various forms of →consensus mechanism or consensus formation algorithms.

→Consensus mechanisms are procedures to ensure that all nodes involved in a →blockchain or distributed ledger network (→DLT) agree on the true and valid state of the database. The →consensus mechanism is key for building trust between the →nodes or organizations involved, since decentralized peer-to-peer networks (→P2P) lack a central trustworthy entity (→intermediation, →TTP). Thus, the →consensus mechanism ensures the single point of truth (→SPoT) in distributed environments with numerous participating →nodes. Depending on the rules and the →algorithm applied, a variety of consensus mechanisms has emerged (see Table 1). Based on various proofs (e.g., computing effort, invested assets) they first determine, which node is authorized to extend the database which will then be replicated among all distributed instances of the database. Second, depending on the trust among the →nodes, a validation of the generated results needs to occur prior to the modification of the database. If trust is not given (→Byzantine agreement) and actors cannot trust each other, the procedures typically require a majority of nodes to validate the modifications. With →Bitcoin as the largest →cryptocurrency, the proof-of-work (→PoW) mechanism is most widespread with proof-of-stake (→PoS) following in various variations (e.g., →PoA, →PoC).

Table 1

Overview of consensus mechanisms

→Practical Byzantine Fault Tolerance	→Proof-of-activity
→Proof-of-burn	→Proof-of-capacity
→Proof-of-elapsed time	→Proof-of-importance
→Proof-of-reserve	→Proof of-stage
→Proof-of-work	→XRP LCP

A generic form of →blockchain governance besides →public and →private blockchains. In this case, the members of a consortium decide on the admission of new members (→nodes) and the rules for the generation or validation of new data records or blocks according to a defined voting procedure (→consensus mechanism). Depending on the configuration, the →blockchain may be both publicly readable and restricted to certain →nodes. Well-known consortium blockchains in the financial sector are →Corda of the →R3 consortium consisting of numerous banks and →B3i, a consortium from the insurance sector.

Construction technologies aim at →IT-supported digitalized processes (→digitalization) in the construction industry in order to streamline processes in the management of construction projects (e.g., construction planning) and buildings to reduce construction and operating costs. For example, contech solutions may contribute in detecting errors in planning in real-time (→real-time processing) and propose appropriate measures and solutions. Contech is considered a form of →proptech and has numerous relationships with the financial or →fintech sector through financial tasks (e.g., rental processing, financing, insurance).

Financial instrument based on price changes of underlying assets (e.g., shares, indices, →cryptocurrencies, commodities). In a CFD transaction, securities (so-called margins) must be deposited with a →broker that correspond to a fraction of the total price (e.g., one tenth). Changes in the underlying asset have a 1:1 percentage effect on the margin and lead to gains or losses. If the underlying asset rises by 10%, the margin also increases accordingly.

The →DLT framework developed by the →R3 consortium aims to support financial transactions between companies via interoperable cross-organizational →application systems (→enterprise blockchain, →interoperability). Corda should enable organizations to create individual solutions and use different →consensus mechanisms. With Corda Enterprise, a business version has been created that connects the →blockchain to →off-chain resources such as SQL databases (→off−/on-chain).

Integrated →application system for service providers in the banking sector, which comprise a wide spectrum of core business functionalities. Following the concept of integrated business application systems (→ERP), core banking systems feature a centralized database, application-wide aligned functional modules and cross-functional processes. To meet these requirements, core banking systems should support at least two of the three customer process categories (according to the →banking model: payments, securities, financing) with the associated core processes. This encompasses a broad coverage of transaction-related functionalities in the areas of transaction as well as transaction-related and cross-transaction processes (see Fig. 21). Since transaction processing (→OLTP) is a key component of core banking systems, they are often referred to as booking engine. Although comprehensive core banking solutions also offer functionality in the areas of management, sales and support processes, these areas are often covered with dedicated →application systems, such as customer relationship management or business intelligence systems (→business analytics). Over the years, core banking systems have increasingly adopted a modular design (→SOA) as well as →platform architectures. For example, they feature directories including all functional modules like in an →app store, which might also contain →applications from external providers in the sense of →open banking. The →platform also represents a runtime environment that executes applications via defined interfaces (→API), which has motivated the terms →API banking or →bank-as-a-service. The latter also includes the hosting of the core banking solution by a service provider (→cloud computing).

Fig. 21
Functional areas of core banking systems (see Alt & Puschmann, 2022)

Cooperation of large companies or groups with →startup companies. Established companies may act as →incubators for the →startup organizations, but also as a classic investors or business partners. A frequent challenge for the large company is to integrate the results of the →startup with the remaining organization.

A →blockchain framework based on →Tendermint that enables the creation and operation of →blockchain-based applications with a development environment (→SDK). It aims at attaining →interoperability of different →blockchain frameworks. For example, the →Binance coin framework uses →Tendermint and Cosmos.

This key performance indicator (→KPI) serves to assess the operational performance of a financial services company and comprises all expenses and income (see Fig. 22). It ranges between 70 and 80% for larger universal banks, while the more specialized →direct banks and →fintech companies without a branch network often feature a CIR between 40 and 50%. Among the main cost drivers of the CIR in financial service organizations are personnel and infrastructure (e.g., material expenses in buildings and →IT).

Fig. 22
Calculation of the cost-income ratio (see Alt & Puschmann, 2022)

A form of decentralized portfolio management (→robo advisory) where →blockchain or distributed ledger infrastructures (→DLT) enable individuals to view and to follow portfolios of professional investors. Following the logic of →P2P asset management, followers copy the trades of these investors by executing orders themselves or empower the system to automatically mirror the entire investment strategy.

A measure for network goods that rely on the participation of actors and creates →network effects that may be positive or negative in nature. The critical mass then refers to a minimum number of participants, which is necessary for →network effects to take off. For →platforms like →electronic markets, critical mass is determined by the transaction volumes which influence the →platform’s →liquidity. However, as a socially determined variable, critical mass is difficult to calculate and strongly depends on the market segments as well as the expectations of the participants.

As an instrument of strategic management, CSF refer to measures and/or determining conditions that positively influence whether a predefined goal will be reached. Although CSFs should not be confused with strict causal relations, they are based on past experience and suggest that the presence of these factors is linked with a high probability that the intended goals may be attained. CSFs are often linked with a →business model, a →business plan or other strategic measures (e.g., a new market strategy, a new →e-business strategy, a new form of →electronic payment). →Fintech →startup companies are regularly referring to CSFs when presenting their idea to venture capitalists (→VC) and →startup businesses as well as →incumbents are using CSFs to prioritize activities.

In the case of →cross-border payments, a cross-border hub connects national card →payment systems with other national clearing systems. This is the case within the European Union as well as with countries outside of the European Union. In contrast to national transactions, these contact points (or hubs) are present in one or both countries as additional actors in the process flow, controlled by the respective →scheme, and thus they entail additional costs and, in some cases, also delays due to transit times. Cross-border hubs are limited to the forwarding of transactions and do not offer other services to the parties in the →four-corner model.

Cross-border payments include transactions outside the home country in different currencies. In the traditional setting, they take place via →cross-border hubs, which often involve additional transaction times and transaction fees. With the rise of →cryptocurrencies such as →Ripple, new solutions have emerged that replace these inefficiencies while challenging existing competitors (→incumbent) such as →SWIFT, which have introduced new solutions themselves (e.g., SWIFT gpi).

Similar to →multi-chain, cross-chain refers to transactions between two →blockchain systems. The →interoperability of these systems is determined by their structure: if key parameters of the →blockchain systems, such as consensus and security mechanisms or the type of participants (public, closed), are identical, then integration is directly possible. If, however, both systems differ in either of these aspects, an additional role is required to align the different systems (e.g., a →validator as in →Polkadot, →CLI).

In view of the growing need to exchange data between distributed ledger systems (→DLT), CLI addresses the →interoperability problem and recognizes that in the emerging →token economy the assets (→digital asset, →token) and the associated →smart contracts are often linked to a specific →framework. The field of CLI thus comprises technological concepts (e.g., →cross-chain, →multi-chain) that enable cross-chain trading as well as cross-chain business processes and models.

Describes activities carried out by numerous individual actors, which by aggregation on a higher level, yield additional capabilities and insight. Examples in the financial industry include the fields of →collective intelligence, but also the creation of sufficient →liquidity to merit peer-to-peer (→P2P) →platforms, such as →crowdfunding with →crowddonating, →crowdinvesting and →crowdlending, →crowdinsurance as well as →crowdrewarding, →crowdsourcing, →crowdtesting and crowdworking.

While →crowdfunding focuses on investors that provide financial resources, crowddonating denotes supporters that donate resources without expecting anything in return. Supporters may be natural persons or legal entities that pursue a humanitarian, social or cultural goal. Crowddonations are conducted via →digital platforms such as Betterplace.org.

Form of financing where a large number of investors provides capital directly to capital seekers. The capital is generally earmarked for a specific purpose, i.e., recipients must use it for the project, product, movie, etc. that is being described on the →platform. The remuneration of the investors is often non-monetary, for instance, in the form of products or the inclusion of the name in the credentials of a movie. The main forms of crowdfunding are →crowdinvesting for providing capital to →startup businesses, →crowdlending for providing loans, usually with fixed interest rates, and →crowddonating for financing through donations. As also shown in Table 2, the various purposes are linked with different types of →tokens.

Table 2

Types of crowdfunding (based on Ackermann et al., 2020, p. 282)

Type	Purpose	Token	Motivation
→Crowdinvesting	Acquisition of company shares	Security token	Return on investment Realization of an idea
→Crowdlending	Purchase of (capital) goods	Asset-backed token (→stable coin)
→Crowdrewarding	Financing as countertrade	→Utility token
→Crowddonating	Funding for good causes	→Payment token

Refers to the provision of equity capital, subordinated loans or similar products by a large number of investors, which may comprise both individuals and legal entities. These equity investments often provide capital for →startup businesses, rather than fixed-interest loans as in →crowdlending. Crowdinvesting is made directly to the borrower via →digital platforms without the participation of a bank as intermediary (→intermediation). Banks often only acts as a service provider in the processing of the transaction, but not as investors. Examples for crowdinvesting →platforms are Companisto, Exporo or Zinsland.

Similar to →crowdinvesting, crowdlending or →peer-to-peer lending, refers to the provision of debt capital for specific goods (e.g., for investments) by a variety of investors (both natural and legal persons). As an alternative to traditional bank loans (e.g., corporate loans), financing is also provided directly to the borrower via →digital platforms. Although banks may participate in the platforms as commercial lenders, they are often only used as liquidators and no longer to hedge against credit default risks. Analogous to an “eBay for loans”, credit brokerage platforms conduct credit auctions, in which borrowers (individuals or groups) specify the required loan amount and their maximum interest rate, and lenders (commercial lenders are subject to approval by the banking supervisory authorities such as the →BaFin) specify the loan amount to be granted and the minimum desired interest rate. The →platforms then match the offerings according to the auction principle (e.g., on a time basis). Examples of crowdlending →platforms are Auxmoney, Funding Circle or Zopa.

Reward-based →crowdfunding or crowdsupporting refers to projects from many areas (commercial, creative, cultural, sports, etc.), that are jointly financed by multiple supporters. The reward for the supporters does not consist of company shares or cash flows, but of a gift or the receipt of the developed product before it is brought to market. The calculation of the type or extent of the compensation depends on the amount of the financial support provided. A well-known crowdrewarding platform is Kickstarter.

Refers to the risk that swarm or →collective intelligence may lead to false investment decisions. For example, social behavior or peer pressure may supersede the principles of rational behavior (according to the homo oeconomicus model) and in times of overheated markets, investments could still be made in certain investment objects due to the herd behavior despite existing warnings and risk signals. It follows the idea that “masses” or →crowds cannot make mistakes.

A type of →crowdfunding where →tokens are issued according to the pre-defined rules of a →smart contract. These rules define the total offer, the time period, the minimum and maximum investment, and the number of available →tokens that are available for sale in an investment round called initial coin offering (→ICO). An →ICO is often used to finance the development of a decentralized and →blockchain-based →application that provides a →service. In this case, the investors’ creditor claims are represented as →tokens that correspond to a share of the loan amount. →Smart contracts then book these →tokens into the →wallets of the debtors. The value of the →tokens after the →ICO is often volatile and depends on the respective positive or negative development of the platform and its adoption in the market. The minimum investment describes the minimum number of →coins that must be generated or issued during the →ICO to ensure the financing of the project. If the crowdsale fails to reach the minimum amount, the invested capital is refunded to the investors. The maximum investment describes the sum of all investments that may not be exceeded. As soon as the maximum investment sum is reached, the →ICO ends.

Known from →open source software communities, crowdslapping is the reaction of the community towards a user’s (e.g., a developer’s) activity. Since the reaction of the community is not predictable, the feedback may be constructive and help in removing flaws in the product. It may, however, be negative and thus harm the company.

Refers to the →sourcing of resources from the →crowd via →digital platforms. Providers of resources (either individuals or businesses) may advertise their offerings or requirements on these platforms where other individuals or businesses can bid on them. In the case of crowdsourcing for employment (crowdworking), jobs, assignments or projects may be published and interested contractors—which often come from other countries worldwide—may bid on them. It enables companies to address a large, often global workforce reservoir and to distribute →services among them. In turn, the workers are rewarded either payments via the crowdsourcing →platform or via external →payment services. Among the largest crowdworking →platforms are Clickworker or Amazon Mechanical Turk. In addition to paid crowdsourcing, there are free forms of crowdsourcing, for example, when companies involve the →crowd in the development of new products and influence the market launch of a product through feedback or feedback loops to the manufacturer (→Social CRM). Another example are knowledge bases that grow based on user input (e.g., in the customer service area of a bank).

Also called reward-based →crowdfunding, crowdsupporting refers to projects from many areas (commercial, creative, cultural, sports, etc.), which are financially supported by many investors. Instead of company shares or cash flows, the supporters receive a gift or a specimen of the developed product before it is brought to the market. The calculation of the type or the extent of the compensation depends on the amount of financial support contributed.

Refers to →outsourcing software testing tasks to the →crowd via →digital platforms. These online community provide software developers with a realistic (real-life) testing environment due to the heterogeneity of the testers in terms of demographic criteria (age, profession, income, region, etc.) and a wide variety of software and hardware being used. The diversity of these crowd testers also offers the opportunity to test products and services in a target group-specific manner, which often leads to cost and time savings. Many →fintech providers are known to benefit from crowdtesting platforms such as Applause or Digivante.

→Cryptocurrency offered by the →payment service provider MCO as part of several payment solutions (→wallet, credit card) on several →crypto exchanges.

A technology driven by IBM that links physical assets to →blockchain systems by inserting or adding small and cheap computing devices (→IoT) that serve as unique identifiers (→UID). They allow to prevent theft and fraud for valuable goods and are also being used in supply chain settings.

Asset that is represented digitally on the basis of a →cryptocurrency. In view of the growing →tokenization, crypto assets not only comprise money and securities, but also other tangible and intangible assets. →Business models may be found in the environment of crypto asset management (→CAM) as well as →crypto banks.

Form of digital asset management (→DAM) where service providers manage →crypto assets or →tokens. CAM services include the execution of →cryptocurrency →OTC transactions or the secure storage of →digital assets and →smart contracts (→custodian).

Although →cryptocurrencies have the potential to substitute established financial intermediaries (→incumbent), financial service providers increasingly support private and institutional investors with →cryptocurrency investments. In order to offer their customers comprehensive investment opportunities (e.g., by means of →tokens), they often apply for a →banking license or a →crypto license and thus constitute a crypto bank. Examples of crypto banks include Bitwala in Germany and Seba as well as Sygnum in Switzerland. Among their services are the trading and custody of →crytptocurrencies, the offering of →cryptocurrency funds as well as the →tokenization of securities or other goods (e.g., real estate, art objects, wine).

Similar to existing →fiat currencies, cryptocurrencies comprise units for payment, investment or clearing purposes. However, these units serve different purposes in →blockchain- or distributed ledger technologies (→DLT). Since the emergence of →Bitcoin, a large number of →cryptocurrencies have emerged based on →blockchain frameworks such as →Bitcoin and →Ethereum (see appendix), which refer to the units as →coins or →token. By the end of 2021 there were 14,933 cryptocurrencies (as of 11/29/2021 at coinmarketcap.com) with a total market capitalization of 2559 billion USD, which marks a steep increase from the 5549 cryptocurrencies that were counted at the beginning of June 2020 (as of 06/06/2020 at coinmarketcap.com). These systems enable secure distributed data storage using →cryptography and use the exchanged →coins and →tokens as “currency”. In the case of payment processes (e.g., →chargeback, →electronic payments, →virtual currency), these currencies are independent of central banks and therefore not secured and regulated like →fiat currencies. Meanwhile, regulation has grown in many countries. For example, →crypto custody transactions are regulated in Germany since 2020, making cryptocurrencies used for payment purposes and corresponding →crypto exchanges subject to licensing requirements. An important drawback of most cryptocurrencies is their limitation to specific system platforms, which has led to several approaches to attain →interoperability (→CLI). This also extends to traditional channels, where →Bitcoin and →cryptocurrencies like →CBDCs are planned as universal payment instruments (i.e., in physical stores or points-of-sale). However, →virtual currencies still lack the typical monetary functions (payment function, value assessment, storage), which is also due to the fact that cryptocurrencies might serve other purposes besides payment (e.g., proof of condition, authenticity, identity, ownership).

Refers to a form of →cybercrime where processing power is hijacked via distributing malware programs for clandestinely →mining →cryptocurrencies.

With the implementation of the amendment to the fourth EU money laundering directive (Directive EU 2018/843), so-called crypto custody transactions will be subject to regulation. In Germany, the first section of the Governance Banking Act (KWG) was enacted in 2020 and regulates →services for the storage as well as for the transmission of crypto values (→digital assets) such as →cryptocurrencies and →tokens. Crypto custody also includes the offering and exchange of →virtual or →digital currencies by financial service providers and →crypto exchanges.

Scientific domain related to distributed or decentralized economic processes such as those enabled by →cryptocurrencies. Among the topics are the representation of →digital assets in →blockchain systems, the determination of prices for →coins, the behavior of participants in decentralized networks (e.g., incentives for →miners, avoidance of collusion) or the establishment of equilibrium states (e.g., equilibrium prices, Nash equilibrium).

Refers to an →electronic market that supports the exchange between →cryptocurrencies and/or to other assets (e.g., →fiat currencies). Two forms of crypto exchanges have emerged: (1) on the one hand, →platforms that support the exchange of →crypto and →fiat currencies (e.g., Coinbase, Kraken) and (2) on the other hand, exchanges that primarily support the exchange between →cryptocurrencies (e.g., →Binance, Bitpanda). An example for trading →digital assets or tokenized values (→tokenization) may be found at SDX, which is an initiative of the Swiss stock exchange SIX.

Crypto finance describes the financial →ecosystem around →blockchain applications such as →cryptocurrencies and →tokens, but also other cryptographic instruments like →e-wallets or digital money transfers. It is a digitally generated and operating →ecosystem (“natively digital”), which exists parallel to the classical financial system, consisting of banks and other financial institutions, intermediaries (→intermediation) and supervisory authorities.

Providers of →services for the custody (→crypto custody), management and storage of →cryptocurrencies such as →Bitcoin and other →digital assets are increasingly subject to regulation. In Germany, the money laundering directive has defined the so-called →crypto custody business since 2020. Based on such a →crypto license, companies are allowed to offer corresponding services to customers in Germany.

A computer game that aims to create and trade virtual cats, which players may then trade based on →Ether and reuse in other →NFT-compatible games. From a technical perspective, CryptoKitties are →tokens whose activities (e.g., distributing CryptoKitties, mapping the cat’s characteristics or geno−/phenotypes) are →smart contracts. They have emerged to demonstrate the potential of →blockchain technology and to make users familiar with this technology. CryptoKitties are available as web-based and as distributed →applications (→DApp).

Since the mid-2010s, an →ecosystem of →fintech companies in the Swiss canton of Zug has been formed along the lines of California’s Silicon Valley. In the meantime, numerous →startup companies as well as suggestions for →fintech regulations have emerged here. For example, the canton accepts the →cryptocurrencies →Bitcoin and →Ether as means of payment (→virtual currency) for taxes since early 2021.

Derived from the Greek words “krypto” (= I hide) and “graphe” (= the document), it denotes procedures for encrypting messages, or the contents contained therein (= hidden writing). Such procedures have existed for centuries in the form of secret writings, which ensured that only the intended or authorized senders and recipients could read the contents of the message. With the advent of information technology (→IT), digital encryption methods have gained in importance. The most important forms are →symmetric and →asymmetric encryption methods, the latter being widespread among →cryptocurrencies.

Assisted shopping describes the process of supported and personalized shopping. Suppliers request certain parameters (for example, clothing size, favorite colors and preferences, in department stores) from the customer and use →algorithms to create a personalized shopping basket (→personalization). Solutions from →fintech providers may be integrated for personalized pricing and settlement options to contribute to →customer experience (→embedded finance).

→Wallets are a key architectural elements of →cryptocurrencies by storing values (e.g., →coins, →tokens) and by supporting the handling of transactions. Each →wallet has a →private key which allows the authorized users (→authorization) to execute orders. In the model of the custodial wallet, the owner transfers his →private key to an intermediary (→intermediation) who acts as an administrator in the sense of a custodial service (→custodian) and executes transactions on behalf of the owner. In comparison to →self-hosted wallets, custodial wallets offer an increased user-friendliness and an improved protection of →private keys against theft and loss, but they require a trustworthy service provider (→TTP).

Service providers (→TPP) that store and manage assets, which includes both physical assets (e.g., shares, gold) and →digital assets. Among others, they provide wallet services (→custodial wallet).

Describes a customer’s overall experience with a company along the entire →customer journey. It reaches from the initiation (pre-sales/marketing) to the execution (sales) and after-sales activities (customer service/customer relationship management). While the customer experience is often expressed qualitatively by customers, for example, on social media →platforms, companies often try to calculate the (monetary) sales potential of an entire customer relationship by means of the customer lifetime value (CLV). Although →e-commerce and also →fintech businesses often emphasize customer experience in the pre-purchase phases, it may be observed that customer experience is neglected in the after-sales phase. For example, →smartphone banks often offer low-cost conditions and service advantages, but limit the contact to call centers, →chatbots and e-mail. To foster the CLV, →customer experience may be interpreted as an approach to customer orientation, which assesses a provider’s performance not from its own (inside-out), but from the customer’s point of view (outside-in), which reaches across the channels (→omni-channel) along the →customer journey. This also implies a multi-provider perspective (→multi-bank) since many customer needs (e.g., a house purchase, a pension plan) include offerings from different providers. →API or →open banking approaches enable the consolidation of individual services into such comprehensive solutions that support the customer experience. To measure customer experience, various performance indicators (→KPI) are used, including the automated analysis of customer sentiment (→sentiment analysis).

This overall view shows the activities that customers goes through during their purchase decision over time and different channels (→multi-channel, →omni-channel). The CJ emphasizes, how customers become aware of the retailer’s product (creating awareness) and how the interactions between customers and providers are designed. As shown in Fig. 23, the CJ is usually a directed path that begins in the pre-purchase awareness phase and continues through the purchase phase to customer care, in which providers strive for customer retention through memberships or preferred customer service. In a positive case, customers have a positive experience (→customer experience) and recommend the service to others (e.g., colleagues, friends). The CJ does not primarily consider the individual components of the product (price, quality, etc.), but rather the customer’s experience with the company (e.g., product presentation, cleanliness, friendliness and helpfulness of the employees), as these are believed to strongly influence purchase decisions. Customer journeys may be visualized using CJ maps, for which various tools and techniques emerged. Performance indicators (→KPI) for measuring →customer experience, such as positive or negative assessments from →sentiment analysis, may be assigned to the events at the respective stages of the CJ. These tools are used in the context of →design thinking and other innovation methods also for developing →fintech →business models.

Model that serves to evaluate the points of contact between a company and its customers (→CJ) in comparison to the competition. As shown in Fig. 24, criteria such as customer access, price, product features, service, and the overall experience (→customer experience) may be assessed on a scale from one to five. Depending on the evaluation, the company will be positioned above, equal or below competitors where a rating of three indicates being at eye level with competitors, while four indicates differentiation and five even a dominance over competitors.

Fig. 24
Assessment of the competitive situation in the customer relevance model

Refers to “digitalizing” physical devices by adding digital components in order to monitor or control them. Among the examples of CPS are complex energy, logistics, mobility or manufacturing systems, which have two main links to financial activities. On the one hand, they are linked to the management of physical cash flows and they may integrate billing and hedging services (→PAYU) on the other.

Crimes in which perpetrators use digital media to conduct criminal acts comprise phishing e-mails, password theft, virus attacks, identity theft or extortion. Cybercrime leads to →cyber risks, which financial service providers need to address with appropriate precautions. Since →fintech businesses process sensitive personal data and valuable financial information, they are often the target of cybercrime. One common method is ransomware, in which criminals penetrate a target system, encrypt data or block user access and only release it again after payment of a ransom. Due to the high material and/or immaterial value of the data, victims repeatedly comply with the demand for payment, which may reach a magnitude of several million US dollars for large companies. →Cryptocurrencies such as →Bitcoin, →Ethereum or →Tether are typically used for payment since they ensure the anonymity of the transacting parties. Depending on their design (→privacy coin, →pseudonymization) and as long as no →platforms, such as →crypto exchanges, are involved, →cryptocurrencies yield high levels of anonymity and security to the transacting parties.

With the increasing →digitalization of →business models, products (→smart product) and processes, the cyber risks that financial service providers need to consider in their risk management and the design of their →IT infrastructure are also increasing. The areas include cyber espionage (e.g., spying), sabotage (e.g., destruction of infrastructure), crime (→cybercrime) and misinformation (“fake news”), but also unintended consequences of malfunctions (e.g., programming errors) and erroneous behavior (e.g., unknown consequences of actions). In particular, businesses in the →fintech sector feature a high degree of →digitalization and operate in a sensitive environment (financial and personal data), which requires a high priority to questions of data security and data protection.

→Cryptocurrency based on →Ethereum, which is constructed as a →stable coin against the US dollar (1 DAI = 1 USD). It allows in the credit business to debit assets against a stable currency. The currency is managed by MakerDAO, which also issues the →cryptocurrency →Maker.

Similar to alternative trading platforms (→ATP), dark pools are privately operated electronic trading →platforms, that match buy and sell bids outside the →order book of official exchanges (→electronic exchange). However, they are (still) less transparent than →ATPs, since both trading volumes and bid prices are not visible and remain “in the dark”. Nevertheless, the non-transparent private markets need to comply with certain transparency criteria since →MiFID was enacted in Europe in 2018. Dark pools have advantages especially for larger orders that tend to influence prices in official markets, for example, causing price drops. Similar to →ATP, major banks such as Barclays, Credit Suisse, Deutsche Bank, Goldman Sachs or UBS are among the providers of dark pools.

The “dark network” is an area of the internet, which is separated from the open area by means of access and encryption software. It reflects an increased need for anonymity on the part of the users, which is based on various motivations (e.g., political persecution, illegal distribution of content, distribution of illegal content or carrying out illegal actions or transactions, →cybercrime). Anonymity also results from the decentralized nature of the Darknet, which does not centrally manage content according to the peer-to-peer principle (→P2P) and is thus one of the early decentralized →digital marketplaces. In accordance with this need for anonymity, decentralized →cryptocurrencies, especially →Bitcoin, are used for →electronic payments in the Darknet.

→Cryptocurrency designed similarly to →Bitcoin, but without publicly viewable blocks or transactions. It focuses on supporting consumer payments and has enjoyed a growing acceptance among merchants, exchanges and →ATMs worldwide. To support direct consumer payments (→P2P), Dash has introduced a dedicated →app and offering an in 2020, Dash changed the →consensus mechanism from →PoW to →proof-of-stake that is referred to as proof-of-service to reward active network participants.

The process of summarizing or aggregating data involves the collection and bundling of large amounts of data (→big data) as a prerequisite for diverse analytical purposes (→business analytics). The aim of aggregation or subsequent statistical analysis is to obtain data on a higher level, e.g., on entire customer or market segments, which may be used for →personalization, improvements of offerings or decision making in general. Besides in analytics, data aggregation is present in many use cases, for example in personal finance management (→PFM) or risk management. From a technological point of view, the extraction of data from “underlying” →application systems occurs via interfaces (→API), for which numerous →fintech companies offer interface solutions (e.g., BanksAPI). They ensure the aggregation from a syntactical (i.e., structure of data) as well as from a semantic (i.e., meaning of data) perspective.

A data-driven approach strives for reaching objective decisions, which are based on a comprehensive set of data (e.g., using →big data). It should enable companies to improve decisions regarding their product, assortment and pricing policies as well as their market strategy. For example, data provides the basis for generating products and →services for their customers via personalization (→smart product, →smart service) or for making more informed assumptions about market developments or customer behavior. Data may relate to information about people, things or context and may be divided into qualitative, quantitative, static or dynamic data. Figure 25 shows an example of the procedure for designing and implementing a data-driven service. The design phase is separated from the implementation phase and subdivided according to the three stages of the →design thinking approach. During the first stage (“Define”), idea generation and evaluation are used to define the →innovation project and to formulate goals and critical success factors (e.g., by means of a data-driven →business model canvas). The second stage (“Develop”) involves the development of a customer journey (→CJ) in order to determine the individual added value for the customer on the basis of the data obtained. The third stage (“Deploy”) comprises the development of the interaction design based on →mock-ups and prototypes (→MVP). The implementation phase is often based on →agile development approaches such as →Scrum, whereby data may again be used to monitor the testing as well as the subsequent roll-out phase (→data innovation board).

Fig. 25
Data-driven approach for a data-driven service

An innovation board may support the development of data-driven solutions, such as →data-driven products and →data-driven services. As the more generic digital innovation board, it is based on the →design thinking approach and visualizes the design decisions along three areas (see Fig. 26): (1) In the explore fields it determines the potential user(s) and structures the target group on the basis of existing data in order to establish a clear understanding of the needs in the market. (2) The ideate fields identify existing and additional data to address customer problems and select a data-driven solution. (3) Finally, the evaluate fields provide details on the customer interaction (→CJ) and collect ideas for further improvements.

Fig. 26
Data innovation board (see Kronsbein and Müller 2020, p. 565)

Following the →data-driven approach, data-driven products are defined by a value proposition, which strongly relies on data from the products’ usage as well as from the use other products of the same category. Among the well-known examples are usage- or location-specific products (→PAYU), such as those found in the insurance sector, which calculate rates based on the product’s usage as well as on the aggregate usage of all users. Data-driven products are often used synonymously with the more narrowly defined “smart” or “intelligent” products (→smart product, →CPS), which denote vehicles or machines, whose control is software-based and often includes adaptive or learning functions (→AI). Similar to smart products, data-driven products may be extended to or enhanced by →smart services in order to implement sharing models (→sharing economy) or preventive maintenance concepts.

Refers to an IT-based service that is provided and billed according to the pay-as-you-use (→PAYU) principle. Compared with a classic IT-based service such as that provided by →cloud computing, →smart services are specific with regard to the user and/or the usage context (→personalization). Data-driven services incorporate personal and/or location-specific data from multiple data sources, in particular intelligent devices (e.g., smartphones, tablets, →wearables, cars). As →smart services, they are often complex →service bundles, for example, a car-sharing →smart service includes a connection to a navigation, a parking and a payment service. Often, data-driven services come with a major shift in the →business model, which changes from being a pure product manufacturer to becoming a comprehensive solution provider (e.g., as many automotive companies on the their move from car manufacturers to mobility and/or software providers). Data-driven services comprise three central key elements (see Kaufmann and Servatius 2020, p. 152): (1) The data sources provide the data input and form the core of data-driven services. (2) The service type describes the different analytical methods, from analysis and prediction (→business analytics). (3) The delivery method determines how customers receive the service (e.g., via an automotive company or a financial service provider).

Refers to the form of organization of data in databases. While classical databases in the relational data model store data records in tables that are connected by identification keys, the more recent distributed databases in the field of →cryptocurrencies feature data structures where transactions are linked. Most popular →blockchain frameworks (e.g., →Bitcoin, →Ethereum) use linear data structures that organize transactions in blocks, but alternative data structures have emerged that follow the directed acyclic graph (→DAG) model (see Fig. 27). The latter also organize transactions in →nodes, but these are linked to several upstream and downstream →nodes (child/parent). By replacing the rigid chain structure, the graph enables several connected nodes to process in parallel, which has the potential to increase the speed, security and →scalability of distributed data management. Similar structures are found with →hashgraph and →holochain.

Fig. 27
Linear and acyclic data structure (based on Bai, 2019)

→Application that is stored and executable in a distributed environment. Early examples may be found in the →blockchain environment of widespread systems like →Bitcoin and →Ethereum, but more advanced within higher →Blockchain x.0 frameworks. While users may access a DApp like a traditional →app via a user interface (→front-end), the program logic and the data are not located on a centralized server, but rather on a peer-to-peer network (→P2P), such as a →blockchain or a →DLT. Thus, DApps require no centralized →services or →platforms, which implies that no intermediary is necessary (→intermediation). An example for a DApp is e-chat, a social network where the →blockchain stores the postings and protects them from deletion and censorship. In the financial context, many DApps have emerged under the umbrella of decentralized finance (→DeFi).

A form of organization, where multiple actors are organized by a decentralized software system. The concept has grown with distributed ledger technologies (→DLT) that include →smart contracts for executing governance and the organizational rules. This allows many activities (e.g., buying or selling securities) of a DAO to be carried out automatically without human intervention and without intermediaries (→intermediation). An example for →cryptocurrency governed by a DAO is →Dash, which is—like most DAO—based on the →Ethereum →blockchain.

In a decentralized exchange, a distributed information system adopts the tasks of a centralized exchange system (→electronic exchange). According to the functionalities of an →electronic market, these tasks include the collection of (buy and sell) offers in an →order book, the allocation of these offers according to a certain mechanism (matching) and the settlement of transactions (clearing and settlement). As shown in Table 3, various →protocols for →DLT systems already exist for the implementation of a DEX. A well-known DEX is →Binance DEX.

Table 3

Protocols for decentralized exchanges (see Schär, 2021, p. 161)

Protocol name	Protocol type	Pricing mechanism
0x	Exchange	→Off-chain order books
(Air)Swaps	→P2P/→OTC	P2P negation
Bancor	→Liquidity pool	→Smart contract
Cyprus Network	Reserve aggregator	Automated price reserve
UniSwap	→Liquidity pool	→Smart contract

The generic term for distributed solutions comprises financial transactions and applications that follow the peer-to-peer paradigm (→P2P), such as →DApps, →DLT and →open banking. DeFi positions itself against centralized approaches such as central banks, credit card organizations or centralized services providers such as →SWIFT, centralized exchanges or trusted actors like banks. It includes the concepts of →crowdsourcing, →crowdfunding and →DEX and are typically based on distributed applications (→DApps) and distributed ledger technologies (→DLT). Since 2018, numerous →cryptocurrencies have emerged in the DeFi space that focus on decentralized trading and transaction processes (e.g., →Aave, →Synthetix, →Uniswap).

Open standard of the World Wide Web Consortium (W3C) for decentralized →identity management procedures, supported by many actors in the →blockchain environment. It refers to data about things or people including →public keys, proof of origin, biometric data or certificates. DIDs are usually implemented on the basis of →DLT systems and do not require a central certification authority, since the →DLT software prevents multiple assignment of identifiers. DIDs are used for →authentication, especially for →KYC purposes, and typically stored in a digital →wallet.

Deep learning is a subarea of artificial intelligence (→AI) and refers to the use of neural networks as a form of →machine learning (→ML). The depth or the topology of the network results from the structure of the neural network, which consists of neurons (i.e., mathematical functions) in several (minimum two) hierarchical layers (see Fig. 8). Starting from the input data, the neurons determine weights that lead to an output (e.g., image recognition, risk calculation). With an increasing number of layers, the decisions of a neural network will be more differentiated, but also less transparent.

Based on the effects of →digitalization on individuals, organizations and society as a whole, the degree of →digitalization describes the extent of use or the degree of maturity of using information technologies (→IT) in these areas. In the business context, the term refers to the →digitalization of products, processes and/or →business models. →Fintech companies are attributed a high degree of →digitalization since they define themselves via digital technologies and often even see themselves as →IT businesses.

This improvement of the →proof-of-stake →consensus mechanism in →blockchain networks is based on the delegation of →mining rights to a smaller number of →nodes (the so-called witnesses). These delegates “lobby” for votes from participating nodes, which assign →tokens to express their vote. The witnesses then validate the generated blocks in a pre-determined sequential order, which tends to increase the performance of →consensus mechanisms. Besides efficiency, DPoS was also designed to be more democratic since →nodes are not required to hold a minimum number of stakes and may reallocate their stakes among witnesses more flexibly (which in turn creates an incentive for witnesses to act honestly). A →cryptocurrency that uses DPos is →Eos.

A method that is often applied to develop →business models and combines the principles of agile software development methods (→Scrum) with →innovation and creativity techniques. Design thinking emphasizes an early understanding of customer problems and aims at solving them with innovative—often digital—solutions that are tested using prototypes (→mock-up, →MVP). The application of design thinking is widespread in the →startup sector and among →fintech companies.

Also referred to as robotic desktop automation (→RDA), this field of →cognitive computing denotes the automation of simple, rule-based processes based on defined actions and decision points. An example is the transfer of sales data from an Excel spreadsheet to an online form. The efficiency improvements in terms of higher speed and lower error rates are particularly important for many →back-office tasks.

The abbreviation for development is often found in the environment of agile project management (→Scrum), e.g., as a term for the developer teams (dev-teams).

The portmanteau of “development” (Dev) and “operations” (Ops) connects the development and operation of software. Based on the principles of →agility and agile project management (→Scrum), DevOps aims at the timely realization of software in short, often weekly cycles (so-called sprints). By including customer representatives in the →dev teams, DevOps ensures the alignment with customer needs, which often include the claim for continuous improvements as well as more radical redesign. DevOps also links to development and operations to safeguard quality of the software artefacts and their operational stability. In addition to agile development, DevOps embraces the automation approaches of continuous delivery and integration of software. In sum, DevOps is rather a collection of key principles than a coherent set of tools and offers orientation in the interaction between customer, development and operation. As shown in Fig. 28, these principles are culture, automation, lean, measurement and sharing (CALMS). They should enable (1) a culture of cooperation and a shared responsibility for software quality in teams, (2) a comprehensive use of development tools along a so-called “delivery pipeline” to automate development, testing and deployment tasks, (3) the use of metrics to measure development performance (e.g., deployment frequency as the frequency of new releases) as well as (4) the comprehensive sharing of existing knowledge.

Fig. 28
Overview of DevOps principles (see Alt et al., 2021, p. 35)

→Cryptocurrency project in the field of →electronic payments, which was initiated by Facebook. Together with 20 other companies (e.g., Visa) the social media company founded the Geneva-based Libra Association in 2019. The initial idea was to create a →digital currency that is linked to existing →fiat currencies. Users should be able to buy Libra currency using a local currency or alternative digital currencies via their →wallet. While the original Libra concept focused on a →stable coin that was backed by several →fiat currencies, the enhanced concept (Libra 2.0) submitted to the Swiss regulation body →Finma aimed at linking each →coin to exactly one specific →fiat currency. This Libra concept was based on a closed →blockchain infrastructure (→permissioned blockchain) and should enable more efficient electronic transactions (i.e., faster and cheaper) worldwide. Since this pointed in the direction of a competing currency to the existing central bank currencies (→CBDC) and →payment systems, the initiative has experienced another strategic repositioning since 2020. On the one hand, it was renamed to Diem at the end of 2020 in order to distance itself from the Libra brand, which was still conceived as being close to Facebook. On the other hand, operations were transferred in May 2021 from Switzerland to the US and it was decided to focus on a →stable coin to the US Dollar only, which should be issued by Silvergate Bank. In early 2022, the Diem project was discontinued with assets being transferred to Silvergate.

Digerati (or digirati) is a compound of “digital”and “literati” and refers to the “digital elite” in the field of →digitalization, in particular →startup businesses such as →fintech companies. Digirati may refer to both individuals and organizations. Following this definition, a company would be a digirati once its digital maturity (→digital champion) is judged superior to that of its competitors.

Following the notion of →digitalization, two aspects of “digital” need to be distinguished. (1) In the technological interpretation, it refers to technologies of digital signal processing, which use binary signs for storing and transmitting signals. In contrast to analog data (e.g., pictures, films, audio) where signal are present in continuous functions, digital technologies record all signals in binary form (0 or 1). Analog-to-digital conversion is achieved by sampling the analog signals and storing these binary codes in files with a specific compression format (e.g., mp3, mp4). Among the important advantages of digital over analog media are that they may be read repeatedly without quality losses and that they may be transmitted in real-time (→real-time processing) via electronic networks. Products and →services, which feature a high information intensity can therefore be reproduced and modified using digital technologies. (2) →Digital transformation has become the established term for the applied interpretation of →digitalization, which recognizes the fundamental change process of most parts of the economic, social and political environment. For financial service providers this has far-reaching consequences with regard to new products and →services, the automation (→RPA) of business processes from customer interaction to →back-office processing as well as new →business models. In particular, the rise of →fintech companies has already led to profound changes in the financial sector.

In contrast to physical assets such as precious metals, real estate and securities, digital assets include all objects contained in digital form with assigned property rights. Examples of digital assets include data, such as images, videos, presentations or text, which businesses can use to generate value. With the advent of →cryptocurrencies, →tokens have enabled to manage property and usage rights more efficiently. For example, →tokenization allows to trade these physical or virtual goods in parts or as a whole more efficiently on →digital platforms such as →crypto exchanges.

The term digital asset management in present in three interpretations. (1) The first includes →application systems for the centralized management of digital media (e.g., documents, image and sound files), including usage rights. For example, such DAM tools may be found for the automated processing of news or press reports. (2) A second understanding stems from the area of asset management and refers to →application systems for portfolio management. These tools range from the construction of portfolios to the partial or full automated rebalancing of portfolios to the execution of stock market orders and back-office functionalities. More recent approaches include →robo advisory and →RPA functionalities. (3) With the emergence of →cryptocurrencies, a third interpretation may be observed, which comprises providers for trading and archiving →crypto assets (→CAM).

In a larger context, the term refers to the →digitalization of banking operations and comprises either →startup businesses that pursue a digital strategy as well as traditional banks (→incumbents) that gradually become digital banks. In narrower sense, it is a synonym to →online banking, which aims to provide customers with digital banking services that were previously only available offline within branch offices.

With the diffusion of the term →digitalization, digital commerce has increasingly established itself as a term for the IT-supported economy (→electronic business) or electronic trading (→e-commerce). Analogous to →electronic commerce, it refers to the electronic support of the phases of an economic transaction.

These →startup companies in the insurance sector exert a →brokerage mandate and usually derive their competitive advantage from a comprehensive and up-to-date market overview. Based on a continuously updated database of offers from the market, they operate solutions to support either agents in call centers or customers via →robo advisory services. Similar to →smartphone banks, digital insurance brokers primarily use digital channels such as the internet, social media and mobile devices for customer interaction. Among the examples are online insurance brokers such as Getsafe, Clark and Insurancebrokers, which are also referred to as pure-digital insurers (→PDI).

This ability of corporate management to master the →digital transformation of industries and markets, is often present in →startup and →fintech businesses. It typically includes a management style that recognizes the potentials of →digitalization with the aim of unlocking these potentials for new or changed processes, products, →services or →business models. The success factors (→CSF) of corporate culture in digital management include an ability for networking, openness to new (technology and market-driven) developments and the associated change, →agility in action and the involvement of as many employees as possible. Managers are expected to spread the knowledge of →digitalization broadly within the organization (e.g., through training and further education, interdisciplinary teams, and agile organizational approaches such as →DevOps). Accompanying change management has the task of creating a balance between continuous change effected by new technologies and to keep employees and customers involved, positive and curious.

Regulatory proposal by the European Commission (EC), published together with the Digital Services Act (→DSA) in December 2020 to limit the market power of large →digital platform providers (→big tech). Since these actors determine the rules of the →platforms (e.g., platform access, user fees, data usage, display of search/matching results), they are considered →gatekeepers with considerable market power. The DMA aims to ensure fairness and openness both on the market-dominating platforms and to safeguard the market opportunities of smaller service and platform providers. For the financial sector this means that →gatekeepers must not benefit from analyzing usage data on their →platform and sell it or use it for offering own financial services. Similarly, →gatekeepers must not prevent external providers of financial products and services (e.g., competing →payment services) from accessing the platform. As sanctions, the EC may impose fines of up to 10% and periodical payments of up to 5% of the platform company’s global revenues.

A term coined by the Massachusetts Institute of Technology, which refers to a company, especially in the →startup and →fintech sector, that has attained a high level of digital maturity (→degree of digitalization). For example, the organization might feature a →business model that is based on digital competencies (e.g., →data-driven products and/or services), a broad use of digital technologies in their operations and a high or well-developed digital transformation management intensity (i.e., the successful organization or “mastery” of →digital transformation).

Refers to a population group that has grown up with →digitalization. Members of this group are attributed a greater affinity with digital technologies such as smartphones and the internet, as well as a stronger familiarity and understanding of technology in general. At the same time, developments such as lower attention spans, lower motivation or low loyalty to traditional authorities (e.g., a main bank) can be observed, which are relevant for future strategies and →business models in the financial industry.

Collective term for digital or electronic means of payment (→electronic payments, →e-payment), that occur either at a physical (e.g., in a branch using →mobile payment or an →ATM) or a virtual point of sale (→PoS) (e.g., an online shop) and that are derived from a primary transaction (→e-commerce). According to the →four-corner model, several players are involved along the payment value chain, in particular →acquirer, →issuer, →PSP, →NSP, merchant and customer. They cover various forms of →electronic payments (or payments at a virtual →PoS), in particular card-based payments along with credit transfer (on account), direct debits and →electronic money. Figure 29 illustrates the interaction between the actors using the example of card payments where buyers in an online shop use the credit card payment option, which is provided directly by an →issuer or another service provider (→TTP). The payment flows are separated according to →authorization, →transaction or information flow, clearing and settlement mechanism (→CSM) and the →fee flow between the banks on the buyer and seller side and the payment network operators (e.g., →processor, →card scheme). In the case of cross-border transactions, →cross-border hubs are also used on the sending and receiving side. With the rise of →cryptocurrencies, forms of digital payment arise that involve less actors along the entire chain as shown in the examples of →Ripple and →Bitcoin transactions.

Fig. 29
Card-based digital payments in the four-corner model

A digital infrastructure, which provides a set of generic services for →authorization (→KYC) and interaction among platform users as well as the →platform for various →services that are offered by the platform provider and/or other providers. Digital platforms are present in various forms, for example as innovation and idea platforms, as transaction and commerce platforms and as social and networking platforms. In the area of business transactions, they may be assigned to the fields of electronic commerce (→e-commerce) with financial activities being part of a secondary value creation process. On the one hand, digital platforms are related to →electronic markets and →multi-sided markets if competition occurs among users. On the other digital platforms are closely related to digital →ecosystems, which comprise the complementary interaction of multiple actor groups, such as hardware and platform provider, the providers of multiple complementary →services (so-called complementors) and the customers.

Regulation announced by the European Commission (EC) in December 2020 on the liability of online services in order to protect consumer rights (e.g., against illegal or fraudulent products, content and profiles) and to ensure transparent and fair competition in the digital economy. Equal competitive conditions are intended to create incentives for smaller →startup businesses that allow them to position themselves vis-à-vis larger providers, in particular the →big tech companies. For the →fintech sector, the DSA applies to new payment procedures (→electronic payments) or customer-oriented offerings (e.g., →PFM), resulting in stronger competition and thus improved conditions for consumers. The DSA addresses all digital intermediaries (so-called online intermediaries), which may be located inside or outside the EU and offer their →services within the European single market. For this purpose, the DSA defines four categories of online services (EC, 2020): (1) intermediary services that have infrastructure character such as internet access or network providers, (2) hosting services such as cloud service providers (→cloud computing), (3) online platforms such as →digital marketplaces, →app stores or →collaborative business platforms of the →sharing economy, and (4) very large online platforms that also fall under the Digital Markets Act (→DMA). The former categories include the latter, i.e., (1) includes (2), (2) includes (3), and (3) includes (4). This sequence also corresponds with growing regulatory requirements in the respective categories.

An electronic or digital signature forms the basis of a secure message or transaction and is an important element for business transactions. These signatures are recognized in numerous countries (e.g., the European Union (EU)) as a legal basis and are based on three requirements: (1) the assurance of the identity of the communication or trading partner (→authentication), (2) the non-repudiation of the actions confirmed by the signature, and (3) the unchanged transmission of the signed message or document (i.e., integrity). Digital signatures are not digitalized manual signatures but based on cryptographic encryption processes (→cryptography), in particular →asymmetric encryption, whereby the →private keys may be implemented on smartcards, smartphones or on private key infrastructures (→identity management) and increasingly also →blockchain infrastructures.

Refers to the process of change that takes place with →digitalization, which may occur at various levels (i.e., individual, organization, industry, society, see →digitalization). In general, gradual changes (e.g., improved management of existing processes) and fundamental or disruptive changes (e.g., a new business model based on the →sharing economy) may be distinguished (→disruption). As is known from the historical analysis of innovation processes (→innovation), transformation processes may endanger the existence of companies (→Kodak trap) and facilitate the emergence of new actors (→startup).

Virtualized models or identities of physical (investment) goods, which are well-known in research and the manufacturing environment. Computer aided engineering (CAE), for example, conducts simulations of three-dimensional virtual constructions to contain both development times and development costs. Digital twins of machines form an essential part of the industry 4.0 concept (→I4.0) and, with →digitalization, they were also adopted in the economic and financial sector. For example, machines might be able to initiate transactions and payment processes independently (e.g., for replenishment, maintenance) and may even possess their own financial accounts.

Describes the macro- and microeconomic value creation through →digitalization or →digital transformation strategies, in which businesses reduce costs and increase revenues. Digital value creation not only takes place in existing industries or areas (e.g., the distribution of existing financial products via electronic channels or the →digitalization of existing business processes), but also through new →business models and processes (e.g., →sharing economy or →smart services).

Collaborative and iterative workshop format, in which employees of a company work with →digital natives and →startup or →fintech companies to develop innovative solutions. The majority of digithons focuses on the development or improvement of products and →services and the development of digital →business models. The digithon serves as an agile development method, i.e., it is an interdisciplinary workshop based on →Scrum, following the formats of →hackathons and →design thinking. Similarly, digithons extend over a period of 1–3 days, with several teams pursuing the goal of developing a clear result in the form of a design →mock-up, a proof-of-concept (→PoC) or early prototypes (→MVP). In order to bypass corporate restrictions, which might restrict creativity and →innovation, digithons should take place in a new or alternative environment rather than in the accustomed office space.

With the use of information technology (→IT), the binary coding of data has created the need to convert signals from analog sources (e.g., sounds, images) into binary data formats. This transformation process refers to a technological understanding of digitalization, which is sometimes also called digitization. In addition, →business information systems conceived IT early on as a pathfinder for redesigned or novel business solutions (business processes, →business models). In this sense, the application-oriented understanding of digitalization, that is widespread today, refers to the design and application of IT-based solutions by individuals, organizations and society in order to achieve improvements in →user experience, efficiency and effectiveness. Figure 30 illustrates the two conceptual understandings of digitalization in connection with their effects on several levels (i.e., organization, society, individual). In the financial industry, digitalization has gained importance due to the intangible nature of financial services and the high volume of structured data. For example, data standards such as the bank code (→BLZ) or data networks such as →SWIFT date back to the 1970s and are among the early application areas of electronic data interchange (→EDI). Since the same time, especially larger stock exchanges, banks and insurance companies have started to establish their own IT departments, which have developed →application systems for internal business processes (→bank model). Over the years, important prerequisites emerged in the domain of standardized message and data formats, which today enable →real-time processing between the numerous players in the financial industry on a global level (e.g., →BIC, →CUSIP, →FinTS, →ISIN, →ISO 20022, →NSIN, →WKN). Since the 1990s, standard software systems (→core banking system) appeared on the market, which have led to digitalization in small and medium-sized financial institutions (→SME) as well as to the replacement of proprietary →applications in larger banks. In the last decade, a strong push towards more open systems (→open banking) and innovative →fintech solutions may be observed.

Fig. 30
Dimensions of digitalization (see Alt, 2018b, p. 399)

Banks that use virtual channels to interact with their customers instead of physical branch offices. Among the examples are the internet (→online banking), call centers as well as mobile applications (→mobile banking). While ING or Consors Bank have been present as direct banks for some time, younger representatives in the →fintech sector like N26 or Revolut are emphasizing the mobile channel and are also considered →smartphone banks.

Enables direct access of actors to the systems of a stock exchange (→electronic exchange). This allows authorized traders to place their orders directly in the exchange’s →order book without the use of intermediaries. In general, only certified or professional traders are admitted for DMA, but this principle might be subject to change with decentralized exchanges (→DEX).

Describes an alternative →data structure to →blockchain technology where data is not linked along a sequential chain but as a directed acyclic graph (e.g., →tangle). As shown in Fig. 27, the data structure is networked and data elements may have several upstream and downstream elements. To prevent self-reference (i.e., transactions pointing to themselves), the graph is directed and points in only one direction. The goal of DAG is to achieve higher levels of security, speed and →scalability. It has to be distinguished whether a connection of blocks (→Block DAG) or of transactions (→TDAG) takes place. A →cryptocurrency according to the Block DAG structure is Nano and one according to the TDAG structure is →Iota. Before →Iota users are able to send a transaction, they need to check two randomly selected transactions. The principle is that a transaction must be sufficiently verified before completion. For coordination purposes there is an administrator who confirms the transactions in a series of approved milestones. Other known DAGs are Byteball and RaiBlocks.

Refers to the replication and hosting of physical or virtual servers by third parties to provide failover in the event of a disaster. This service is provided either on a fixed contractual or on a pay-as-you-use (→PAYU) basis. Disaster recovery typically takes place in →cloud computing environments, so instead of having to provide their own disaster recovery environment, companies are required to trust third-party providers (→TPP) for data protection and recovery time.

Refers to a fundamental innovation that changes or displaces existing solutions and markets. In the age of →digitalization, information technologies (→IT) and their application in business and society are main drivers of disruption. →Blockchain, →big data, →quantum computing or →AI technologies are typical examples of disruptive technologies. The disruptive potential of these technologies requires companies to prepare early and be able to question existing solutions to avoid the →Kodak trap.

The field of distributed or decentralized artificial intelligence (→AI) refers to the behavior and coordination of numerous participants in a network. DAI has included multi-agent systems (→agent) for a long time and recently the combination of →AI methods with →blockchain or →DLT systems.

Connection of several computers without central control for processing common tasks as is the case with →P2P and →DLT technologies. Computing tasks are distributed among the participating computing →nodes and coordinated by a distributed database management system (DBMS). This DBMS schedules tasks and combines them to form a result as well as ensures the consistency of shared databases like the →consensus mechanisms in distributed ledger systems (→DLT).

In the case of a DDoS, the request for an internet-based service is refused if the service is overloaded due to a high number of requests. This is a strategy frequently used by cybercriminals (→cybercrime) to deliberately damage services or their operators. The distributed nature of this strategy is due to the fact that the attacks originate from several systems and are therefore difficult to track. Since →fintech businesses are strongly relying on digital processes and →business models, the need for preventive measures, such as the definition of packet filters, Geo-IP blocks or emergency plans, is also increasing.

A distributed →ledger is a transaction-based →ledger that is typically designed as synchronized databases that are distributed among multiple computing →nodes. Distributed ledgers are the technological basis of →cryptocurrencies and include datasets that represent transactions regarding payments, property transfers or other economic purposes. In the pure distributed form (e.g., the →Bitcoin system), there is no master ledger (central account ledger or central point), but with the maturity of distributed ledger systems (→DLT) a variety of models emerged that comprise →nodes with more rights (e.g., →master nodes).

Describes a specific form of the architecture of a →DLT database, which comprises several coordinated software components and facilitates the use of →DLT solutions and applications based on them (→DApps). Essentially there are →front-end and →back-end components that are distributed on the decentralized →nodes as opposed to centralized architectures (see Fig. 31). Despite different versions of these nodes may exist (→master node, →miner), the decentralized model lack a centralized actor that provides the application logic (e.g., offer database or catalog, matching mechanism, shopping basket, clearing and settlement functionality) and which all participants must use. In DLT architectures, →the back-end usually contains the necessary functionalities with parts of the application logic and the decentralized database, while the →front-end contains the decentralized applications (→decentralized application, →smart contract, →wallet) and has specific development environments (e.g., →Solidity or Clarity for →DApps). Development tools such as Angular are used for the user interface.

Fig. 31
Centralized (left side) versus decentralized (right side) platform architecture (see Alt, 2020b)

Form of a distributed database system that stores transactions in decentralized structured (→data structure) databases (→distributed ledger) on several computers which may therefore not be manipulated (or only with great effort). A major consequence of distribution is the higher reliability, since there is no central point of failure (→SPoF) compared to centralized architecture concepts. DLT systems focus on the use of cryptographic procedures (→cryptography) to ensure confidentiality and data security, and on updating and synchronizing distributed data (→consensus mechanism). The widespread forms of DLT databases are the →blockchain and →DAG technologies.

Refers to the seventh phase of venture capital (→VC) financing with the sale of the shares and the realization of the capital gain. The preceding phases are (1) →seed financing, (2) →startup financing, (3) first stage financing, (4) second stage financing, (5) third stage financing and (6) late stage financing.

Financial regulation in the U.S. led by Congressman Barney Frank and Senator Chris Dodd, which was created in the aftermath of the financial crisis in 2008 and came into effect in 2010. The aim was to increase the stability of the financial system and to strengthen the rights of customers. The comprehensive regulatory framework comprises 16 chapters and has increased requirements for the granting of loans as well as the options for →fintech →business models. Similar to the European →PSD2 regulation, service providers such as Mint now have the opportunity to obtain account data from banks in order to offer services such as →PFM (→multi-bank).

Internet protocol (IP) (→protocol) that handles the name resolution of internet addresses. DNS converts user-friendly domain names such as “leipzig.de” into an IP address so that the user no longer has to store and use complex IP addresses.

While general purpose languages (GPL) are programming languages (e.g., Java, Python) and modelling languages (e.g., UML) that can be used for all application fields or domains, domain specific languages concentrate on representing the problems of a specific domain. Examples include HTML as the language for web pages, SQL for database queries and XML for data structures. Domain experts map the data objects, activities and rules from their environment, so that the defined syntax and semantics are formalized as the basis for further automation. This may be used to test and certify →application systems as well as →smart contracts. For example, using a DSL for →smart contracts, developers can check whether the implementation corresponds to the draft of a →smart contract. This provides the opportunity to certify →smart contracts or →tokens (e.g., certified →ERC-20 →tokens).

The economic crisis, named after the internet domain ending “.com”, is linked to the “New Economy” that emerged in 1995 when many →startup companies were launched in the field of information technology (→IT). In addition to the growing demand for shares in the IT sector, there was an increased demand for capital through initial public offerings (→IPOs). The media coverage of →startup businesses and →IPOs led to an euphoria of demand and culminated in a boom of the sector. In 1999 alone, there were 457 →IPOs in the US, most of which were internet or technology-oriented companies. On the first day of trading, 117 of these 457 companies doubled in value, but the dotcom speculation bubble collapsed in March 2000. This particularly affected the so-called dotcom companies of the new economy and led to asset losses for numerous small investors, especially in industrialized countries.

Users who have registered in a distribution list using their e-mail address (regular or single →opt-in), will receive a subsequent confirmation e-mail asking them to confirm their registration. If the user confirms the registration, a double opt-in is complete. The double opt-in procedure improves protection against spam and unauthorized access and thus offers stronger legal security, as the sending of unsolicited commercial e-mails is prohibited under many legislations.

Double spending describes the risk of a →digital currency being spent twice due to the reproducibility of digital data. The owner of the currency could make a copy of the digital →token or →coin and send it to a merchant or other party, while retaining the original. The risk is lower with physical currencies, since they are more difficult to replicate and the parties involved in the transaction are more likely to immediately verify the authenticity of the currency.

In the context of non-fungible token (→NFT), a drop denotes the sale of a →NFT by an artist. In many cases, drops are announced via social media.

To regulate →electronic money, the European Commission adopted the second e-money directive 2009/110/EC in 2009, which was incorporated into the →payment services supervision act in 2011. The directive defines the characteristics of e-money transactions as well as the type of e-money institutions, which have to meet lower capital requirements compared to a →banking license and thus should facilitate the market entry for new providers.

→Startup financing (with equity capital) serves to provide capital in the early phase of a company’s development. In the case of a successful development of the →startup, other forms of financing (→business angel, →VC) follow.

Referring to the natural sciences, the term has been increasingly used in recent years to denote the coaction and →collaboration among multiple economic actors in loosely and/or tightly coupled →business networks. These actors offer complementary as well as competing →services and may also include customers. Ecosystems show parallels to biological systems, in which living beings or organisms flexibly coexist as a community in a self-organizing and ideally in a balance (e.g., in a forest ecosystem). In the economic environment, individuals and organizations participate in an ecosystem, whereby synergy and growth potential can arise vertically along industry-specific value chains (e.g., in a banking ecosystem) or horizontally across industry boundaries (e.g., an →operating system ecosystem). One example is the investor ecosystem in California’s Silicon Valley, in which capital providers, research institutions and →accelerators create an attractive environment for →startup companies. A key differentiator from the environment is the admission of actors to the ecosystem (e.g., capital, relationships, technical standards or approval procedures), which in the case of enterprise-centered ecosystems often determines a leading company (e.g., the platform operator). →Digitalization has created digital ecosystems, with examples such as the →operating systems Android, iOS (Apple) and Windows (Microsoft), the →e-commerce platforms Alibaba, Amazon and JD, the social networks Facebook, Instagram and Twitter, the payment platforms PayPal, Mastercard and Visa as well as the various banking networks (→open banking) and →cryptocurrencies (e.g., →EEA). →Digital platforms (e.g., as →app stores, →platform banking) are important for the interaction of services in the ecosystem and for its management. Figure 1 shows these in conjunction with the reinforcing →network effects that are key to ecosystem growth, which result from the interplay between partners (or complementors), the platform operator (or ecosystem orchestrator) and the users (or consumers).

Fig. 1
Actors and effects in an ecosystem (after Cusumano, 2010)

In contrast to the centralized concept of →cloud computing, edge computing is a decentralized architecture concept that foresees1 data processing and storage “at the edges” of a network. By moving activities to the point where data originates or is being used, data traffic over the network is reduced and response times tend to be improved. Edge computing has gained particular relevance with the proliferation of decentralized computing devices (e.g., IoT devices, smartphones) and decentralized network concepts (e.g., →peer-to-peer networks). Besides the use cases in networked manufacturing environments (e.g., →M2M, →I4.0), examples are also known in the financial sector with personalized location-specific services (→personalization, →smart service, →LBS) or concepts of immersive customer interaction (e.g., →augmented reality, →mixed reality, →virtual reality).

A standard developed by the German association “Die Deutsche Kreditwirtschaft” (formerly “Zentraler Kreditausschuss”) in 2006 for internet-based payment transactions between banks, which is also used in the context of →SEPA (e.g., for handling payments between banks and larger businesses) and permits forwarding these messages to the →SWIFT network. The focus is on secure message transmission, e.g., using →HTTPS and the →RSA procedure. Similar to →FinTS, EBICS is a procedure to process →electronic payments within the →PSD2 framework. While →FinTS is mainly used in →online banking and →PFM for private customers, EBICS also allows the processing of larger transaction volumes (e.g., in bulk payments with more than 200 orders per transaction).

In the simplest case, the electronic bill is an invoice in a digital format (e.g., PDF) that the recipient receives via e-mail. This form of electronic invoicing has become established for many →e-commerce transactions and has often replaced physical invoices accompanying the consignments of goods. However, electronic invoicing is only one part of the overall payment process and requires, as a counteractivity, the instruction to pay the invoice. Private customers typically use →online banking portals and corporate customers their business →application systems (→ERP, →core banking system) via →EDI linkages. E-bill services are also present within the concept of electronic bill presentment and payment (→EBPP).

Procedure of electronic invoicing (→e-bill) and payment that aims to increase the efficiency of payments on account. Instead of being printed and mailed via paper, the documents are shown (“presented”) on portals of the billers, a bank or a service provider (e.g., Serrala, Swisscom). This allows banks to make bills accessible in →online banking systems, while service providers often concentrate on aggregating bills from different billers and then paying them via the accounts of several banks (→multi-bank). While the substitution of paper-based invoices already creates efficiency effects, more comprehensive EBPP systems also provide for the payment of the invoice. For private customers, this is often done using a function included in →online banking. In this case, bill recipients activate the invoicing companies that are registered in the →online banking system, which allows them to view and to approve the bills with a click. Although this results in a digitalized payment process, this procedure has not gained much acceptance yet compared to other procedures for →electronic payments such as direct debit or card payments. There is a greater penetration the business-to-business area, since EBPP functionality is often included in business →application systems such as SAP. However, this electronic data interchange (→EDI) often involves the agreement of data formats among the transacting partners and represents an effort that will only merit with larger transaction volumes.

Compared to →e-commerce, which focuses on the transactions of buying and selling products and/or →services, e-business is broader in scope and includes the support of economic activities with information technologies (→IT) and may be interpreted as →digitalization in the economic sector. Analogous to the objectives of →e-commerce, e-business also strives for a high level of integration of processes and systems between the parties involved. E-business is therefore regarded as a continuation of intraorganizational integration (e.g., within the framework of →ERP systems) in the interorganizational area, i.e., with suppliers, business customers and sometimes end customers. Thus, it includes other activities such as research and development (R&D), customer relationship management (CRM) or supply chain management (SCM).

Describes the support of economic transactions with information technology (→IT) along three phases. These include the information phase (market overview, selection of providers and products), the agreement phase (negotiation of conditions, conclusion of contracts) and the settlement phase (delivery and payment of services). →Digitalization has led to increasing sales via electronic distribution channels (websites, social media) and →platforms (e.g., →digital marketplace). Financial services are typically present as a derived (secondary) demand in the processing phase of a primary transaction (e.g., as electronic financing, payment and insurance services), whereby e-commerce and financial systems (e.g., for →electronic payment) are linked via interfaces (→API) from dedicated service providers (see also Fig. 5 for the connection of financial services at a car manufacturer in chapter “A–D”). As shown in Fig. 2, the secondary value creation process again involves the transaction phases, as financial service providers have to be selected, contracted and paid for. →Digital platforms and →ecosystems coordinate the numerous electronic services and thus allow an integrated or media break-free transaction processing (→media break), which also contributes to the reduction of →transaction costs. The financial industry provides its own application case when it represents the primary value creation process itself, as is the case with financial investments or stock trading.

Fig. 2
E-commerce and financial management (see Alt 1997, p. 143)

Refers to the electronic exchange of data between →application systems to transfer electronic documents from one computer system to another, without →media breaks (i.e., without manual re-entry). For this purpose, the data must be available in a defined syntax (character set, field length and field name) and use shared semantics (meaning of the data fields). However, as data models differ among companies, standardization initiatives have emerged that develop syntax and (in some cases) semantics at the interorganizational level. EDIFACT (Electronic Data Interchange for Administration Commerce and Trade) has achieved cross-industry significance, as have →FinTS, →ISO20022 and →SWIFT for the banking sector and →BiPRO for the insurance sector. Although the development of many of these standards dates back decades, they are still relevant for stucturing digital messages (e.g., in →fintech solution) and transactions (e.g., in →DLT systems).

Physical and/or virtual space where supply meets demand for a certain economic good and where an allocation is made using defined coordination mechanisms (e.g., price, quantity). While electronic exchange systems initially supported physical trading on the exchanges with information and settlement services, fully electronic exchanges have replaced physical (floor) trading and at most exchanges worldwide. As →digital marketplaces they reduce →transaction costs but are often only accessible to registered →brokers. In contrast to these traditional exchanges, numerous alternative platforms have emerged (e.g., →ATP, →MTF, →crypto exchange), which cause increasing competition among stock exchanges and open access to →non-banks. A further development may be observed with the emergence of decentralized marketplaces (→DEX), which execute market functions entirely digitally and without a central marketplace operator (→intermediation).

Refers to →digitalization in the health sector, i.e., the use of →IT in hospitals and medical practices, the exchange of data between the individual players in the healthcare system (e.g., service providers and health insurance companies) and solutions to support patients. Solutions often feature links to the →fintech sector, for example, regarding →authentication, billing and documentation.

Electronic identification serves as proof of identity of legal entities or persons. As a basic service, it is a precondition of many use cases, in particular for accessing →services of government agencies, banks or other companies (→KYC). Issuers of electronic identities may be both federal institutions (e.g., SwissID) as well as private sector organizations (e.g., →big tech companies or specialized providers of →identity management services). The scrutiny of the identity check (e.g. with/without proof of an official identity card) significantly determines the “quality” of the qualified logins.

Electronic identity verification stands for the verification or →authentication (identity verification), as well as the proof of identity (identity proofing).

An electronic or →digital marketplace is an electronic platform (→digital platform) where customers can search and compare offerings by several (often competing) providers. Depending on the number of actors on each market side, single-sided markets involve scenarios where only one actor exists on one side, for example, when a seller acts as a dealer of products from multiple suppliers. Since the term market always subsumes several suppliers and consumers, digital marketplaces in their pure form are →multi-sided platforms. The →platform operator provides the market infrastructure and, depending on the adopted →business model, also acts as a →service provider. The infrastructure includes the provision of the website and the market database, which might be an electronic catalogue or in the auction or exchange area an electronic →order book. It includes the description of the market offers in a standardized way for comparison and provides functionalities for transaction processing (or clearing and settlement, →CSM). Depending on the allocation procedure, there are catalogue, exchange and auction systems, whereby the latter also offer functions such as the request for information, the request for quotation or the request for proposals. Analogous to the trading systems of official and over-the-counter markets (→OTC, →MTF), →platforms for trading →cryptocurrencies have developed with the →crypto exchanges. As shown in Fig. 3, digital marketplaces have a topology that differs from other inter-organizational relationships. At present, most electronic marketplaces feature a centralized structure where an intermediary (→intermediation) provides the marketplace functions. However, with the evolution of decentralized systems like distributed ledger technologies (→DLT), a decentralization of these marketplace functions and the emergence of n:n topologies may be observed (→DEX).

Fig. 3
Topologies of electronic markets (see Alt, 2018a, p. 124)

These non-cash payments comprise payment transactions via electronic networks such as the internet or trusted infrastructures like →SWIFT. Electronic payment methods may include both existing (e.g., credit transactions, direct debit, credit transfer) as well as new (e.g., →electronic money) forms of electronic payment. Many of these forms are based on the →four-corner model, which defines that buyer (debtors) and seller (creditors) keep accounts with their respective bank and that the payment is processed via electronic networks (e.g., →SWIFT, →SEPA, →EMV, →scheme). The financial institutions are reflected in the role of the →issuer (the payer’s bank) and →acquirer (the payee’s bank) well as →third parties (e.g., →EMV). As shown in Fig. 4, the activities like →authorization, →authentication, clearing as well as settlement are distributed differently between these roles. Clearing may either occur (1) internally within the bank or a banking group, (2) bilaterally between two interconnected banks, or (3) via the →payment systems, i.e., →ECB, →RTGS, →ACH. More recent approaches use the decentralized →blockchain technology to process traditional payments and enable new payment procedures using →electronic money (→virtual currency) by means of →cryptocurrencies. The main differences are the timing of →authentication and the debiting (clearing and settlement, →CSM) of the buyer’s account. For example, →authentication for direct debit takes place before the purchase phase, while most procedures provide the →service at the →point of sale during the purchase phase. In the case of direct debits, credit transfers and credit cards, the debit process is separated from the purchase phase, whereas in the case of debit cards and electronic →wallets, the debit process occurs immediately after the purchase phase. A further distinction refers to whether the payments are made at a physical →point of sale (→mobile payment) or a virtual →point of sale (→e-commerce).

Fig. 4
Alternative forms of electronic payments (based on Bons & Alt, 2015, p. 172 and Huch, 2013)

Describes the macro- and microeconomic value creation through →digitalization or →digital transformation strategies via cost reductions on the one hand and/or increased revenues on the other. Electronic value creation occurs not only in traditional industries or areas (e.g., sale of existing financial products through electronic channels or →digitalization of existing business processes), but also through new →business models and processes (e.g., →sharing economy or →smart services).

In contrast to →mobile wallets, e-wallets are hosted on the internet and cannot be used via a mobile device solution without an internet browser. Nevertheless, many e-wallet providers such as PayPal also feature mobile solutions (→app).

→Asymmetric encryption method used for →cryptocurrencies, which is known as Secp256k1 for →Bitcoin. ECDSA is characterized by shorter key lengths compared to the well-known →RSA method (e.g., 521 bits instead of 15,360 bits for 256-bit keys) and thus requires less computing power. This also makes it suitable for mobile devices and network applications such as →blockchain technologies in general.

Concept that denotes the integration of financial services in the products and →services of →non-banks. This comprises →e-commerce businesses and, in particular, the →big tech companies which not only seamlessly link to payment and insurance services, but which also offer the access to checking accounts and the like via their (electronic) presences. For example, customer accounts with an →e-commerce retailer also include information from the bank account and various forms of payment (→electronic payment) as well as credit that are integrated as →whitelabel services from external partners (e.g., lending-as-a-service). In addition, →authentication (→KYC) is often required to access →services and to meet regulatory requirements. Embedded (or →contextual finance) finance follows the logic that in many cases, financial services are part of the settlement phase of an economic transaction and serve to support a primary transaction (→e-commerce). It allows automotive, retailing or gaming companies to keep the link to their customers and is believed to contribute to →customer experience. The concept is enabled by →banking-as-a-service offerings from →fintech companies and increasingly also from →incumbents.

Standard for chip card-based payments, which was developed on the initiative of the major credit card companies Europay International, MasterCard and VISA (EMV). The current EMV consortium (EMVCo) also includes other card companies such as American Express and Discover. EMV goes beyond the physical printing of credit cards or the reading of the magnetic stripe and also regulates the stages and the technical conventions (e.g., offline PIN verification, encryption) regarding the chips’ use in payment cards (prepaid, debit, charge and credit cards) as well as in merchant terminals and →ATMs.

The application of information technology (→IT) and →digitalization have become recognized as structural elements that enable new or redesigned processes and/or →business models. They allow established (→incumbent) or new financial service providers to close the so-called “digital gap”, for example to improve competitiveness (e.g., cost base) or →customer experience (e.g., customer interaction, →CJ) by means of innovative digital →business models and processes.

Describes calculation processes that convert plain text or unencrypted text (so-called decipher) or any other type of data into an encrypted version. To decrypt the data and convert it into a plain text form, a key (→public key, →private key) is required (→symmetric encryption, →asymmetric encryption) and ensures data security, especially for end-to-end data transmission via (public) networks. As part of →cryptograph, encryption forms a key element of →virtual currencies and →cryptocurrencies.

Represents a model-driven approach to structure the complex design elements of an organization in their context. For this purpose, an EA distinguishes several dimensions (or views or levels) that map technological, organizational, strategic and/or cultural design elements. Well-known contributions to EA include the methodological approaches of TOGAF and the Zachmann framework as well as numerous supporting IT tools (e.g., Iteratec, Sparx). While EA typically aims at achieving coherence between the business and technological areas of a company (business IT alignment), →digitalization in recent years has brought an increased cross-company orientation with →platforms and →ecosystems (→architecture 4.0). This is particularly important for providers of →fintech solutions, who need to integrate their solutions in transactions of primary goods (→e-commerce, →EFI).

Term for a →blockchain implementation that is tailored to the needs of one or more companies that is often initiated to achieve data confidentiality and access control (→permissioned blockchain). It reflects the desire to grant different access rights to authorized participants is typically linked with the possibility of a comprehensive or central control, which implies at least a partial deviation from a fully decentralized peer-to-peer model (→P2P).

Founded in 2015, this initiative of multiple actors aims to further develop the →Ethereum blockchain. This includes standards that improve the →interoperability between different →enterprise blockchains by means of certification. The members of the EEA also include numerous companies from the financial sector (e.g., Accenture, Avaloq, ING, JPMorgan Chase, Sberbank and UniCredit) as well as technological businesses like Microsoft and groups such as OASIS.

Describes integrated business →application systems that provide comprehensive support of intraorganizational business processes. This includes both the primary value creation activities (for example, purchasing and sales, distribution, production, customer service) and supporting functional areas (for example, finance, accounting, and human resources). ERP systems map the operational resources (for example, materials, machines, employees, customers, suppliers, jobs, and orders) of a company in a centralized database and implement cross-functional processes. Over the past decades, providers of ERP systems such as SAP have preconfigured their standard solutions to individual industries (so-called industry solutions) and may also act as providers of →core banking systems.

Denotes a segment for financial products that are associated with achieving goals in the area of sustainability. Follwing the triple nature of sustainability, the investments may emphasize ecological (e.g., greentech), social (e.g., diversity) and/or business (e.g., stability) goals.

→Cryptocurrency with →smart contract functionality introduced in 2017 that is available →open source and uses →proof-of-stake as →consensus mechanism. Eos claims to waive transaction fees and achieve high transaction rates (→TPS).

Ethereum request for comments (ERC) denote developments and technical specifications used in the →cryptocurrency →Ethereum. For example, they specify the technical implementation of →tokens to ensure the compatibility of →tokens (e.g., with regard to the functionalities in →smart contracts). Most →cryptocurrencies with the →proof-of-stake consensus mechanism are based on the ERC-20 →token, with OmiseGo, Golem, or →WETH being among the well-known ERC-20 tokens. While ERC-20 →token primarily serve fungible →tokens, ERC-721 →tokens have emerged for non-fungible goods (→NFT).

Refers to a trustee service for the processing of transactions between unknown partners. For example, the service provider (e.g., →fintech companies such as Paylax or Intersolve) manages funds or assets in escrow accounts until the funds or assets are released upon receipt of instructions or until the recipient fulfils predetermined contractual obligations. A similar procedure is the documentary letter of credit.

After →Bitcoin, Ethereum is the →cryptocurrency with the second highest market capitalization in terms of the valuation of →coins (→Ether). Since 2015, Ethereum is available as an →open source solution and has seen multiple →forks, including the original version →Ethereum. Ethereum is the →blockchain framework that has gained high importance in the area of business applications (e.g., for fast payment transactions) with the →smart contract functionality (→Blockchain x.0) being a key element for the execution of business logic, i.e., digitalized processes. Ethereum is therefore considered the most important programmable →cryptocurrency and most decentralized finance applications (→DeFI) as well as most solutions with non-fungible tokens (→NFT) are based on Ethereum. A key factor is the ongoing development driven by the Ethereum Foundation based in Zug (Switzerland), which gives it important advantages over →Bitcoin in particular as the leading cryptocurrency. Among the examples is an improved version (Ethereum 2.0 or Eth2) that yields improvements regarding →scalability, security and decentralization. This version, called “Beacon Chain”, will include a change in the →consensus mechanism from →PoW in the previous Ethereum chain (Eth1) to →proof-of-stake.

Original version of the →Ethereum →blockchain that was created in 2015 and dates back to a split in 2016, while the newer version (→Ethereum) features the corrected record that excludes the theft of numerous →coins. Ethereum Classic reflects the original state that includes this incident.

Also known as E-Euro, this initiative by →ECB was announced in October 2020 to realize digital central bank money (→CBDC) based on →DLT. The project is strategic in nature since the decision to either implement a wholesale or a retail version directly affects the central bank’s existing →fiat currency. In the case of a retail →CBDC, it is no longer only financial institutions that hold accounts with the central bank, but also private households. This would give the →virtual currency a status similar to that of cash, but would be associated with greater efficiency and transparency. At present, the specific design with regard to the involvement of commercial banks and user data protection (e.g., scope of anonymized money) are still under development. In view of other emerging →CBDCs especially in Asian countries, the digital Euro is expected to be launched in the forthcoming years.

The European Banking Authority is a European Union authority that develops general regulations, which are then implemented by the national authorities (e.g., →BaFin in Germany). In the →fintech area, →EBA has developed a →fintech roadmap and a →fintech action plan which serve as the basis for regulating developments such as →cryptocurrencies.

Central bank that is responsible for the European currency (Euro, €), which has been adopted by 19 of the 27 countries in the European Community. ECB has initiated several activities in the →fintech domain, for example, the guidelines for →fintech credit institutions and the discussion of introducing a →virtual currency (→CBDC, →Euro-on-ledger).

A federation of European banking associations that emerged in 1992 from the three main banking sectors: private-sector banks (Banking Federation of the European Union, EBF), public-sector banks (European Savings Banks Group, ESBG), and cooperative banks (European Association of Co-operative Banks, EACB). The aim was to formulate technical standards in cooperation with other players such as →EMV and →SWIFT. Since 2004, the activities of ECBS have been successively merged into the European Payments Council (EPC) with the most widely known standard being the international bank account number (→IBAN).

Initiative launched in 2020 by 20 major European banks (e.g., Deutsche Bank, Santander, Unicredit) and supported by central banks to create a pan-European →payment system as a continuation of the Pan-European Payments System Initiative (PEPSI). EPI enhances existing systems for real-time electronic transfers (e.g., Instant Credit Transfer from →SEPA, Instant Payment Settlement from →TARGET) and positions itself as a competitor to card networks (→EMV, →scheme). This should enable customers to use a uniform card and electronic purse (→wallet) throughout Europe.

Investment products that have become popular with institutional and private investors due to the →digitalization of financial instruments and stock exchanges (→electronic exchange). In contrast to traditional actively managed funds, they are linked to a financial index (e.g., stock or →fintech index, gold or commodity price) (e.g., the S&P 500) and are therefore less dependent on the individual assessment of fund managers. The world’s largest providers comprise iShares/Blackrock, Vanguard and State Street. Since 2016, there have also been initiatives to allow →cryptocurrencies, especially →Bitcoin, as underlying asset, although these often faced concerns about possible market manipulation or lack of regulation.

Similar to →ETF, this generic term for exchange-traded financial products or instruments includes funds (→ETF), securities (so-called exchange traded commodities, ETC) and currencies (so-called exchange traded notes, ETN). More recently, ETPs have spread, which reflect the prices of →cryptocurrencies such as →Bitcoin and are listed on exchanges such as →Xetra in Frankfurt.

Development phase of a company (→startup), which is concerned with the financing of expansion steps or special financing occasions, such as the takeover of other companies or the bridging of capital (→bridge finance) or →liquidity bottlenecks in →IPOs.

Procedure in the area of →business analytics, which comprises the extraction of data from source systems and the transformation of this, typically heterogeneos, data into a common data format that is then loaded in a dedicated database (data warehouse) for analytical purposes. Data homogenized in this way is the prerequisite for calculating key figures (→KPIs) that may be presented in dashboard or cockpits to users. Numerous dedicated →application systems have been established for the ETL steps (e.g., Apache Nifi or Pentaho Data Integration in the →open source area as well as solutions from Microsoft, Oracle, SAP or SAS). ETL is used by various applications in the fintech area, e.g., the evaluations of →liquidity, the overall asset situation or spending behavior in personal finance management (→PFM).

Similar to the peer-to-peer concept (→P2P), F2F interactions take place directly between individuals, but require immediate physical proximity. In addition to differentiating between various forms of interaction (e.g., social media, e-mail, telephone), F2F in the financial sector refers to →digital payments, for example, where the debtor and the creditor are private individuals and payment transactions are conducted cashless via →mobile payment solutions at the →point of sale. For this purpose, the debtor and creditor need a compatible →mobile payment solution, such as PayPal, Apple Pay, Google Wallet, etc.

This identification procedure uses biometric characteristics (→biometrics) to recognize faces and to assign them to a specific person. It is widely used in the field of →video authentication of persons, but also for the analysis of crowds, for example in shopping centers. Linking these face images with personal data is strongly tied to the compliance with data protection (→GDPR).

The Federal Financial Supervisory Authority is responsible for the supervision of banks and financial service providers, insurers and securities trading in Germany. As an institution of public law it is under legal and technical supervision of Germany’s Federal Ministry of Finance. BaFin issues licenses for the provision of financial services, which includes in particular the →banking license (Sect. 32 of the German Banking Act) and the license for payment services (Sect. 8 of the German Payment Services Supervision Act, →ZAG). BaFin is financed by fees from the supervised institutions and companies. Depending on their design, the diverse →fintech business models may require BaFin permission, e.g. in payment transactions, funding or portfolio management. Although BaFin has issued numerous assessments and statements on developments in the →fintech sector (e.g. →blockchain, →robo advisory, →electronic money), the decision often requires an individual case-by-case assessment.

Fiat money is typically based on physical money without coverage by scarce resources (e.g., reference assets such as gold or silver) or without a signifiant own intrinsic value. While traditional fiat money is backed by governments, this is not the case with most →cryptocurrencies. On the one hand, this gives the advantage of independence from intervention by governmental institutions. On the other hand, tying the currency to a reference object creates greater stability and therefore underlies →stable-coin initiatives such as →Tether.

Denotes an interface from →cryptocurrencies to →fiat currencies that →offer crypto exchanges. This allows users to →buy cryptocurrencies (e.g., →Bitcoin) with →fiat currencies (e.g., US dollars) and exchange →cryptocurrencies for →fiat currencies.

The purpose of financial inclusion or integration is to make financial products and services available on favorable terms to individuals and enterprises, irrespective of their wealth or size. As large parts of the world’s population continue to rely on informal financial services providers, financial inclusion aims at solutions that enable currently excluded people to participate in the formal financial sector. Often, access to a bank account is a first step towards broader financial inclusion and increased social and economic participation. Among the approaches for financial inclusion are →microfinance solutions where individuals offer financing to other individuals (→P2P).

This semantic data standard for the financial industry was published by the Object Management Group (OMG) in 2014 to create a uniform terminology with precise definitions, term contexts and synonyms. Using ontological technologies (RDF/OWL) and the established modeling language UML, a basis for →data aggregation and processing was created that comprises terminology for agreements, products and services, organizations as well as date and times.

A data standard for the electronic exchange of data (→EDI) in securities transactions initiated in 1992, which is now considered the de facto message standard for all main processes in global securities trading. FIX comprises technological specifications on the transport and session layers as well as syntactic conventions for the vocabulary (or data fields) used in the messages. On the application layer it has specified numerous messages for the pre-trade (e.g. with quotation negotiation, market data), trade (e.g. program trading, cross orders) and the post-trade (e.g. with →settlement instruction, confirmation) phases.

In 1989, the Open Management Group (OMG) established a freely available 12-digit identification standard to identify financial instruments (see Fig. 5).

Economic entities that act on behalf others to mediate between supply and demand for financial instruments and who provide own financial industruments or instruments they adapated from other intermediaries (financial engineering). Depending on market structures, the use of financial intermediaries (→intermediation) may increase or decrease →transaction costs. On the one hand, investment advisors can increase the price of financial products through their own commission, while on the other hand, comparison portals (→electronic markets) may increase competition among providers through improved market transparency. Although both directions are possible with →fintech providers, their main focus should be to contribute to customer benefit (→customer experience).

Regulatory agency for financial services in Switzerland with similar duties like →BaFin in Germany. Although Switzerland is not a member of the European Union, many European regulations (e.g., →MiFID) are subsequently adopted in Swiss law to reduce →transaction costs with European countries.

A company that offers selected and often highly standardized financial services. These include financial advisory and/or intermediation services (such as brokers, insurance companies, etc.). Within the FSPs there is a legal differentiation between so-called key people and representatives. While key people are responsible for regulatory reporting and all actions of the FSP, the representatives advise potential policyholders on financial services and eliminate other intermediary services in relation to the selected products.

This standard in the field of →online banking enhances the →HBCI standard that has been used by German banks to standardize the communication interface between customers and credit institutions. Driven by the central credit committee in Germany (“Zentraler Kreditausschuss”, now “Die Deutsche Kreditwirtschaft”) and thus supported by the three banking pillars in Germany (mutual savings banks such as DZ Bank, public sector banks such as savings banks, as well as private banks such as Deutsche Bank and Commerzbank), version 3.0 was released in 2002 as a continuation of →HBCI 2.2 and is now available in version 4.1. FinTS offers agreements in several areas, e.g., message protocols (e.g., HTTPS, SOAP), security procedures (e.g., PIN/TAN, chip card, →RSA), business transactions (so far >100 business transactions, e.g., international credit transfer) as well as data formats (e.g., data fields in business transactions). These facilitate electronic data interchange (→EDI) between corporate and business customers and banks (→SWIFT) and improve →multi-bank capabilities. Figure 6 shows the use of FinTS for private as well as corporate customers and distinguishes between a connection via portals (→PFM) or a direct connection of →application systems (→EDI). The latter is widespread among corporate customers and primarily includes the →EBICS procedure for retail payment transactions.

Refers to the financial well-being of individuals or, from a business perspective, of employees. By establishing a comprehensive overview of past and planned expenditures, income and reserves, corresponding →application systems help to avoid risks and critical situations. Examples include →apps for expenditure and budget planning, cash flow analysis or portfolio optimization. Often, such solutions summarize financial wellness in a numerical score (→KPI).

Meetings or discussions from →startup or →fintech companies with different investors in successive stages. These are the →seed round or the →series A to C. The aim of →startup or →fintech companies is to complete equity financing by assigning shares to investors, thus enabling further company growth.

Combination of the initial syllables of the terms “finance” and “technology”, spelled fintech or FinTech. There are two basic meanings: an institutional view denotes a specific type of company. These are mostly →startup businesses that renew traditional financial services by using modern technology and try to offer their →services in a more innovative, efficient and/or customer-oriented way than existing service providers (→incumbents such as banks). A second view is function-oriented and characterizes fintech solutions, which increasingly rely on standardization (economies of scale) and less complex products or services in the financial sector, which are often already familiar to the client or may be explained by means of short descriptions (text, picture or video). Generally, fintech solutions are based on comprehensive →digitalization and are not limited to →startup companies. There is also an increasing number of partnerships between →incumbents and fintech companies. From a functional point of view, fintech solutions for the banking and the insurance sectors may be distinguished (see Fig. 7). According to the →banking model, the key banking processes comprise financing, payments (→paytech) and investment (or saving and investing, →wealthtech), while insurance processes include the areas of improvements and protection and, to some extent, investment (for example in life insurance). Mixed solutions of banking and →insurtech services are found under the term →bancassurance. Other sub-sectors are →regtech for regulatory applications and →contech and →proptech for the construction and real estate industry. Due to the innovative character of fintech solutions, a distinction is made between product, process and technology →innovations. According to this distinction, innovative information technology (→IT) provides the basis for designing efficient processes, which in turn can be exploited on the market in the form of new products. In contrast to process and especially product innovations, technological innovations are not directly related to the functional areas. For example, →blockchain or →IoT technologies are applicable for both payment and insurance solutions. In the case of process and product →innovations, fintech companies must observe the regulatory framework conditions, as banking and insurance transactions are subject to a license issued by the regulatory authorities (e.g., →BaFin in Germany, FMA in Austria and →Finma in Switzerland) (→banking license). Fintech services are not subject to these guidelines if they directly concern money-creating or risk-bearing activities (e.g., consulting, settlement), or relate to a previously unregulated area, as was initially the case with →cryptocurrencies.

Fig. 7
Areas of fintech (based on Alt and Ehrenberg 2016, p. 13)

An →incubator that accelerates the growth and success of →fintech companies by providing resources and services free of charge or at low cost. Typical supporting services are the provision of physical space and shared services as well as capital, coaching and (relationship) network (e.g., to lawyers, developers, investors).

Refers to the third to fourth phase of venture capital (→VC) financing. The first-stage phase consists of the start of production, the market launch, the development and expansion of personnel, the increase in sales, and the adaptation and further development of the range of →services as well as strenghtening business relationships. The risk for investors may be better assessed from this phase onwards, as initial market experience is available and the market response and thus the potential returns may be better estimated. The importance of outside capital for companies also increases in this phase (leverage effect).

Similar to the clearing and transaction flows another relationship within →electronic payments applies to the settlement of individual charges between the parties involved in these transactions. For charge and credit cards, the flow of fees is similar to that of debit cards but neglects the internal cost allocation of the parties involved. Consequently, the flow of fees for →electronic payments is divided into three categories: (1) national point of sale (→POS) processing of card payments (→MSC), (2) card payments at the →ATM, and (3) clearing and settlement fees (→CSM, →interchange fee).

In social media like Facebook, Instagram or Twitter followers, fans or friends form the basis of social networking. A person, organization or →robot may follow another profile and receive messages published by that profile or send messages to their followers themselves. Similar to other businesses, financial service providers have recognized the potential of social media to attract a large number of followers on the respective social media →platforms, as this allows them to establish a direct and interactive form of communication, which may be used in particular in customer-oriented processes (→Social CRM).

Foreign exchange trading and cross-border payment transactions are considered fields that are strongly affected by →digitalization. They are driven by the emergence of electronic →payment systems (→electronic payments), which are based on payments between banks via the →SWIFT network and, due to time and cost advantages, increasingly via the more recent →blockchain systems (e.g., →Ripple).

Process of generating blocks in →blockchain systems, following the →proof-of-stake →consensus mechanism. The forging process allocates the transaction fees of the last completed transaction to the person who was allocated to creating the last block using the →proof-of-stake principle.

A fork refers to a branch of development after the splitting of a project into two or more subsequent projects. In software development, this refers to a modified →open source code, whereby the forked code has been subject to important or fundamental changes compared to the original code. Common use case for forks are testing purposes or when new →cryptocurrencies with similar but not identical properties are to be developed. A fork also means the gradual enhancement of →open source software, since its free accessibility allows developer to make their own copy and modify (or fork) it for their own purposes. In the context of →blockchain or →DLT networks, forks have led to numerous variants of →cryptocurrencies. These forks are often the result of disagreements about further developments, e.g., regarding block sizes, the →tokens used, openness (→permissioned blockchain) or the →consensus mechanism used. After a proposed change, either a →soft fork or a →hard fork may occur, which differ primarily in their compatibility with the previous version. An overview of important forks in →Bitcoin and →Ethereum is shown in Fig. 8.

Fig. 8
Selected forks in Bitcoin and Ethereum 2008–2022 (based on Viens, 2019a, b)

The architecture of existing →payment systems typically comprises four players, with the two transaction partners initially acting as debtor/buyer and creditor/seller. For payment processing, both connect to a bank that authorizes and then executes the payment. The other party (→TPPSP) is a network provider such as the credit card companies. Figure 9 shows the four-corner model using the example of a card payment, with the →acquirer acting as the creditor bank, the →issuer as the debtor bank, and the →card schemes as the network providers. →Fintech companies, in particular, are positioning themselves along the four-corner model in various forms, for example as payment service providers (→PSP) that take over traditional banking services. More recent approaches, especially in the field of decentralized networks (→DLT), attempt to replace this third party as well as the banks and thus tend to increase the efficiency of the →payment system. One example is →Ripple.

Fig. 9
Actors and activities in the four-corner model (based on Huch, 2013, p. 39)

This trading strategy is increasingly being offered by online brokerage services and allows smaller investors to invest in highly valued stocks (e.g., from the →big tech companies). While the smallest order quantity at exchanges has traditionally been one share, fractional trading allows to invest in only fraction of this share and fosters diversification strategies via the combination of fractions of various shares.

An artefact that organizes elements of specific object of investigation. It is frequently used term for →cryptocurrencies that comprise several elements. These are the →operating system of the →blockchain or →DLT system, the database with a defined →data structure, the →tokens as exchange objects between the participants and a →development environment. Examples of well-known →blockchain frameworks are →Corda, →Ethereum or →Hyperledger.

Describes the →applications that provide functionalities for user interaction. The terms user interface or graphical user interface (GUI) are typically used as synonyms. Front-ends, such as →wallets, supplement →back-end functionalities, which comprise a →blockchain or →DLT, for example. Front-ends are an important component of →blockchain frameworks.

Refers to all customer-oriented processes (e.g., distribution and transaction entry processes, →bank model), organizational units (e.g., counter) and systems (e.g., →online banking) of a bank.

A full node is a program in distributed ledger technologies (→DLT) that validates transactions and blocks. Full nodes accept and validate transactions and blocks from other full nodes and forward them. As key components of decentralized systems they include not only include the program logic for validating and synchronizing data, but they also store a copy of the distributed database. Similarly used terms are those of →master and →supernodes.

Describes the action of raising money for a specific purpose (fund acquisition). Fundraising is often associated with organizations that aim to acquire the resources (money, goods and services) needed to fulfil their statutory purposes by consistently focusing on the needs of the providers of resources (private individuals, companies, foundations and public institutions).

Abbreviation for the “Big Four” of the digital economy (→big tech), the largest and most dominant companies in the information technology (→IT) industry of the US namely Google, Amazon, Facebook and Apple. All four are now also providing financial services (e.g., Google Pay, Amazon Pay, Facebook Pay and →Diem, Apple Pay) and link their →payment services with other services, especially in the →e-commerce sector. While the GAFA term is limited to US companies, the acronym →BATX also includes Chinese companies

Concept that denotes the use of playful elements in non-play situations. Elements of game design include leaderboards, which represent a ranking of participants, the achievement of primarily non-monetary points, rewards, badges or certain levels, which in turn are linked to certain achievements, or the placement of content objectives (e.g., strategy development, training) in game situations. Gamification is present in numerous →fintech solutions, e.g., in →PFM, to create awareness of spending or saving behavior, or in →Social CRM, when customers receive points or other incentives for advising other customers.

Term used in the European Commission’s digital markets act (→DMA) for →digital platforms that dominate with their →services (e.g., search engine, operating system, social media/messaging, intermediary) in at least three EU countries through a high number of users (>45 million active end users/month and >10,000 active business users/year in the EU). The →DMA quantifies these companies with annual revenues in the EU region of at least 6.5 billion € in the past 3 years or a market capitalization of at least 65 billion € in the past year. If →digital platforms qualify as gatekeepers, they must not exploit their dominant position opportunistically, but must comply with certain rules regarding openness and transparency.

In an (electro)technical context, a gateway denotes an interface between two components (e.g., between an →application system and mobile devices such as →RFID tags). Following this meaning, the term has also established itself in the German payment transaction community. As a so-called →headend, a gateway acts as a technical interface between the three banking pillars in Germany (private banks, mutual banks, savings banks) as well as an interface between a merchant and the bank or the credit card provider (→issuer) for processing financial transactions. Actors offering gateway services are often also referred to as payment (service) provider or payment processor (→PSP).

Regulation of the European Commission, which is mandatory for all EU member states and regulates the processing of personal data by private and public data carriers. The goal is to ensure, on the one hand, the protection of sensitive data within the EU member states and, on the other hand, the free movement of data within the European single market. The GDPR is transferred in national legislation, for example the DSGVO (“Datenschutzgrundverordnung”) in Germany and also applies to →fintech companies operating in Germany. Their digital →business models require them to comply with data protection laws when processing personal or personally identifiable data (in particular gender, title, password, bank/account/payment data, date of birth, age, other IP address, phone number, residential/delivery/billing address, first name and surname).

In terms of the age of users of digital services and devices, there are several categories of users known as Generation X, Y or Z. This assumes that young users are more familiar with digital technologies as they have already grown up in an increasingly digitized world. While the birth of Generation X (born 1965–1980) took place in an early phase of →digitalization, which was thus limited to certain sectors of companies and society, the two successive generations of →Generation Y (born 1981–1996) and →Generation Z (born 1997–2012) are considered the prototypes of →digital natives. Those born younger (from the early 2010s onwards) are also called Alpha Generation. The →now-generation, which includes those born between 1985 and 2000, refers to the overlap of Generation X and →Generation Y. Typically, each generation is associated with its distinct style of digital media use (e.g., while →Generation Z makes greater use of the social media service Tiktok, →Generation Y prefers Instagram and →Generation X is most adept with Facebook and Twitter).

Members of this population group were born between 1965 and 1980. As a generation between the previous “baby boomers” and the subsequent →Generation Y, they grew up in an affluent society characterized by television and video and computer games. They have thus already experienced the early phase of →digitalization in companies and society. In contrast to the →digital natives of →Generation Y and →Generation Z, however, the use of digital media was restricted to a certain group of people (e.g., representatives of the IT department and IT specialists or “nerds”) as well as sub-sectors of companies and of society. The representatives, also known as “twentysomethings” or “slackers”, are also considered to be rather pessimistic and weak in decision-making, besides being not very determined and interested in professional or material fulfilment. For financial service providers, addressing this customer group is challenging, since the individuals are little interested in financial matters on the one hand, but are increasingly gaining in prosperity through inheritance on the other. →Fintech companies are trying to lure them to financial matters by digital offerings, →gamification strategies and the like.

Describes the population group of the so-called Millennials that were born between 1981 and 1996. They grew up with the presence of digital technologies and rapid change, and are therefore considered flexible, less brand loyal and often immune to traditional marketing and sales methods. On the other hand, recommendations, relationships and opinions from social networks (→social banking, →P2P) and sustainable behavior (→ESG, →sharing economy) are often more important.

Refers to a group of →digital natives born between 1997 and 2012, who grew up not only with computers but also with the internet and mobile technologies. Members of this population group are not only active users of digital services (e.g., social media, →e-commerce), but are also increasingly involved in the establishment of →startup companies in the →fintech sector.

A genesis block is the first block of a →blockchain, often marked “0”. It has no upstream block to which it can refer and therefore cannot be calculated by the network. Rather, the genesis block is assigned in the context of an official release and is firmly anchored in the source code. Each →cryptocurrency based on →blockchain technology has its own genesis block from which the →master chain and possible →side chains are formed.

In general, the gentleman agreement stands for an agreement between two or more parties that relies on good manners and is therefore not specified in writing. →Fintech companies often neglect formal declarations and rely on the word of their partner(s).

This method determines the geographic location of a computer by identifying the IP address of that computer. Although Geo-IP can assign the location of a terminal to a city, the method is less accurate than other methods of geolocation. The use of Geo-IP is well known to tailor content to specific locations, to target advertising, or to impose location-based access restrictions. Besides GPS coordinates, Geo-IP is one element for location-based services (→LBS).

Method for identifying the geographical location of a person or institution by means of digital technologies (e.g., GPS or →Geo-IP devices in smartphones and/or →wearables), which enable the offering of location-specific services (e.g., →LBS, →PAYD).

Interpretation of human gestures through mathematical →algorithms to control computing devices. This may occur either via cameras or sensors, which are installed in mobile devices or via →wearables that record and process the movements of the user. Financial service providers have experimented with these technologies to support user interaction, e.g., to control displays or input devices in branch offices and to enable payments for pay-as-you-use services (→PAYU). The aim is to positively contribute to →customer experience.

A global interconnection of different networks to enable the communication of a participant of one network with participants of another network. Gateways are also used as an online electronic identity verification (→eID) service for the international market to support companies in complying with anti-money laundering (→AML) and customer information (→KYC) regulations.

Investment concept, which uses →algorithms to determine the appropriate investment instruments to achieve specific goals within a given period. Relevant factors are the customer’s initial capital and risk preference, possible deposits and withdrawals, and the desired time frame. The approach is present in →robo advisory and →wealthtech solutions.

A method used in decentralized networks (→P2P) to ensure the synchronization of the network →nodes and thus the consistency of the distributed data sets. It is found, for example, in →cryptocurrencies in various forms with the →consensus mechanisms determining how data fields are appended to the database (e.g. blocks in →blockchain systems, transactions in →hashgraph systems). If, for example, more than half of the →nodes acknowledge a new data record, the system adopts it into the distributed data pool. Due to the time requirements and the computing and energy intensity associated with communication, the gossip process has faced limitations in the business environment, in particular when high transaction volumes are present as in the area of payment transactions. In these environments alternative →consensus mechanisms are advocated that involve less communication (e.g., →Ripple).

→Cryptocurrency provided by a federal (government) institution. An important domain of government-backed currencies is traditional central bank money, which recently has seen attempts to be provided digitally as central bank digital currency (→CBDC).

Determines how control occurs in systems of multiple actors, which may be socio-economic, political as well as technological systems. Following systems theory where (super)systems may comprise (sub)systems, governance is apparent on various levels, e.g., on an organizational and a supra-organizational (i.e., →business network, industry or even global level). In the organizational context, standards for “good” governance have emerged (e.g., ISO 37000) with more recent initiatives also focusing on the governance principle for digital technologies (e.g., →AI by OECD or the European Commission). In the context of →digitalization, this includes the governance of electronic networks and →platforms as well as the entire field of →cryptocurrencies (see also the activities of →ISO/TC 307). In the latter case, the design of governance determines the rules in the system (e.g., for →mining, the →consensus mechanism or the tasks of the →nodes) and who decides on the further development of the network. While in →public blockchains that create consensus with proof-of-work (→PoW) principles this is achieved by means of almost basic democratic principles (→DAO), →proof-of-stake systems are based on quasi-democratic principles (→validators) and closed →enterprise blockchains are based on more centralistic or hierarchical principles.

The portmanteau consisting of “hack” and “marathon” describes an event format that takes place in a physical and/or virtual environment during a defined period of time, e.g., 1–3 days. The objective is often to create a competitive and creative atmosphere for the development of business solutions that are often based on information technology (→IT). It combines creativity and the understanding of market requirements with the knowledge of operational processes and software development. Thus, hackathons favor mixed teams with complementary skill profiles and apply existing methodologies like →design thinking, →Devops and →Scrum. At the end of the hackathon, the teams present their solutions in a competitive setting (so-called pitches), receive feedback from a jury and often the best solutions are awarded. Hackathons typically comprise different stages (e.g., preparation, execution and follow-up stage) and may occur in various forms (e.g., →Digithon).

Method in the →Bitcoin system, which reduces the remuneration by half for the →miners after 210,000 blocks were produced or mined by the →miners. For example, from the third halving that took place in May 2020 onwards, miners receive only 6.25 →Bitcoins instead of 12.5 →Bitcoins starting from block 630,001. Halvings take place under the assumption that the reduced money creation will curb the inflationary tendencies of the →Bitcoin and thus have positive effects on its price development. The first two halvings have shown this: in the 12 months after the halving in 2012 the price rose by 8.000% and in the 12 months after that in 2016 by 290%. The next halving is expected for 2024.

In the case of a hard bifurcation, the →protocol or code of the →blockchain undergoes a change that invalidates the old →protocol or code. Therefore, this type of →fork is not downward compatible and existing →nodes must update their software to be able to consider new blocks. The incompatibility of the versions leads to a split and often the old version exists alongside the new one (e.g., with →Bitcoin and →Bitcoin SV).

A data structure in →cryptography named after the scientist Ralph Merkle. A hash tree or →merkle tree is a structure of →hash values of data blocks that resembles the branching of a tree consisting of edges and nodes. Hash trees are thus an extension of hash lists and are intended in particular to ensure the completeness and integrity of data.

This method, known in IT security as the scatter value function, is based on the mathematical conversion of a numerical input of any length into a compressed numerical output of fixed length. The resulting hash values are usually significantly smaller than the original values and have a uniform length. This makes them easier and faster to process than the original values. The important feature is that hash values are one-way functions based on cryptographic procedures (→cryptography), which makes them almost impossible to resolve and, thus, to modify. They are therefore used as digital fingerprints for signing messages or for ensuring data integrity since each change of the input data would lead to a different hash value. For example, the identification of participants and the storage of transactions in →blockchain systems is done via hash functions.

Procedure that allows →interchain transactions or →atomic swaps. It is based on so-called hashlocks, which block the →coins on the respective systems until the other side has unblocked them. Examples exist for transactions between →Bitcoin and →Litecoin.

Like →DAG and →holochain, it is a →data structure that has emerged as an alternative to →blockchain in order to avoid its disadvantages regarding the energy-intensive →consensus mechanism (especially →PoW) and its limited →scalability (e.g., by replacing →PoW with →proof-of-stake). While in →blockchain systems no blocks can be created in parallel and the number of blocks generated per time unit is limited, hashgraph uses the →gossip protocol (“chatter protocol“) to process information continuously and asynchronously by means of an election mechanism (rather than a →consensus mechanism like →PoW or →PoS). A node then passes the signed information (events) to two randomly selected neighboring →nodes (see Fig. 10), which in turn combine it with information from other nodes to form a new event and pass it on to other randomly selected neighboring nodes. This process continues until all nodes are aware of the information created or received at the beginning. Ideally, all nodes have the same view of all transactions. In addition, each →node may determine whether a transaction is valid through virtual reconciliation, by having more than two-thirds of the nodes in the network as “witnesses”. One of the advantages of this method vis à vis the →blockchain is the higher speed of >250,000 →TPS compared to seven TPS (and one block per 10 min) with the →Bitcoin blockchain. However, Swirlds’ Hashgraph (not →open source) has only achieved a low penetration rate compared to →blockchain-based currencies such as →Bitcoin or →Ethereum so far.

Fig. 10
Structure of hash graph (based on Hays, 2018)

Denotes the unit of measurement for the performance of →cryptocurrencies, which use →PoW as a →consensus mechanism. For →Bitcoin, the hash rate refers to the power consumption for generating blocks in 10-minute intervals. In March 2020, it was between approx. 95 and 120 tera hashes per second. It is critical for the stable and trustworthy functioning of the →PoW mechanism that no →node has a majority (>51%) of the hash rate and can therefore influence the block formation in its favor (→double spending).

Denotes a centralized →gateway in →electronic payment transactions that identifies the various processes along the value chain in payment transactions, in particular for card payments. These headend systems exist both on the →issuer and on the →acquirer/merchant side. In the card business, the →acquirer’s headend sends the →authorization request from the merchant to the →issuer’s headend, which performs a final confirmation/debit of the account and sends a response to the →acquirer’s headend for the final approval or rejection of the card transaction. For example, four headend transfer points (one per banking association) have been established for processing transactions across institutions/associations within the framework of the agreement on the “national ATM-Association” (NOV) of the German banking industry.

Refers to →startup companies in the healthcare sector that offer innovative digital solutions in the field of →electronic health.

HedgeTrade is an →Ethereum-based →cryptocurrency that aims at →social trading. Participants use their market knowledge and assessment to create a price forecast in which other participants may invest. If the forecast comes true, the creator receives the →coins, if it does not, the creator has to refund them.

With the →digitalization of processes on →electronic exchanges, high frequency trading occurs when systems execute high trading volumes automatically with short holding periods (→algorithmic trading). The →algorithms execute the orders partly in the microsecond range and can thus achieve arbitrage gains due to the high amounts involved.

Saying that has spread in the →Bitcoin community to resist the strong bull movements of the →cryptocurrency and keep their investments in the currency.

Another alternative to →blockchain based →DLT systems besides →DAG and →hashgraph. Similar to →hashgraph, it uses a →gossip method instead of a →consensus mechanism and is based on the concept of distributed hash tables. These are independent local datasets (→ledgers) that can search each other according to a defined search procedure. For example, the distributed datasets are queried until the desired content is retrieved. It is particularly suitable for implementing distributed →applications (→DApps) but is not widely used yet.

Agreements on the home banking interface that have been in place since the mid-1990s as a result of an industry-wide standardization initiative in Germany. With the participation of players from the three sectors of the German banking industry (cooperative/mutual banks, public sector institutions and private banks) and the German central credit association “Die Deutsche Kreditwirtschaft”, the various versions of HBCI have created an open standard (→open source) that defines security procedures (e.g., PIN/TAN) and numerous functionalities (so-called business transactions such as individual and collective transfers or the display of account balances). Due to its broad support in the German banking industry, HBCI is an important basis for →multi-bank relationships and was renamed →FinTS in 2002.

An emulator is an information system that replicates another system in certain aspects. In the case of HCE, a software takes on the function of a physical hardware, which can be found particularly in the card area (ID cards, health insurance cards, bank cards, and so on). Thus, HCE emulates the security chip in →mobile payments and eliminates the need for a separate SIM card from the mobile network operator for payment processing. It forms the basis of many well-known smartphone-based →NFC payment methods (e.g., Apple Pay, Google Pay), in which the payment network providers (→EMV) transmit a security →token to the mobile payment provider and use this token to carry out secure →NFC communication with the payment terminal. Thus, the payment network provider acts as a token service provider (→TPS) while the →payment service provider (→PSP) acts as a token requestor.

Refers to the storage of →cryptocurrency online, i.e., in internet-based →wallets or →wallets that are connected to the internet. In contrast to →cold storage, they are regarded to present a higher ease of use, but also involve greater security risks.

A check that is used to determine whether a →token is a →utility token or a security token. The test dates back to an examination by the US Supreme Court in 1946 when it was necessary to decide in a lawsuit whether a transaction was an investment contract or not. If it is an investment in a company with the prospect of making a profit, the Howey test is positive and a →token is →classified as a security token.

→Cryptocurrency based on →Ethereum, issued by the operator of the crypto platform (→crypto exchange) Huobi. It is primarily used to settle the fees on the own trading platform.

→Blockchain or →DLT framework published in 2015 by the Linux Foundation, which has been developed by a consortium of well-known companies from the finance, logistics and →IT sectors (including ABN Amro, Accenture, Cisco, Deutsche Börse, IBM, Intel, J.P. Morgan, →R3, State Street, Wells Fargo). Like numerous →blockchain frameworks, Hyperledger is designed as →open source, but is intended to have a higher performance than →cryptocurrencies such as →Bitcoin and to offer comprehensive functionality (e.g., regarding the →consensus mechanisms used, access control or →smart contracts). The Hyperledger framework lacks an own →cryptocurrency and aims especially at the realization of →enterprise blockchains. Hyperledger Fabric has experienced the greatest adoption in the domain of →permissioned blockchains.

Term for providers of →cloud computing services that are able to realize high economies of scale and thus cost advantages due to their size. Examples include Amazon (Amazon Web Services), Google (Cloud Platform), Microsoft (Azure) as well as IBM (SoftLayer), Oracle (Cloud) and Salesforce. Compared to companies in other industries, financial service providers (major banks as well as →startup companies from the →fintech sector) tend to make more frequent use of hyperscaling services.

Approach for the administration of identities and permissions in companies, which is usually based on a separate →application system or module that is linked to other →application systems of the company. The aim of the master data, which are usually managed on a central identity data management (IDM) server, is to achieve a high degree of consistency and integrity of the data to enable →front-, →middle- and →back-office areas to access data for →authentication and →authorization purposes. Identity management is usually a prerequisite for channel strategies (→multi-channel, →omni-channel) and →SSO. With the move towards →multi-bank relationships (e.g., due to →PSD2) and the use of →digital identities in other areas of life (e.g., health, public administration), services for identity management have become established. Among the solutions that are also known as →KYC, are centralized solutions (e.g., PostIdent, Verimi, Veriff or WebID) as well as decentralized solutions based on →blockchain technology such as Hyperledger Indy, Sovrin or Vetri (→SSI).

Corresponds to and →authentication procedure where a user provides his credentials, which are then checked by a provider (→KYC). It is the prerequisite for →authorization or →legitimation for the service offerings of financial service providers.

Term for a electronic payment network in India that supports real-time payment processing (→RTP).

Refers to applications in which the vehicle is the main channel of distribution and communication. Passengers may use in-car electronic (financial) services via corresponding devices (e.g., displays, →AR, →wearables).

Describes the progression in small steps to achieve something. After each step, self-reflection and reassessment of the performance is carried out. When combined with an iterative procedure these steps are repeated within the framework of continuous repetition until the solution or the desired improved state is satisfactorily achieved. Incremental procedures are found in numerous methods that are common in →startup companies (e.g., →design thinking, →DevOps, →Scrum).

Originating from the medical field, where incubators serve to raise for premature creatures, e.g., in the breeding of chicks, to ensure the optimal environment for rearing or development at an early stage of life. In the →startup sector, it refers to the state in which a company can develop under the best possible conditions in a non-competitive-market environment. The incubator promotes this state with the aim of generating growth in order to increase the market value of the →startup company. Incubators are often institutions, bodies or private investors who accompany and support a →startup company on its way to independence in various ways, e.g., with venture capital (→VC) or know-how. For →startup companies in the →fintech sector, the term →fintech incubator is also used.

Term for companies that are established in an industry and receive a challenge from new players (→startup) in the course of technological →disruptions, such as the →digital transformation. Incumbents in the financial sector are typically the banks challenged by →fintech companies or the insurance companies challenged by →insurtech companies. If incumbents are not successful in mastering the change, they might run into the →Kodak trap.

A concept that refers to the extensive →digitalization of processes in production companies by integrating all resources (e.g., machines, conveyor systems, workpieces, materials, warehouses) and processes within and between companies by means of →IT. The term cyber-physical systems (→CPS) is also used to describe the networking of intelligent machines (→M2M), storage systems and operating resources. Together with →IoT technologies and decentralized control logic, these systems are increasingly replacing a centralized control of processes with more flexible decentralized procedures (e.g., Kanban, negotiated solutions) in real-time (→real-time processing). I4.0 concepts are present not only in the area of physical manufacturing processes, but also for information-based services and processes such as those found in the financial sector (e.g., →back-office processes).

Due to the large number of →followers in their social network, influencers have a high reach with their own social media contributions and are therefore considered to influence opinion formation. Influencers have become an important part of online marketing, especially for purely digital companies such as →fintech companies. An overview of influencers in the →fintech sector may be found at Influencer.World.

(1) From a functional point of view, the term refers to information processing technologies. Although these can also be realized non-electronically, with the advent of the computer age from the middle of the twentieth century onwards, IT has become synonymous with electronic data or information processing as well as information and communication systems (ICT). IT systems consist of a hardware and a software system, which can be divided into computer hardware with peripherals and system and application software (→application). →Cloud computing has led to virtualization, which makes IT resources more flexible. (2) From an institutional perspective, IT often refers to the organizational unit of a company responsible for the deployment and operation of IT systems. Due to the relevance of software development and the operation of IT systems in →fintech companies, the responsibility for IT should be located at top management level (and not in sub-departments). (3) From an economic perspective, IT refers to all areas or sectors of an economy that comprise hardware and software providers, telecommunications companies and service providers, and increasingly also media providers and service providers.

Also known as a →crowdsale or token generating event (→TGE), an ICO is based on a company’s going public (→IPO). In the ICO case, the investor first receives a virtual equivalent in the form of a →token for real money, which is a →virtual currency or a →cryptocurrencies. Depending on the type of →token, the countervalue may also be a →service or the right to obtain a product that is still under development. Figure 1 shows the process of an ICO after a credit auction (→crowdlending). Two investors have agreed to make a total of 30,000 € available to a borrower via the →platform (step 1). The →smart contract documents the debt relationship and contains the credit conditions such as interest (in this case 5.5%), term, loan amount and balance. The investors receive 10,000 or 20,000 →tokens in their →wallets and the borrower receives the payout of 30,000 € (steps 2 and 3). Steps four to six contain the monthly repayments (paybacks), which result in an update of the balance in the →smart contract and a payout to the investors.

Fig. 1
Process steps of an ICO (see Swisspeers, 2019)

Financing strategy in which (→startup) companies obtain their financing entirely via →crypto exchanges. The exchange provider conducts appropriate checks (e.g., due diligence) and takes over the entire →ICO process.

The terms “primary offering” or “going public” refer to the going public of a company. For →startup companies, this is usually the result of several successful rounds of financing and the hope of raising substantial capital.

Based on the translation of the Greek word “Innovatio” for renewal and “something newly created”, innovation describes a new idea and its implementation. The essential characteristics of an innovation are the reference to an innovation object (a →business model, product, process or technology innovation, see Table 1), the degree of novelty (either →disruptive or gradual innovations) and the application or marketability of the invention. In the financial sector, the →fintech term is inherently linked to innovations, which in the age of →digitalization are often technology-induced innovations (e.g., through the application of →big data, →blockchain, →IoT or →AI technologies). Innovations may also stem from market- or demand-driven impulses such as an improved →customer experience. Regarding the area of application in banking, the →term fintech is used in addition to the term →banking innovations to also comprise innovations from the insurance sector (→insurtech).

Table 1

Areas of innovation in the banking sector (see Alt & Sachse, 2020, p. 225f)

Innovation area	Examples from banking innovations
Strategic innovations
Business model	→Crowdfunding, →PAYU
Product/service	Advisory among customers (→P2P)
Organizational innovations
Process	→Mortgage comparison, online mortgage
Organization	→Outsourcing, single point of contact (→SPoC)
Technological innovations
→Application system	Personal finance management (→PFM)
Infrastructure	Hardware for secure information transfer (→token)

Denotes a →sourcing strategy that aims at the (re)integration of tasks into the own organization. For example, a bank might decide to take over back-office functions from competitors to foster their →business model as a →transaction bank. Similarly, a →fintech company might insource their accounting function, which was previously performed by an external tax advisor. In competitive markets, insourced tasks should closely comply with the organization’s core competencies.

Applied scientific discipline which may be regarded as a within the →business information systems discipline and deals with the application of technologies for the automated processing of insurance company data as well as for supporting insurance business processes.

The combination of “insurance” and “technology” describes a subset of →fintech solutions in the insurance sector. Insurtech companies are →startup companies that provide digital solutions for improvements and protection (→fintech). Examples for insurtech solutions are meanwhile present in all lines of insurance (e.g., life, property and health insurance). Similar to the →fintech companies in the banking sector, partnerships with existing insurance companies (→incumbent), but also with products and service providers (e.g., →e-commerce, →smart service, →mobile service) can be increasingly observed. These collaborative settings (→collaboration) are particularly suitable, since underwriting and carrying risks are subject to regulation, which is not the case with advisory and brokerage services. One model, for example, is the development of an innovative insurance product by an insurtech →startup company coupled with a cooperation with a primary insurer as risk carrier and with a distribution partner (e.g., a bank) for the distribution of the insurance product.

→Business model of an intermediary (→intermediation) based on the bundling of →services combines services of different providers. In contrast to the →aggregator model, the focus is less on →intermediation, but rather on linking →services along a value chain (provider view) or a problem-solving process (customer view). The essential value contribution of integrators may be seen in the coordination of →services to form a comprehensive →service for customers (→customer experience). In the banking sector, for example, central institutions such as Germany’s mutual bank DZ-Bank provide integrator services for other banks in their →ecosystem. Integrator models are also present in payment transactions when providers such as Klarna or PayPal support a variety of electronic payment procedures (→electronic payments).

An intelligent virtual assistant or intelligent personal assistant (→IPA) is a software →agent that can perform tasks or →services as a virtual employee for a person based on commands, rules or questions. The term is often used synonymously with →chatbot and virtual assistants (→virtual assistant). Some of them apply artificial intelligence (→AI) to interpret human speech (→NLP) and to respond via synthetic voices. Users may interact with their assistants and ask questions or manage business tasks such as emails, to-do lists, and meetings via verbal commands. Other forms of AI-based IVA in the financial sector may be found in the field of →chatbots in advisory (→robo advisory) and customer service processes.

Refers to transactions in →DLT or →blockchain systems that take place between different →cryptocurrencies. In contrast to trading →coins via trading platforms (→crypto exchange), interchain transactions occur directly or between the respective →cryptocurrencies. Similar terms aiming at the →interoperability of different →DLT frameworks are →cross-chain, cross-ledger interoperability (→CLI) and →multi-chain.

For credit card payments in the →four-corner model, IF are payments made from the →acquirer to the →issuer. These form a part of the merchant service charge (→MSC) that is billed by the →acquirer to the merchant. In the case of →EMV, the IF for debit and charge or credit cards in Germany are often in the range of 0.20% to 0.30% of the transaction value.

Describes a →business model that links two tiers in a value chain, for example, buyers and sellers. Depending on their functions, there are various forms of intermediaries (e.g., →aggregators, →brokers, →digital marketplace, →integrators) that add value to market participants (e.g., improved market overview, simplified transaction processing, independent trust authority). In return, intermediaries charge fees, thereby increasing costs in value chains. Intermediation underlies many →fintech initiatives and is the countermovement to →disintermediation.

Standardized syntax for an international account number consisting of the →bank code, a check digit and the country code. The IBAN code was created in 1997 on the basis of numerous national numbering systems through the initiative of →ECBS and is now internationally certified as →ISO 13616. It features a length of up to 34 digits, which varies among countries. In Germany, the IBAN has 22 digits and consists of the eight-digit bank code (→BLZ) and an institution-specific account number, as shown Fig. 2.

Founded in 1947, the standardization organization ISO comprises representatives from currently over 160 countries and, as an independent non-governmental organization, aims to develop standards to simplify trade. Since its inception, ISO has developed standards in many sectors (e.g., telecommunications, agriculture, healthcare) and for many applications, including the financial sector (→ISO 20022). Development is carried out in over 250 technical committees (TC) according to a defined standardization process. For example, since 2017, →ISO/TC 307 has been working on the development of standards for →blockchain and →DLT applications, which were published from 2020 onwards. In addition to ISO, there are other standardization organizations, some of which are in competition with each other. These include technology-oriented organizations in the internet (e.g., World Wide Web Consortium, W3C) or in the blockchain context (e.g., →EEA) as well as industry-related organizations such as →BIAN, →SWIFT or the Blockchain in Transport Alliance (BiTA).

This standard by →ECBS specifies an international payment instruction. The so-called EBS206 document contains both the →BIC and the →IBAN. With the introduction of →SEPA payments, IPI has become less important in the Euro area and is only occasionally used outside this area (e.g., in payment transactions with Switzerland).

Internationally valid standard for the semantic denomination of securities, which dates back to the US company ISIN Network and has been available since 1990 as →ISO norm 6166. ISIN consists of 12 digits with the first two letters specifying the issuing country according to ISO 3166-1 alpha-2 (e.g., DE for Germany), the following nine numerical digits specifying the national security number (→NSIN such as the security identification number →WKN in Germany), and a concluding check digit. ISIN is used by numerous national and international clearing systems (→ACH) and is likely to replace national identification systems such as the →WKN in the future.

Initiative launched by the German association “International Token Standardization Association (ITSA) e.V.” for the standardized identification of →tokens in →cryptocurrencies. Similar to the concept of the security identification number (→ISIN, →WKN), the ITIN identifies the various →tokens and provides an eight-digit alphanumeric identification number and one check digit. Among other things, the uniform designation is intended to prevent different →crypto exchanges from trading the same →cryptocurrency with different symbols (e.g., →Bitcoin Cash as BCC or BCH) and also allows identification across →forks.

Refers to the networking of real-world objects by means of →digitalization based on extensive automated machine-to-machine (→M2M) communication. The aim is the comprehensive integration of sensors, processors and actuators in operational and/or social applications. Mundane objects equipped with IoT technology are able to record environmental information and to act on events based on pre-defined rules. It is expected that such rules will increasingly be replaced by more adaptive →AI →algorithms, which may render IoT objects to act more autonomously. IoT is considered an important driver for →digital transformation along the value chain and for integrated concepts such as industry 4.0 (→I4.0). The elements of IoT architectures may be divided into three levels (see Fig. 3): The infrastructure level manages hardware and network technology, the platform level includes services, storage resources and →middleware, and the application level provides the →front-end to the various user groups.

Fig. 3
Elements of an IoT architecture (Capgemini, 2020)

The acronym from internet of things (→IoT) and the smallest letter in the Greek alphabet Iota denotes a →cryptocurrency launched in 2015. The →open source quantum-proof →protocol, also known as →Tangle, is based on a direct acyclic graph →data structure (→DAG), which offers improvements regarding →scalability and secure data transfer compared to →blockchain technologies. The suitability for the →IoT environment stems from fee-free transactions, so that frequent transactions (e.g., status data, payments) between devices are also viable from an economic perspective.

Refers to the ability of organizations and →applications to work together. As an important success factor in networked business models (e.g., →collaborative business, →open banking, →sharing economy, →sourcing, →smart service), the organizational and technological interoperability influences the →transaction costs between organizations. The existence of industry-wide or cross-industry standards is considered an →enabler for achieving interoperability. These include standards for business processes (e.g., →BiPro), application interfaces (→API) or data semantics (→BIC, →IBAN) and syntax (→EDI, →ISO 20022) as well as the use of dedicated →applications for integration (→middleware). Interoperability is also relevant, when data needs to be transferred between different →cryptocurrencies, since neither the →data structures nor the →coins are currently standardized across distributed ledger (→DLT) →frameworks. Appropriate approaches for →interchain transactions and →digital identities are emerging for this purpose (e.g., Chainlink, →Corda or →Cosmos).

Describes the →interoperability of →coins of a →cryptocurrency or →blockchain framework.

The combination of “investment” and “technology” refers to →business models that offer digital investment services and often apply →AI to determine the appropriate strategy and actions for financial investments. Examples are established in the field of portfolio management, in particular with →robo advisory systems.

ISO 20022 is an →ISO message standard, also known as →UNIFI. It specifies data and message formats for processing financial transactions, especially in payment transactions. Well-known examples in Europe are →SEPA credit transfer (→SCT) and SEPA direct debit (→SDD). ISO 20022 comprises eight parts, including an overarching (data) meta-model, data models in UML notation and XML schemas for implementing the total of more than 400 already specified messages. An example scenario in the →four-corner model is shown in Fig. 4. The importance of ISO 20022 is expected to increase in the future through its use in the →TARGET and →SWIFT systems.

Fig. 4
Message exchange scenario in payment transactions with ISO 20022 (ISO, 2020)

Technical committee of →ISO for the development of a standard for →DLT and →blockchain technologies. In addition to terminology and architecture, the areas of work include →interoperability, security, →smart contracts, →governance and use cases. First documents were released in 2020.

In the payment area, there are two interpretations for issuers. (1) In a narrower sense this is a financial institution that provides cardholders with the payment instrument and maintains a contractual legal relationship with them. The issuer uses an issuing license of the respective →payment system, which yields access to the payment and acceptance network. In addition, the issuer takes accountability for the marketing and sales of the payment card, as well as the acceptance and processing of card transactions at the →ATM. (2) In a broader sense, an issuer denotes an organization (company, authority or investment company) that issues securities (e.g., shares, bonds, →cryptocurrencies) or payment instruments (e.g., debit, credit or prepaid cards) to customers and is subject to supervision. →Fintech companies such as Revolut cooperate with issuers like American Express, Discover or banks (e.g., Wells Fargo, Deutsche Bank UBS).

Coding to identify the →issuer of a financial instrument with a length of six or eight digits after the revision in 2017. Since the issuing organizations are often banks, the IIN is also referred to as bank identification number (→BIN) but differs from the bank identifier code (→BIC).

An iterative approach aims to reach a defined goal in small steps (→incremental) and foresees continuous repetition cycles (iterative). A well-known methodological →framework in technological and →innovation projects is →Scrum.

Structured, text-oriented and thus human- and machine-readable data format that is used for communication between →application systems. It has seed wide adoption especially in combination with →API and →REST-based interfaces. An example of a message in JSON format is shown in Fig. 6 for an exchange rate query at the British →smartphone bank Revolut in chapter “A–D”.

Originating from the Japanese word for card, note, board or receipt, it dates back to the invention of the Toyota production system in 1947. Kanban implements a decentralized control method with self-controlling loops between a requesting and a supplying point. The cycles are demand-driven based on so-called Kanban cards, which are placed by the requestor on a Kanban board and then trigger the production of new items. The procedure is widespread in logistics processes and has also found its way into agile software development and agile project management (→agility) for the coordination of tasks between teams.

Structured overview of the product and/or service information of investment funds. These information sheets describe the nature of the financial instrument, how it works and the associated risks, profit prospects and costs.

Refers to a performance metric or key figure that reflects aspects of the company’s performance, i.e., operational successes or failures. KPIs measure the degree of achievement with regard to operational objectives or →critical success factors within (e.g., revenue, profit) or outside an organization (e.g., growth, market share) and are closely related to controlling. They support decision-makers and investors in evaluating and managing processes, which is the basis for taking appropriate action in the event of deviations from defined targets. Different areas of a company require different KPIs, e.g., key figures such as market share or brand coverage image are relevant for the marketing department, while for accounting it is more likely to be variables such as profitability or cost recovery. For investors in the →startup environment, KPIs such as return on investment (→ROI), net present value (→NPV) or profitability of product development (→RoPDE) are the most important. A well-known structuring approach for KPIs is the balanced scorecard, which distinguishes KPIs in the areas of finance (e.g., sales, profit), customers (e.g., customer satisfaction and profitability), internal processes (e.g., process costs and throughput times) as well as potential (e.g., time-to-market, employee turnover) and suggests that these areas should be equally addressed (i.e. balanced). The example of a balanced scorecard is shown in Fig. 5.

Fig. 5
KPIs in the balanced scorecard (based on Kreutzer et al., 2018, p. 187)

“Get to know your customer”or “Know your customer”are not only phrases from marketing, but regulatory requirements that mostly financial institutions must comply with. They need to ensure that new customers or suspicious existing customers are checked for legitimacy in order to prevent money laundering (→AML), terrorist financing (→CFT), etc. KYC is a process within a company for checking the identity of its customers (→authentication), but is also found in the environment of banking regulations, i.e., by purely digitally operating financial companies (e.g., →direct banks, →PDI) during acquisition. The goal is to know customers as if they were personally present. With the opening of bilateral bank-customer relations by means of the →PSD2 regulation, KYC procedures that are applicable across banks (→multi-bank) have gained in importance. Financial companies have therefore developed their own →identity management solutions or used external →services (e.g., nPA, Verimi, Veriff, Yes) and standards (e.g., Blockcerts, OAuth, OpenID, Liberty Alliance). In contrast to the established solutions, which follow a centralized architecture model, decentralized approaches have emerged that are more in line with the principle of consumer sovereignty (→SSI).

An →authentication procedure that identifies end users via pre-defined security questions in order to obtain →authorization for using digital services.

This notion was coined when the dominant manufacturer of analog cameras failed to master the transformation to digital photography and refers to a key problem of →innovation. When companies like Kodak are successful in an existing technology, this success tends to harm the ability and openness for disruptive change (→disruption). Kodak recognized the rise of digital technology too late and fell behind competitors. Analogies to the Kodak trap may be found in the financial sector, for example with the transition from physical to →virtual currencies or with the (future) substitution of →incumbents by decentralized technologies (→DLT) and decentralized finance (→DeFi) concepts.

Refers to the sixth phase of →VC financing and includes financing of acquisitions, succession arrangements, consolidations or restructurings, buy-outs, turnarounds as well as →bridge finance.

Describes the initial phase of a project that may be the start of a business or the introduction of a new product, →service or software. For →startup businesses, founders aim try to specify and validate the →business model during the launch phase. This is typically done →iteratively and fundamentally (→pivot), as the idea and plans often need to be adjusted during the search period due to dynamic technological change on the one hand and the market environment on the other.

Describes the “industrialization” or professionalization of the initial phases of starting a new business (→startup). Lean startup divides the →startup process in several phases in order to maximize capital efficiency. Besides favoring a sequential approach (instead of a one-time “big bang”), lean startup advocates an experimental approach (e.g., by means of early →MVPs) instead of an (too) elaborate planning of all steps (e.g., of →business plans that are differentiated in detail) and prefers the close →collaboration with customers over a purely intuitive approach.

In economic and social life many forms of ledgers are present, such as general ledgers, (e.g., cash, stock or subsidiary) books, journals, accounts or registers. From the →IT perspective, a ledger is a collection of data (or transactions) organized according to a specific →data structure. Each economic entity usually has one or more ledgers that ideally work neatlessly together in economic structures where division of labor is present (→digital value creation). Systematic reconciliation and synchronization of distributed databases is at the heart of distributed ledgers (→DLT), which are currently attributed a high potential for efficiency and change (→disruption) in the financial sector.

Notion for a software system (→application system) that has been in operation for some time and is in discussion with the introduction of new systems. Often, the legacy system has the advantage of being functional and reliable but fails to support novel requirements regarding new functionalities and system infrastructures, security standards and interfaces or modularity and architectural requirements. Among the well-known examples in the financial organizations are →core banking systems that have been developed internally by many (especially larger) banks and have become the backbone of many operations. In view of the →digital transformation, many banks and insurance companies decided to integrate or even replace these systems with newly developed (or purchased) systems. Compared to →incumbents, it is considered an advantage of young →fintech businesses that they lack the “burden” of legacy systems and may start developing their solutions on a “green field”.

This US-based →crowdlending marketplace was founded in 2006 and aims to broker funds from private individuals to private individuals within the a loan transaction. Following the peer-to-peer model (→P2P), the allocation of funds focuses as far as possible on individuals and less on groups as financiers.

As an area of decentralized finance (→DeFi), lending pools enable decentralized lending and borrowing among individuals (→P2P). These →crowdlending services are based on →cryptocurrencies like →Maker, Compound or →Aave and aim at automatically providing collateral-based loans in →real-time. Typical collaterals are →digital assets, which trigger →smart contracts for providing the loans and for paying interest on these loans (→liquidity pool).

Extension of the →Bitcoin blockchain to increase the performance of payment transactions. For example, this includes increasing the block size from one megabyte to 32 megabytes for →Bitcoin Cash. As Bitcoin improvement proposal (→BIP) number 112 it aims at enabling →off-chain payments, in particular the processing of →micropayments. In addition, the lighting network is intended to improve the execution of →cross-chain transactions (→interchain).

Refers to the ability to execute transactions in (electronic) markets at all times. In liquid markets, suppliers and buyers have the opportunity to find a market partner, which requires that a certain minimum number of offers to buy or sell need to be present in the market (→critical mass). In order to ensure liquidity in certain product or market segments, (electronic) stock exchanges have specialized market makers who place offers (see →AMM for crypto markets).

This concept within decentralized market and trading systems (→DeFi) aims at creating →liquidity automatically via →smart contracts instead of centralized →order books. The latter support the exchange (“swap”) between two different →tokens (e.g. →ERC-20 tokens in →Uniswap). Several participants may provide →tokens in a pool and receive a fee for their role as liquidity provider for each executed transaction (e.g., 0.3% divided equally among all liquidity providers in →Uniswap). Similarly to market-makers who quote prices in centralized exchanges, users ensure the →liquidity of the market. Since the →smart contract represents the “counterparty”, the terms “automated market maker” (→AMM) and “peer-to-contract” are also used.

Litecoin is a →cryptocurrency, which offers a decentralized →open source payment network. It works similar to →Bitcoin, but uses reduced mining times (one new block every 2.5 min instead of 10 min for →Bitcoin) with a total volume of 84 million →coins (instead of 21 million for →Bitcoin) and a more complex encryption →algorithm.

This indicator (→KPI) is frequently used in practice to measure loan collateral and, puts the loan amount in relation to the amount of the investment (e.g., the market value of a property). It serves to check the creditworthiness of the investment to be financed and to set a lending limit. →Fintech companies (e.g., in the area of →crowdlending) use it to support creditors in their credit assessment.

Location-based services use the →geolocation technology of mobile devices to determine geographic data in real-time (→real-time processing) to provide users with personal or location-specific information. Once users have given their consent (→opt-in), LBS may identify the location (e.g., an address) automatically without the need for manual data entry. Advantages for the user include being able to check-in to restaurants, shops, concerts and other locations or events online and to receive corresponding context-specific offers or news. Financial service providers may, for example, offer (micro) credits or insurances (e.g., when buying skiing equipment or ordering an insurance before a steep descent).

Manufacturing machinery equipped with sensors and/or other computing devices (e.g., →IoT) is able to automatically communicate directly or via a centralized management and control system (e.g., a production planning and execution system). Use cases are integrated concepts like →industry 4.0 in the industrial sector and contactless payments (→M2M payment) or pay-as-you-use (→PAYU) models in the service sector.

Describes a communication between two machines (→M2M), whereby a payment transaction between two electronic devices takes place without human interaction (e.g., PIN entry). It is now widely used for contactless card payments at the →point of sale using →NFC technologies (e.g., credit card, smartphone).

This field of →AI comprises →algorithms that enhance machines or →application systems with learning abilities or adaptive behavior. For this purpose, ML distinguishes between different learning styles or forms of learning, which pick up (“learn”) a behavior based on training data in a supervised or unsupervised procedure. While supervised learning presupposes the definition of an initial learning model and training data, unsupervised or reinforcement learning learns the behavior through experience or through the feedback received. Among the →algorithms for the respective procedures (see Fig. 6) are regression models, decision trees, clustering procedures or artificial neural networks with →deep learning for supervised learning. Among the use cases in the financial sector are fraud detection, market analyses, language or text recognition in the processing of paper documents.

Fig. 6
Forms of learning in machine learning (based on Lanquillon, 2019, p. 103)

The phrase “with a little magic” describes the enrichment of an activity or product with a differentiating value proposition. This is often the result of a (creative) development process that leads to product, process or business model innovations (→innovation) and is a common way to create →fintech →business models.

→Cryptocurrency based on →Ethereum, which is designed as a →stable coin against the US dollar and aims to be used as a currency in various decentralized financial applications (→DApps, →DeFi).

In →blockchain →data structures this is the longest block sequence that may be traced back to the →genesis block. Additional sequences resulting from the main-chain are →sidechains. The conceptual pairs main-/master-chain and sidechains are sometimes used synonymously with parent/child chain.

Refers to lending via electronic platforms (→digital marketplace) which often pursue the peer-to-peer (→P2P business) model (→crowdlending, can also happen) and foresee lending without existing intermediaries (→intermediation). Since both natural persons and legal entities can act as lenders, the default risk is borne directly by the capital providers and not by a legal entity such as a bank.

EU directive on the harmonization of financial markets, which dates back to 2007 and is now in its second version (MiFID 2), valid since 2018. The aim of the regulation is to improve investor protection and the transparency of the financial markets. This includes the obligation to declare investment recommendations and to disclose commissions, to ensure best execution by financial service providers and to document transactions on the financial exchanges (→electronic exchange).

Approach to flexibly adapt the range of services to customer requirements, which aims to combine a high degree of →personalization with a high degree of efficiency. MC allows customers to individually configure goods and services, such as clothing, vehicles, travel or financial services. The basis for this is the standardization of service or system components or modules (e.g., equipment variants in vehicles) along general solution models (e.g., a vehicle consists of certain components), which span a solution space of possible configurations. The matching of customer requirements (the problem space) with the components from the solution space is usually done by means of configurators (e.g., →robo-advisory), which are used either by consultants or by the customers themselves (→self-advisory).

Describes a →node in →blockchain networks that has a complete copy of the distributed database (→distributed ledger) stored within itself. Depending on the →cryptocurrency (e.g., →Dash), this participant may qualify for remuneration in the form of →coins. In →cryptocurrencies that have implemented the →proof-of-stake →consensus mechanism, this represents a revenue opportunity for →validators similar to the →miners in the →PoW model.

Describes the need to re-enter data between different media, which may be physical (e.g., paper, DVD, USB sticks) or virtual (e.g., →application systems) in nature. Breaks occur when data has to be transferred from one medium to another. In the physical case, this occurs when data is transferred between paper forms or between paper and an →application system. In the virtual case, data is transferred or manually (re)typed from one →application system to another. The discipline of →business information systems attempts to avoid the inefficiencies associated with media breaks in the form of error potentials, delays as well as costs in time and workforce with the design of digitalized business processes supported by integrated →application systems (e.g., →core banking system, →ERP). In addition to designing digitalized business processes in intraorganizational systems and to using electronic documents for interorganizational integration (→EDI), the use of →robots to automate manual data transmission activities (→RPA) is a nother possibility to address media breaks.

Denotes an extension of the Bitcoin →blockchain (→BIP) that creates a buffer for unconfirmed →Bitcoin transactions at each →full node. This is necessary to manage peak loads and bridges the time between the verification of the transaction by the →node and the processing by the →miner. The size of the mempool varies with the number of cached blocks and amounts to 3 MB for three blocks.

Service fee charged by the →acquirer to the merchant for e.g., credit card transactions, which the merchant can include in the sales price. Frequently, the fee is calculated as a percentage of the transaction value plus a transaction-fixed fee (e.g., for →authorization). The MSC reflects the →acquirer’s transaction processing costs and, together with the interchange fee (→IF), gives the total cost of a card transaction charged to the customer. The calculation of an Amazon Pay payment in Fig. 7 shows this principle.

Fig. 7
Fees for a card payment using the example of Amazon Pay (Amazon, 2020)

This →symmetric encryption mechanism is used in →electronic payments to ensure the integrity of messages and that the sender is authorized to access accounts or to initiate transactions. Contrary to →asymmetric encryption it is based on a →private key that is shared among the parties and lacks a separate →public key.

→Protocol for machine-to-machine (→M2M) communication that allows the real-time transfer of telemetry data between devices. For example, it is used between payment terminals at the point of sale (→PoS) such as vending machines, →mobile payment terminals or other →IoT devices. Recent solutions are based on →APIs that follow the →REST principles.

Describes the possibility of customers to interact with companies within a messaging or chat application (e.g., Facebook Messenger, →WeChat). Customer support is provided, for example, via (voice or text) chat on the homepage using →chatbots. Such approaches can be found in →Social CRM.

Notion from a science fiction novel by Neal Stephenson from 1992 that has recently spread to denote a comprehensive virtual world created by virtual (→VR) and augmented reality (→AR) technologies. Similar to the Second Life environment that was launched by Linden Labs in 2003, metaverse represents a separate world besides the real world where users are present as avatars and are able to purchase goods or properties and to conduct transactions via digital technologies (e.g., →cryptocurrencies). Among the early examples are Decentraland where events (e.g., concerts, exhibitions) take place, the gaming platform Roblox where users are able to purchase items as well as the Horizon platform announced by Facebook, which even renamed itself into Meta at the end of October 2021 to reflect the importance of the metaverse.

Granting of small (micro) loans to people who are not served by traditional banks, due to poverty or to companies whose borrowing requirements are too low to receive loans from traditional banks. The microfinance industry that developed has its origins in the emerging markets and has spread to Europe and Germany with the rise of →startup or →fintech businesses. At present, microfinancing has become a specific financial instrument for →startup businesses that operate with low debt capital requirements and is reflected in →crowdlending platforms such as Kiva.

Payments with low payment amounts are in the range of up to 5 € and tend to exhibit process costs that exceed the payment amounts. For example, →e-payments such as credit card payments often require minimum amounts and special procedures have been established for small amounts (e.g., cash card, →mobile payment).

In contrast to the often monolithic (or “one-piece”) architecture of →application systems (e.g., in →core banking systems), the architectural principle of microservices aims at a modular design of →applications. Since it is more lightweight than the complex monolithic architectures, it has become also common in the →fintech sector. →Crowdlending solutions could, for example, include microservices for credit registration, credit scoring, debt collection or customer analysis. Companies such as Modularbank have built their platform on microservices, and microservices are also found in →open banking concepts. They may be implemented using →web service technologies, often using →REST.

Organizational and process area of financial service providers that is concerned with the ex-ante verification and ex-post control of transactions. This also includes cross-functional organizational units such as risk management or product development, which are “downstream” of the →front-office and “upstream” of the →back-office.

Denotes a middle layer in software system architectures and forms an approach for the integration of →application systems. While a bilateral coupling of system components or modules leads to a high complexity of connections, the concept of middleware aims at reducing this complexity by adding a layer that manages the interfaces. As shown in Fig. 8, one component accesses many other systems (or modules or →services) via this middleware layer. Depending on its functional scope, the middleware takes over this coordination between the →services, e.g., the administration of the interfaces (→API) in directories, the flow control or the assignment (mapping) of data formats.

Fig. 8
Bilateral integration and integration via middleware (based on Alt, 2018a, p. 124)

Derived from the activities of workers in physical mines, miners are participants in a →cryptocurrency network who perform the task of →mining. They compete for the calculation of new blocks, whereby successful miners generate the blocks and store the transactions in the distributed database (→ledger). In return for this mining of blocks and the provision of the necessary computing power, miners receive a remuneration in form of →block rewards.

Based on the philosophy of prototyping, users should receive an impression of a new solution (product and/or service) with sufficient or minimal basic functions at an early stage in the development process. Pilot users should be given an opportunity to test the new solution, which enables developers to collect relevant data and include this in subsequent development steps. The complete functional scope is typically only available after the interaction with the early adopters of the product, so that the development of an MVP also serves to reduce risk.

Mining is a key task in →cryptocurrency systems that use the →PoW procedure as a →consensus mechanism. In this procedure, the →miners generate the individual blocks that include the transactions of the →blockchain network.

This virtual combination of several →miners intends to conduct successful →mining in →blockchain systems that are based on the →consensus mechanism →PoW and require significant computing power. The remuneration (→block reward) is divided according to the shares brought into the pool (so-called pay-per-share). Among established mining pools are AntPool, Poolin and Slush.

Combination of augmented reality (→AR) and virtual reality (→VR) that allows users to see both real and virtual objects in a display (e.g., a head-up display). The concept originated from the field of computer games and has found use cases in service industries. In the financial sector, users may, for example, see their (physical) credit card together with the (virtual) transfers made with it.

Refers to service providers who exchange →coins of →cryptocurrencies (in particular →Bitcoins) and thereby change the allocation of the →coins and prevent traceability. On the one hand this increases privacy, while it may contribute to money laundering on the other.

Describes the financial activities that are carried out via mobile devices such as smartphones, tablets or →wearables using an →app. Logging into →online banking via a browser on the mobile device is not considered as mobile banking.

Securities trading via mobile devices allows investors to access trading platforms and actively manage portfolios via an →app or a mobile website. Besides traditional banks, →fintech companies such as Acorns, Robinhood or Stash offer mobile brokerage solutions.

Describes solutions in the insurance sector that support customers in claims processing via mobile devices. The functionalities include the recording, documentation and calculation of claims, thus enabling a more efficient claims processing. In the future, claims can be reported not only via smartphones or tablets, but also directly via intelligent objects (e.g., vehicles, houses) and →M2M communications. Several →insurtech companies (e.g., Lemonade, MotionsCloud) already offer solutions for mobile claims handling and often combine these with an overview of insurance policies, etc.

This form of →electronic payments comprises the recording and processing of payments via mobile devices such as smartphones, tablets or →wearables. Well-known providers are →Alipay, Apple Pay, Google Pay, PayPal, Paydirekt or →WeChat. They complement the →four-corner model by supporting payments at the point-of-interaction (→PoI) via host card emulation (→HCE), thus providing an alternative to payment cards at the →point of sale. A distinction is made between forms with or without reference to card-based procedures (→EMV). While →peer-to-peer payments or →cryptocurrencies often have no reference to card-based →payment systems, this is not the case with many existing mobile payment methods (e.g., Apple Pay, Google Pay). While customers have the impression to use mobile →payment services, established payment processors known from the four-corner model or technical solutions such as →ACH or →EMV continue to operate in the “background” (see Fig. 9). However, as the example of PayPal with its own payment network illustrates, alternatives to the →four-corner model with →three-corner models as well as fully decentralized (two-corner) models with distributed ledger technologies (→DLT).

Fig. 9
Mobile payment as a connection to digital payments

This →wallet is an →application on mobile devices such as smartphones or tablets for making cashless payments.

Although mobility services have been established with public transportation as well as private transportation companies (e.g., railways, airlines) for long, →digitalization has given rise to digital mobility services that feature stronger →personalization and are based on the principles of the →sharing economy. Examples are ride hailing services such as Uber and Lyft, car sharing services such as Teilauto, e-scooter services such as Bird, Lime, Tier or Voi and carpooling services such as BlablaCar. A key aspect of these services is the integration of several digital services (→smart service), including navigation and payment functions.

In the sense of a demonstrator or a demonstration model, a mock-up is an early, not necessarily functional prototype of a product or service. For →startup companies, mock-ups are important because they concretize the idea of the future solution for potential customers and investors. Mock-ups can therefore be found as a component of many innovation methods, e.g., →design thinking. Typically, mock-ups precede the development of minimum viable solutions (→MVP).

Initiated in the early 1990s, Mondex offered the first stored cash card and was purchased by Mastercard in 2001. It allowed decentralized payments without central authorities long before →Bitcoin and other →crytocurrencies emerged.

→Cryptocurrency, which aims at achieving high degrees of confidentiality. The transactions stored in the →blockchain (e.g., payments, account balances) cannot be viewed transparently, which is why Monero is a popular medium for payments in the →darknet.

→Digital platform that connects people without bank accounts to the global economy and provides access to the full range of financial services.

This financing option for →fintech businesses is similar to the purchase of tangible assets such as real estate, which are partly financed by the company itself and partly by external financing. Debt financing is usually provided with a mortgage. The creditor of the mortgage (usually a credit institution or a building society) provides the →fintech company with the necessary debt capital and receives a lien on licenses, patents, etc. in return. In the event of the →fintech company’s insolvency, the creditor can realize the licenses in his own interest.

Based on the observation that customers maintain several bank accounts instead of a single account with a main bank →application systems that aimed achieving an overall consolidated view and functionality on these individual accounts were already developed in the 1990s. They enable customers to manage several bilateral bank relationships via a uniform user interface that allows consolidated views on accounts and assets (sometimes even banking and insurance services) and a centralized initialization of transactions. The introduction of standardized bank-customer interfaces since the mid-1990s (→HBCI, →FinTS) formed the basis for these multi-bank solutions, whereby customers can access the other systems via a bank’s →online banking or a separate →PFM system (dashed lines in Fig. 10). The multi-bank capability is considered an important element of the →customer experience and, in particular with the regulatory basis being created by →PSD2 (→access-to-account), has been subject of →business models of numerous →fintech companies (e.g., N26, Neon, Revolut, Robinhood or Yapeal). As shown in Fig. 10, in the multi-bank scenario only the consolidating actor has direct customer contact (bank 1 or PFM system provider), while banks 2 to 4 loose this contact.

Fig. 10
Bilateral vs. multi-bank relationships

Term for →blockchain or →DLT frameworks that focus on the →interoperability of different →cryptocurrencies. On the one hand, →coins of one →cryptocurrency (e.g., →USD Coin) can also be used in other →cryptocurrencies and, on the other hand, →cryptocurrencies can build intermediary →data structures (e.g., →Polkadot) that sustain cross-ledger integration (→CLI).

This concept refers to the interaction of a company with its customers via at least two different channels (e.g., online, e-mail, app, in-car) in order to support customer-facing processes (i.e., marketing, sales, service). Multi-channel approaches shall support a consistent →customer experience across all channels, which is regarded as a →critical success factor especially in service industries. The similar concept of →omni-channel management goes beyond offering various channels (as so-called silos) and foresees the possibility of seamlessly switching between the different channels.

With the transition from physical floor trading to virtual electronic trading on →OTC markets at the beginning of the 1990s, intermediaries emerged to allow their clients to trade across multiple banks and platforms (e.g., →ATP, →electronic exchange, →MTF). The dominant providers are Refinitiv, Bloomberg, State Street, CME or Deutsche Börse.

Indicates a situation in a market or industry where customers and/or suppliers can choose between several offers without monopolies being present. In the financial sector, the term is commonly used to denote the choice between different forms of payment. In addition to cash payments, there are numerous forms of →electronic payments.

This form of an →electronic market assumes that more than one player is present on both sides of the market. While single-sided platforms are based on the principle of the supermarket and include products from different suppliers→, multi-sided platforms act as →brokers and make their platform available with the corresponding functionalities (e.g., product/service catalogue, shopping basket/contracting functions, billing/payment functions). One example is Amazon, which has developed from a single-sided to a multi-sided platform with the Amazon Marketplace. As a result, suppliers competing with Amazon (e.g., book suppliers) may also offer their products via the Amazon platform. While they benefit from the reach and functionality of this →platform, Amazon in its role as platform provider receives fees for each of these transactions and obtains access to the corresponding data for usage statistics. In the financial sector, the MSP logic is reflected in →platform banking strategies and also in various forms of →peer-to-peer platforms (→crowddonating, →crowdfunding, →crowdlending, →crowdsourcing).

Multi-signature or multisig is a technology used in →cryptocurrency transactions to provide additional security. Multi-signature addresses require at least one other user to confirm or sign a transaction before the final entry in the →distributed ledger is made. The required number of signatures may vary and may be defined by the users upon setup of the solution.

Multi-version Concurrency Control (MVCC) is a method for controlling the consistency of data accessed by multiple users simultaneously. This database technology procedure is designed to execute concurrent accesses to one or more (distributed) databases as efficiently as possible without blocking the system or jeopardizing the consistency of the database. Each transaction receives a consistent image (“snapshot”) of the data at startup and when a transaction updates an entry, the system checks that no other transaction is updating the entry at the same time. Only then it will create a new version of the entry. The new version is not visible to other transactions until it has been successfully completed. At the time of the update, the entry is blocked and signals an error, known as an update conflict.

In addition to the bilateral interchange fee (→BIF), which is charged between the →issuer and the →acquirer for card payments, MIFs represent the interchange fee (→IF) that credit card companies such as Visa and MasterCard may charge as a margin on card transactions between the →issuer and the →acquirer. Currently, the MIF is 0.2% for debit cards and 0.3% for charge and credit cards.

Multilateral trading systems are (mostly electronic) market →platforms that allow securities to be traded as an alternative to existing financial exchanges (→electronic exchange). Examples are Aquis, Bats Chi-X, Cboe, Tradegate and Turquoise.

A term used synonymously with distributed ledger technology (→DLT) that emphasizes mutual validation of transactions, but has not been widely used, at least so far.

System of the Reserve Bank of India that processes payments as an automated clearing house (→ACH).

Denotes country-specific identification standards to characterize securities. NSINs consist of nine alphanumeric digits and include national standards such as the →CUSIP in the US, the →SEDOL in the UK, the →WKN in Germany and the security number (“Valorennummer”) in Switzerland. The respective →NSINs, in turn, are part of the international securities number →ISIN. Figure 1 shows the structure of the NSIN using the Deutsche Bank share as an example.

Fig. 1
Structure of NSIN using WKN as an example

Method within the field of artificial intelligence (→AI) for human speech (text or audio) by computers based on rules and →algorithms. The goal of NLP is a direct communication between humans and computer systems based on natural (written or spoken) language. NLP is used in the financial sector, for example, for →sentiment analysis or in the context of →chatbots or →virtual assistants.

A technology of wireless data transmission based on induction, similar to →RFID technology. NFC devices must be located in immediate vicinity (<10 cm) of each other, since the short distance is intended to make it more difficult for third parties to intercept the transmitted data. NFC chips are already widespread for processing of low-value payments at the →point of sale. For example, the provision of NFC chips in credit cards and mobile devices such as smartphones has led to a significant growth of cashless and contactless →electronic payment methods.

→Cryptocurrency introduced in 2015 and named after the New Economic Movement. Nem is based on →blockchain technology and uses the →proof-of-importance procedure as →consensus mechanism.

→Blockchain-based →cryptocurrency using the →proof-of-stake →consensus mechanism and →smart contracts (→Blockchain x.0). It is targeted for use in internet of things environments (→IoT) and is designed for high transaction rates (e.g., up to 10,000 →TPS versus 5–7 transactions in the →Bitcoin system).

Refers to →fintech businesses that entered the banking sector with innovative →digital solutions and challenge →incumbents. Therefore, the notion of →challenger banks has also emerged. Examples of such →startup banks are Monzo, N26, Neon, Revolut or Starling. In contrast to the →direct banks that have existed already before, they pursue a →digital-only strategy without physical branches and rely on a comprehensive →digitalization of their products and processes. They also emphasize a focused and rather standardized product scope that they offer via the mobile channel. Since many functionalities are based on →apps, neo bank have also been called →smartphone banks. The high →degree of digitalization allows neo banks to offer competitive conditions and to target the young generations (→digital natives).

Denotes →fintech businesses in the insurance industry and is similar to the concept of →neo banks in the banking sector. Due to their high →degree of digitalization, they are also referred to as pure digital insurers (→PDI).

The net present value of an investment is calculated by discounting the returns determined for a given period to the present (see Fig. 2). According to this, Investments (e.g., in a →startup) make economic sense, if the returns exceed the investment costs, i.e., the NPV is positive.

Fig. 2
Calculation of the net present value

The concept of network externalities is present in so-called infrastructure goods, such as telephone or communication networks. It characterizes the positive or negative relationship between usage and benefit. Positive network effects occur when many users of a target group use the infrastructure, since this generates high benefits for the users (e.g., regarding mutual accessibility). In the case of negative network effects, the users assume a low acceptance of the infrastructure and therefore see little incentive to participate. Whether positive or negative network effects occur often determines whether a →critical mass of participants and transactions will be attained or not. Network effects are characteristic for the →business model of →digital platforms and →ecosystems. They also show the importance of direct and indirect network effects: while direct effects are based on the direct use of a →platform (e.g., the →app store), indirect network effects also consider the use of complementary offers on that platform (e.g., widely accepted payment and logistics services).

In the card-based payment business, a NSP acts both as a technical and banking service provider at the point of sale (→POS) and enables the merchant to accept card payments. On the basis of cooperation agreements with the →schemes (e.g., Girocard, →EMV), the NSP ensures the acceptance and processing of transactions on behalf of the merchant with the merchant or the →acquirer forwarding economic and technical data to the participating banks or financial institutions as well as the →scheme. Therefore, NSPs are involved in all card-related transactions of the →scheme, for which they are responsible and provide the merchant with the necessary hardware and software at the →POS.

These →application systems are often hosted by service providers (→cloud computing) and allow adaptions or customizations by different users with the modification of just a few settings. This is done by configuration without requiring programming skills. An example are →fintech solutions on the Hydrogen platform. Closely related to no-code approaches are →low-code approaches, which denote solutions where limited programming knowledge is required.

Network nodes are active or passive connection points in social, organizational or technological networks. In computer networks the nodes refer to routers, switches, bridges and →gateways as well as the database nodes in →distributed ledgers. In general, a node has the ability to recognize, process, and forward data for other network nodes. A node has at least two, but usually more, connections to other network elements. Depending on the →consensus mechanism, nodes with a special role exist in the →cryptocurrencies, for example, the →miners in proof-of-work (→PoW) system, the →validators in →proof-of-stake systems or the →master nodes in other →DLT systems.

With the →digital transformation of the financial industry, many actors from outside this industry have embarked on offering financial services. This follows the strategy of automotive companies that have established their own financial service units since decades to provide customers car loans and to increase →customer experience (e.g., by offering competitive interest rates and by not having to involve other actors, e.g., banks). With the rise of →fintech, many →big tech companies as well as →startup businesses have entered the financial domain. Although their roots are in other industries (e.g., IT, retailing, automotive), some have acquired →banking licenses (e.g., like many →big tech companies). With the embedded finance concept (→EFI), collaborative arrangements (→collaboration) between non-banks and financial service providers are expected to increase.

Compared to typical →utility tokens, NFTs are highly specific and less transferable or fungible →tokens. Examples are collectibles with high unique value like digital collectibles and art objects (crypto collectibles), but also digital avatars or characters (cryptopunks) such as user-created objects in computer games (e.g., →CryptoKitties). →Cryptocurrencies like →Eos, →Ethereum, →Neo or →Tron have created their own →token standards for NFT, e.g., the extension ERC-721 (Ethereum Request for Comments, →EEA) within the →Ethereum →framework. These →tokens represent the identity of the respective objects, thereby enabling electronic transferability and tradability (e.g., via NFT marketplaces such as opensea.io or superrare.com). When an artist sells an NFT, it is considered a →drop. In addition to individual collectors and investors, initial steps may be observed when professional investors identify NFT as a new asset class (e.g., the purchase of a cryptopunk from Visa for USD 150,000 in August 2021).

In computer science, a number generated for a specific use and stands for “number used once” or “number once”. Typically, a nonce is a value that varies with time. Used as a timestamp, a session authenticator, a web page visit counter, or a special marker, nonces can restrict or prevent unauthorized reproduction or playback of a file. In the →cryptocurrency environment, nonces denote a uniquely used random number that is a component in the calculation of →hash values and →merkle trees.

Refers to the population born between 1985 and 2000. Attributed to this group is the preference to consume experiences instead of material goods and to share these impressions with friends in social networks. The individual benefit results from the community’s approval or the experience associated with the publication. In addition, the assumption is that members of the Now generation prefer immediate over delayed rewards.

This methodology for employee leadership and management originates from the →IT sector (Intel, Google) and is frequently used in →startup companies. It emphasizes the orientation towards measurable end results. Ideally, this is done in the form of percentage degrees of fulfilment (0–100%) and by using established measurement parameters (e.g., Euros, quantities, time).

Pair of terms referring to the storage of data within or outside of →DLT or →blockchain systems. On-chain describes the classical form as used in →Bitcoin transactions where transactions are contained in the distributed database after completion of the consensus procedure (→consensus mechanism). In the case of off-chain transactions, the consensus procedure (e.g., for reasons of speed and confidentiality) takes place outside the →blockchain, e.g., through a third party acting as a trustee (→TTP), which may be a →crypto exchange. An example is the →Lightning Network in the →Bitcoin blockchain. Likewise, data storage may be off-chain and connected via SQL interfaces as with →Corda. Combinations of off- and on-chain are considered hybrid transactions.

In the field of payment transactions these transactions describe the relationship between the financial service provider that processes the transaction (→acquirer) and the card-issuing financial service provider (→issuer). In contrast to →on-us transactions, the →acquirer and →issuer are different companies, so that the use of a →middleware is required for processing without →media breaks.

→Wallets are an important component in the field of →cryptocurrencies and are present in various forms. Offline →wallets, also known as →cold storage, are used for the storing or safekeeping of digital →coins and →tokens as well as the processing of transactions. They may be stored as data on a computer or a mobile device, or even on a piece of paper (e.g., printed →private keys). Although they are considered secure due to their offline nature, there is a risk of theft or loss.

→Cryptocurrency of the →crypto exchange OKEx based on the →ERC-20 token, which is traded on numerous →crypto exchanges and has →fiat gateways to numerous →fiat currencies.

This enhancement of the →multi-channel concept to include not only multiple, but all (customer) interaction channels, as well as the coordination between these individual channels. Omni-channel management is based on the idea of the customer journey (→CJ), which often takes course across several channels (e.g., a customer configures an investment portfolio at home and then discusses it with the advisor in the branch office or with other customers via social networks). Coordination between the channels ensures that different media may accompany (or control) the customer throughout the buying phases. For example, the customer could receive contextual information about contact points (so-called customer touchpoints in the →customer journey).

Describes a usage and licensing model for →application systems that companies operate in their own hardware/server environment. It is the counterpart to →cloud computing and application service provisioning (ASP) where the operation of hard- and software resources is outsourced (→outsourcing) to third party providers (→TPP). Financial service providers in particular often rely on on-premise operation due to the (control, security, confidentiality) risks associated with →outsourcing when processing personal and financial data.

This term from the field of payment transactions describes the relationship between the financial service provider that processes the transaction (→acquirer) and the card-issuing financial service provider (→issuer). In contrast to →off-us transactions, on-us transactions assume both roles in the responsibility of the same company, or the transaction being processed within one banking group (e.g., a savings bank association).

Refers to the process from signing a contract to establishing an operational business relationship with employees, business partners or customers. The term originates from the human resources domain and refers to hiring and, in a further interpretation, recruiting future employees. After the contract is signed, the focus is on the introduction or integration of new employees or partners into the organization in order to familiarize them with the necessary information, goals and resources, as well as with the company culture and internal working practices. The onboarding of companies as cooperation partners of financial service providers has gained in importance, especially with recent organizational concepts in the financial industry (e.g., →ecosystem, →open banking, →sourcing) that are designed for networking. Onboarding also comprises the registration of new customers with the activities of →authorization, →authentication and →legitimation, which, as a result of →digitalization, are becoming virtualized (e.g., via →video ID procedures) and no longer require physical branch visits. As →while label offering (→banking-as-a-service) such services are increasingly integrated in the offerings of →non-banks (→embedded finance).

Describes the reuse of data in public administrations. The aim of the once-only principle as formulated in the →GDPR, is to enable citizens and companies to more easily handle the personal data they provide to public authorities by reusing existing data. Depending on the EU member states, the principle is designed differently and may either comprise a centralized data storage at a public authority or decentralized storage at the user’s premises (→SSI).

Instant purchase or 1-click, one-click or one-click buying refers to simplified purchasing processes in →e-commerce based on existing data records. This allows the process from the selection of goods to the confirmation of payment (purchase-to-pay) to be approved by the customer with only one confirmation. Instead of manually entering billing, shipping and payment data to complete a transaction, a user may release the transaction with a single click and, for example, use a predefined address and credit card number to purchase one or more items.

A method used in the →authentication process that provides dynamic one-time passwords generated by code generators that cannot be used for a second logon. Such →tokens are used for two-factor authentication (→2FA) in →online banking, but also in the corporate context.

Denotes the interaction channels that buyers and sellers are using during the phases of a transaction (see Fig. 2 in chapter E–H). Electronic or online channels include the electronic forms of e-mail, call center, →e-commerce, →mobile banking, →online banking or →social banking. Offline or brick-and-mortar channels comprise primarily include stationary formats such as the traditional bank branch, but also points of sale (→PoS) with cash registers in retail stores. O2O refers to concepts that aim at linking online and offline channels, such as online purchasing (→e-commerce) and offline collection and payment in a branch (so-called purchase online, pay offline). An example in Germany is the →service of Barzahlen.de.

Online banking, along with other forms such as →mobile banking, is part of →digital banking and an interaction channel in overarching concepts such as →multi-channel or →omni-channel management. It refers to banking →services that customers use via the internet. They either supplement existing customer contact channels of financial service providers as a cost-effective variant or, as with →direct banks or →smartphone banks, even replace them. The usual functionalities of online banking solutions or →apps include account and card management, the execution of transactions and payments as well as overviews on →liquidity, investment information or spending patterns. Similar to →e-commerce, major benefits vis à vis offline channels (offline banking) are the time savings and constant availability (i.e., 24 × 7 × 365). Online banking services, which have been in existence since the 1980s, are now considered to be among the mandatory services of a bank and have expanded considerably, especially in the direction of →PFM with functionalities in the areas of →multi-bank capability and the integration of complementary services, such as financing, investment and insurance services (e.g., mortgage comparisons, securities trading, pension services, purchase of event tickets). In addition to online banking services offered by traditional banks (→incumbent) and insurance companies (→bancassurance), there are also →services offered by specialized →PFM providers such as Mint and electronic payment providers (→electronic payment systems) such as →Alipay or →WeChat Pay.

An electronic credit application is a document or web form completed by a customer (person or company) to apply for a credit at a credit institution, which the institution processes (either directly digitally or by OCR scan) to conduct credit checks. For this purpose, it uses an →algorithm that assesses the customer’s historical, demographic and geographical data. The goal is to grant credit in real-time (→real-time processing), whereby the use of →video ID procedures for→ authentication should avoid →media breaks.

Term for →application systems that focus on transaction processing. The →real-time processing of data provides users with current data, which, in contrast to →batch processing, is also processed immediately (i.e., in real-time without intermediate storage and within defined time intervals). OLTP is based on the operational functionalities of →ERP and →core banking systems where it is also known as booking engine. On a tactical-strategic level, OLTP is often linked to online analytical processing (OLAP) →applications, which refer to supporting an analysis of aggregated data for decision-making purposes (→business analytics).

An open programming interface is an application programming interface (→API) whose syntax and semantics are publicly available to allow the use of electronic →services at low →transaction costs. Numerous Open APIs follow the architectural model of representational state transfer (→REST) and are accessible to encourage third parties to find innovative ways to use a manufacturer’s software product, thus creating win-win situations and, ideally, →network externalities (see Fig. 3).

Fig. 3
Example of an open API banking architecture

This strategy recognizes the move of traditional banking organizations towards more open →business networks based on the integration of →services (→sourcing) from external partners or third-party providers (→TPP). The terms →API banking and →platform banking are closely related and often used synonymously, as the integration of →services takes place via electronic interfaces (→API) and electronic →platforms. Open banking has three features: (1) The use of →open APIs by third-party providers (→TPP) to create →applications and →services related to the financial institution, e.g., universal access to bank accounts for reading balances and transaction volumes (see Fig. 3). (2) Increased financial transparency for account holders, by combining freely accessible and private data. (3) The possibility of using open access concepts to enable third parties to access to customer and transaction data. Due to the large amount of generated data along (digital) customer journeys (→CJ) new potentials for improving →customer experience possible. Open banking concepts refer to both banks and →fintech companies, whereby two basic characteristics are present: (1) In the →front-end customers receive a single →platform, through which they may conduct all banking transactions together with additional →services. (2) In the →back-end, financial service providers make their →online banking data available via →APIs for selected external services on the →platforms of →fintech companies or third-party providers (→TPP). This requires the consent of the customer (→opt-in) regarding the use of personal data according to data protection regulations (→GDPR).

Based on the philosophy of →open source, this data is available to be freely accessed, processed and used. Numerous open data sources have emerged, for example, in the environmental (e.g., geo and mobility data) or media (e.g., open access journals) and statistical data (e.g., demographic data) sectors. They may be used via interfaces (→API) and linked by means of semantic technologies (so-called open linked data). A broader view differs from the pure open data criteria and describe the possibility that data is available and may be reused under certain conditions. For example, institutional requirements (e.g., account data according to →PSD2 is only accessible to financial service providers, →TPPSP) must be fulfilled, a contractual relationship must exist (e.g., service provider contract in →open banking) or a certain price needs to be paid.

Concept that provides for open instead of closed →innovation processes where companies involve external partners (e.g., customers and suppliers) when developing new processes, products or →business models at various points within the innovation process (e.g., idea generation, selection, market test). The aim is to improve internal innovative skills by linking external resources from the →ecosystem more closely to the company.

Refers to the free availability of products or →services and is found in particular in the software and services sector. In a narrow sense, software products are considered open source if their source code is freely available, usable and modifiable. Numerous →application systems in the area of operating and database systems as well as development tools, office solutions, →cryptocurrencies and →business analytics →applications are freely available today, whereby the industry-specific →applications (e.g., →core banking system) are usually commercial software products (so-called commercial-off-the-shelf, COTS). In a broader sense, the open source model can may also be found in the provision of information in →community banking or in the opening of innovation processes in the context of →open innovation.

An operating system is the interface between a user or application software (→application system) on the one hand and the hardware (e.g., desktop, smartphone, →wearable) on the other hand. It comprises all programs of a computer system that manage the operation of the system and usually consists of a kernel, which administrates the computer’s hardware, and basic system programs, which are used to start and configure the OS. Operating systems such as Linux, MacOS or Windows, on personal computers, are also suitable to run →blockchain frameworks, as are sometimes the OS for mobile devices such as Android and IOS. Recently, specific →blockchain operating systems such as Consensys Codefi, →Eos or →Libertyos have emerged, which are called decentralized OS and already provide functions such as support for →tokens (e.g., the Liberty Token) or →cryptocurrencies and numerous →wallets.

Registration procedure in online marketing, where online users must actively agree to a choice. Opt-in procedures are often used in e-mail marketing when users need to provide their consent to receive e-mails. It is also possible to agree at the time of contract conclusion or customer contact, e.g., like confirmations in a check box. This procedure is more in line with the requirements of the →GDPR, especially with regard to the →opt-out model.

Compared to →opt-in, this consent procedure requires online users to actively object to the measures taken by a company (e.g., sending advertising mailings, processing user data). As long as the user refrains from doing so, the company’s measures will continue.

Despite this term resembles the name of the global software provider Oracle, an oracle denotes a software component that supports the data flow between the →blockchain and an →application system outside the →blockchain (→off/on chain). This allows components from outside the →blockchain (e.g., a sensor) may be accessed via an interface (→API) by the →smart contract of the →blockchain system. As shown in Fig. 4, four basic variants of oracles may be distinguished.

Fig. 4
Types of oracles (see Mühlberger et al., 2020, p. 2)

The order book of a stock exchange brings together buy and sell bids in tabular form and is a key element of →electronic exchanges. It shows the number of (buy and sell) bids for a financial instrument (e.g., shares, derivatives, →cryptocurrency) for certain prices. Figure 5 shows this using the example of the order book of the →crypto exchange Bitfinex, where the three left columns reflect the buyer side and the three right columns the seller side. If the orders are not part of a →dark pool, the sellers or buyers are also shown in the order book. On →electronic exchanges, the order book is continuously updated in real-time (→real-time processing), so that the market price is constantly calculated. An alternative to centralized order books is the decentralized concept of →liquidity pools.

Fig. 5
Example of the Bitfinex order book (Medalie 2019)

Orphan blocks are valid blocks in a →blockchain that are not part of the →main chain. They can occur naturally if, for example, two →miners produce blocks at similar times or if an attacker (e.g., with sufficient →mining resources) attempts to reverse transactions.

→Sourcing strategy that shifts responsibility for resources (e.g., hardware, software, buildings, workers), their operation and/or the execution of processes (→BPO) to a third-party service provider. It may be found in bilateral cooperation with a service provider as well as in the cooperation of several complementary service providers in an →ecosystem. Although outsourcing measures leverage external resources and the service providers’ skills and scale, outsourcing involves →transaction costs and risks. If technologies such as →blockchain contribute to the reduction of →transaction costs, an increase in outsourcing may be assumed. With the availability of standard services (→API banking), an evolution of →ecosystems and short-term outsourcing solutions based on the pay-as-you-use model (→PAYU) may be expected.

Form of trading securities as well as derivatives outside the official stock exchange via telephone or corresponding platforms (e.g., dealer systems, →ATP, →dark pools, →MTF). The offerings in OTC trading are typically broader, as they also include securities not listed on official stock exchanges. In addition, as a result of →digitalization, corporate and retail investors may increasingly participate in OTC trading, which explains why the concept has also spread to other sectors, such as energy trading.

In the field of →cryptocurrencies, the term has primarily been used for enhancements of the →Bitcoin system to enhance privacy and anonymity. Overlays serve similar purposes like alternative →cryptocurrencies, such as Darkcoin or Zerocash. Among the examples are Pinocchio Coin based on →Zerocoin or Coinshuffle.

The abbreviation for parallelized chain refers to →data structures that usually follow the →blockchain model and aim to improve →scalability by parallelizing an “underlying” →relay chain. Para-chains thus follow the concept of →sharding and are present in the →cryptocurrency →Polkadot.

→Cryptocurrency, which is a →stable coin with a 1:1 ratio to the US dollar. Each →token is deposited with a real currency unit at the issuing (→issuer) Paxos Trust Company. The →open source →blockchain system is based on the →ERC-20 token and includes the →smart contract functionality of →Ethereum.

Term from the automotive and insurance industries, which follows the pay-as-you-use (→PAYU) principle. Following this model, the premiums are calculated according to actual use, for example, the number of kilometers driven compared to pre-agreed premiums (e.g., a flat rate). The processing of PAYD requires movement or usage data (e.g., the customer’s driving style, the geographical location) and thus the connection with additional systems (e.g., in the vehicle). This data may also form the basis of a risk analysis in order to structure future policies not only according to usage data, such as kilometers driven, but also with regard to risk classification (e.g., premium for low-risk and defensive driving).

Also called “pay-as-you-go”or “on demand” or “pay per use”, it refers to a (rental) system in which users pay only for the periods during which they use a specific item. Such usage-based models are found, for example, in →cloud computing that provides customers with computing resources or →application systems on demand. One advantage of PAYU is that fixed costs become variable and customers contribute to a sustainable use of resources by only using the services, which they actually need (→sharing economy).

Refers to the sector of →payment service providers in the payment card industry. These actors include the classic providers of payment cards (e.g., debit, credit, customer and prepaid cards), but also providers of →e-wallets. Some of the PCI companies are organized in the PCI Security Standards Council (PCI SSE) and participate in the development of the PCI Data Security Standard (PCI DSS). The latter is known as the PCI standard and defines the security mechanisms for most card companies (e.g., →PIN on Glass).

In the context of →ISO 20022, PAIN comprises a set of messages for payment initiation (e.g., credit transfers, direct debits) and various forms of payment →authorizations. They enable the seamless processing of payment messages (i.e., without →media breaks) and represent an important prerequisite for →real-time processing (→EDI, →RTP, →STP).

→Service defined in the →PSD2 regulation that accesses payment accounts in order to initiate a transfer in the user’s name with the user’s consent and →authentication. PIS offers an alternative to online payments by credit card (→electronic payments).

Third-party providers (→TPP) that offer financial services following the European →PSD2 legislation.

According to the payment services supervision act (→ZAG), payment services include (1) the deposit or withdrawal business, (2) the payment business in the form of the direct debit business, the credit transfer business and the payment card business without the granting of credits, (3) the payment business with granting credits, (4) the payment →authentication business, (5) the →electronic payment business and (6) the money remittance business. Payment service providers (→PSP) may be found in the areas of →electronic payments and the bundling of several payment procedures by →integrators such as →acquirers. An overview of payment service providers such as →acquirer, →issuer and →scheme in the card payment value chain (shaded in gray) is shown in Fig. 6.

Fig. 6
Payment services in the value chain (see Huch, 2013, p. 83)

These service providers assist →e-commerce merchants in accepting payments by providing them a bundle of →electronic payment methods (e.g., credit transfer, credit card, direct debit) from different providers. A PSP regularly connects to several acquiring banks (→acquirers) as well as payment and card networks, e.g., via →API, to process the various →payment services. For merchants, there are several advantages to using a PSP, such as reduced dependency on financial institutions, reduced administration and control efforts, and the ability to use regional and global PSP relationships with payment and card networks.

The second payment services directive of the European Union updates and enhances the EU rules put in place by the initial PSD from 2007. The PSD2 was enacted on 12 January 2016 and EU Member States were given until 13 January 2018 to transpose it into national law. The main objectives are (1) to contribute to a more integrated and efficient European payments market, (2) to further level the playing field for →payment service providers by including new players, (3) to render payments safer and more secure, and (4) to enhance protection for European consumers and businesses. On the one hand, PSD2 aims to foster →innovation as well as competition in retail payments and to enhance the security of payment transactions and the protection of consumer data on the other. PSD2 is supplemented by regulatory technical standards regarding strong customer →authentication and secure open standards of communication as well as guidelines on incident reporting and guidelines on security measures for operational and security risks. In particular, PSD2 focuses on two-factor authentication (→2FA) for online payments, open access to account data at financial service providers (e.g., via →API) and the elimination of fees for online credit card payments.

In order to standardize →payment services in the European single market, the first payment services supervision act (ZAG is German for Zahlungsdiensteaufsichtsgesetz) was enacted in Germany in 2009 on the basis of the 2007 EU directive on →payment services in the single market. It was updated in 2018 based on the second payment services directive (→PSD2) and defines who is considered a payment service provider (→PSP) and what tasks are included in →payment services. It also implies that banks need to make account data available to their competitors, which enables →multi-bank approaches and associated →business models (e.g., →PFM).

The generic term has two main interpretations. (1) In some cases, it refers to the set of instruments, banking procedures and interbank funds transfer systems which facilitate the circulation of money in a country or currency area. (2) Mostly, however, it is used as a synonym for a funds transfer system. Depending on the type of →electronic payment, different actors are participating in the organization and operation of a payment system with the →four-corner model being the most well-known. In addition to these systems with centralized actors, decentralized models have emerged with the rise of distributed ledger technologies (→DLT) that operate without intermediaries (→intermediation).

A term often used synonymously with →cryptocurrencies to denote →tokens, which primarily work as means of payment in economic transactions. Best known are →Bitcoin and →Ether.

As a subcategory of →fintech, paytech comprises companies and solutions in the field of payment transactions. It includes various forms of →electronic payments and →mobile payment. The paytech sector has seen significant growth in new solutions and providers, especially since the →PSD2 directive allowed →non-banks to act as service providers.

Denotes an organization model that is based on the interaction among equal or equivalent actors in networks. In general, network participants (e.g., computers, participants, groups) have equal rights and may provide each other with functions, →services and data. It is an established principle in the scientific community (e.g., the peer review procedure) where scientific progress is based on the independent review of research findings among colleagues, who ensure that results are only published after having successfully passed a critical review by other domain experts. From a technological point of view, P2P describes distributed networks that due to their decentralized topology are less susceptible to attacks (→cybercrime) or a total failure compared to centralized networks (→client-server). From an application point of view, P2P is suitable for workgroups, where employees access computers in the network and share files and resources. It may be traced back to file sharing networks for pirated music and films, while P2P solutions in the →fintech sector focus on various types of →digital platforms (e.g., →peer-to-peer insurance, →peer-to-peer lending, →peer-to-peer payments) and applications of decentralized finance (→DeFi), →crowdsourcing or the →sharing economy.

→Insurance offerings that follow the →P2P logic are based on a group of individuals that support each other in the event of a claim (e.g., share the excess among themselves). If no damage occurs, the participants receive a reimbursement of a certain part of their insurance fee. An example for a P2P insurance is Friendsurance.

In P2P lending (→crowdlending), natural and legal persons provide capital, which is transferred directly between natural or legal persons. The combinations are typically equal pairs, i.e., natural persons lend to natural persons and legal persons to legal persons. In the P2P lending model, traditional bank loans and intermediaries (e.g., banks) are obsolete (→disintermediation) and the negotiating power of customers is improved, which is likely to benefit them in the event of excessive lending rates or lack of credit approval.

Refers to payments between two equal or equivalent market participants without an intermediary (→intermediation). In payment transactions, P2P payments often comprise micro payments (i.e. payment values below 5 Euro) among peers via electronic systems (e.g., from one →wallet directly to another →wallet). However, not all P2P payment schemes are fully distributed since they may involve →non-banks like PayPal or →big tech businesses (e.g., Apple Pay, Google Pay).

A →node in the distributed ledger system (→DLT) →Iota that persistently stores an entire dataset and relieves other →nodes in the network to hold full database copies. The goal is to limit the size of the distributed datasets (→ledgers) the other →nodes and to ensure that data is available over the long term.

Contrary to →public blockchain systems, only authorized participants may access a permissioned →blockchain. This restricts the possible group of participants and thus allows a higher level of confidentiality for transactions. For example, the participating financial service providers must have agreed to certain rights and obligations before they are allowed to join. This creates trust and thus simplifies the →consensus mechanism since it reduces the Byzantine problem (→Byzantine agreement). Although, outside participants may be granted read-only rights or the →ledger may even be viewed publicly, transaction processing remains restricted to the registered participants. These configuration options make permissioned blockchains particularly suitable for application purposes in the business environment (→enterprise blockchains).

The combination of the concepts of the (virtual) assistant or advisor and →personalization leads to personal assistants who offer comprehensive services, like →family offices in private banks, for their (typically) wealthy clients (→wealthtech). The service portfolio of personal assistants in the financial sector is broad and includes banking-related services (e.g., asset management) as well as numerous additional services (e.g., legal advice, travel planning, succession/heritage arrangements). →Digitalization has not only provided electronic support for these activities, but the personal assistant concept has also found its way into the comprehensive support of users of →application systems and electronic services. Popular personal assistants provide voice interfaces to many services and are offered by most →big tech companies, e.g., Alexa (Amazon), Assistant (Google), Cortana (Microsoft) or Siri (Apple). They comprise →digital platforms that list numerous interaction routines (so-called skills) from various application areas and from various providers, including many routines from financial service providers that use them to access their →services. Some financial service providers have also developed their own personal assistant systems, like the Australian ASB-Bank with its assistant Josie.

→Application systems that focus on the individualized and comprehensive management of financial affairs for individuals as well as for small and medium-sized companies (→SME). They support users in financial planning, management and transaction processes and provide an aggregated view (→data aggregation) of financial data by integrating with systems from multiple vendors. In some cases, the solutions offer →multi-bank integration, as enabled by standardized interfaces (→API) such as those for accounts based on the →PSD2 regulation. While PFM solutions date back to the 1980s where the Quicken software was created, more recent solutions have emerged from →fintech companies (e.g., Emma, Moven, Strands, Yolt) as well as →incumbents (e.g., BNP Paribas, Goldman Sachs). Increasingly, they provide automation functionalities based on artificial intelligence (→AI), for example, to categorize deposits and withdrawals, to initiate investments or to analyze portfolios and to suggest potentials for optimization. For these purposes, PFM solutions may be linked to →robo advisory and for compatibility with the →GDPR, users are typically required to →opt-in.

These cloud-based digital services (→cloud computing) aggregate profile and rating data from multiple services and →digital platforms. Via PIMS such as Deemly or Traity, users may centrally manage ratings and their →authentication data for many systems (→identity management) and support users in managing identification data across many service providers.

The adaptation of resources (e.g., products, services, websites) to user needs is a goal that is often pursued with →digitalization and also →fintech services. Personalization follows the →data-driven approach and tailors the resources based on publicly available data (e.g., location, weather, →operating system) as well as data provided by the user (→opt-in) and data collected by the provider himself (e.g., click behavior, page visits, likes). Although different interpretations of the term exist, personalization is often considered to be synonymous with individualization.

Refers to the broad penetration of business and society with information technologies (→IT). These networked computing devices (→IoT) are present ubiquitously in/on objects as well as animals or humans. They lead to data-based (→data-based approach) scenarios where →personalization and per-per-use-models (→PAYU) are present. For example, smart homes would recognize their inhabitants and adapt to their preferences as would cars for their passengers. Payments for usage-based services could be processed automatically once this permission is granted by the users.

A procedure for entering a personal identification number (PIN) during →authentication, which is not effected on a keyboard (“PIN on keyboard”) but on a touchscreen. An important distinction refers to whether the device is a certified terminal device (→PCI) or a consumer device (“PIN on commercial off-the-shelf devices”). In the latter case, the PIN is entered on a regular terminal device (e.g., a smartphone) that is enhanced with an additional device (e.g., a card reader, a security chip). The term may also be found under the notion “tap to phone”.

The term “pivot” refers to the substantial change of one or multiple elements of a →business model in the →startup phase. An example is the →big tech company Amazon, which started as an online book retailer and has established the Amazon Web Services business segment in addition to its →e-commerce platform, thus developing the →platform‘s services (e.g., server resources, storage space, shopping cart, logistics, payment services) as a separate →business model. Another example of a pivot is the announcement of the →payment service Klarna that plans to develop from a pure →payment service provider towards a shopping platform provider.

The term platform is present in many domains (e.g., construction, politics) and refers to an (often elevated) area that provides the basis for further activities (e.g., viewing, drilling). In the economic context, it refers to a →business model that links several users with different roles (e.g., supplier, customer) and offers services that are associated with the platform (so-called platform services). Platform providers enable platform access and operation (e.g., with subscriber directory, market supervision) and/or support transactions on the platform (e.g., with payment and logistics functionalities). While traditional marketplaces already provide a platform for merchants and customers, the importance of digital platform →business models has increased with →digitalization. Well-known →digital platforms are present in the areas of →e-commerce (e.g., Amazon), →digital marketplaces (e.g., Ebay, →app stores), →e-payment (e.g., PayPal) or →social networks (e.g., Facebook). →Network effects are characteristic of the platform model, in particular for →multi-sided platforms. Terminologically, the platform concept is close to that of the →ecosystem, which emphasizes the interaction of competing and collaborating actors in a network rather than the (typically centralized) digital platform that is often a important element of an →ecosystem (see Fig. 7).

Fig. 7
Platform concept versus ecosystem, electronic market and e-commerce (Alt, 2020a, p. 6)

The persons or departments serve as coordinators or initial points of contact to address requests or complaints or to initiate activities (e.g., orders, returns) in the contact with business partners (e.g., suppliers, customers). For →fintech companies, which often lack physical presences (i.e., branch offices), this may be a customer contact center towards clients and a service center towards service providers. The PoC coordinates the processing of the request and typically creates a service order or ticket to track and document it. To emphasize a central PoC, the term single point of contact (→SPoC) has emerged.

Refers to the place where a message exchange between individuals and/or machines occurs. In cashless →payment systems, the PoI denotes the location where the interaction occurs and may be more specific than the →point of sale. For example, it is the card terminal or the touchless device reader for →mobile payments. Depending on the technology used, this may be a →RFID or →NFC module of a mobile device (e.g., smartphone), which can send and receive data and thus act as a point of interaction PoI.

The location where the purchase takes place may be a building or a shopping center in which a sales outlet is located and the direct customer contact occurs. The focus is on addressing customers as personalized as possible (→personalization) to promote impulse purchases via targeted sales promotion measures. A PoP may differ from the →point of sale since in →omni-channel concepts, the customer journey (→CJ) can allow for in-store advice and subsequent online purchases.

Although the point where goods and services are sold may differ from the point of purchase (→PoP), it is where the contractually binding agreement and payment takes place. In payment transactions, the non-visible and cash payment transactions that a customer makes at the (physical or electronic) cash register systems take place at the PoS.

Indicates the selection of payment methods (e.g., →electronic payments) for the customer at the →point of sale. Irrespective of regulatory requirements, or the so-called →gentleman agreement, customers at the →point of sale should be able to select their preferred payment method, when paying with payment cards and not just be presented with the merchant’s default settings.

→Cryptocurrency that aims at the →interoperability of different →blockchain frameworks and has evolved from a →permissioned blockchain to a →permissionless blockchain. The interconnection and trusted exchange of data and →digital assets from multiple →blockchains (e.g., →Bitcoin, →Ethereum) is accomplished by mapping them as a parallel data chain (→parachain) to a central mediating data structure (→relay chain) and forwarding data from one →parachain to another. For this purpose, the system uses a modified →proof-of-stake (nominated proof-of-stake) →consensus mechanism.

A strategy in the →fintech field that aims to achieve an optimal composition of an asset portfolio (e.g., regarding risk and returns) via the use of semi- or fully automated methods. The starting or target point is not the existence of an optimal portfolio, but rather the intention to cover previously non-existent customer needs. Numerous →fintech initiatives implement artificial intelligence methods (→AI) to address portfolio optimization, e.g., Call Levels, Future Advisors or StockTwits.

→Consensus mechanism in →blockchain systems, which is named after the →Byzantine agreement problem. In analogy to the generals, who are not able to trust each other, the →nodes of a communication network are potentially mistrusting their superiors and negotiate among themselves before accepting a decision. The procedure is used in distributed ledger (→DLT) and →blockchain systems but creates a growing load of communication with a growing number of →nodes. Therefore, it is mainly used in →enterprise or →private blockchains with a limited number of →nodes. PBFT is found in variations in the systems →Hyperledger, →R3, →Ripple and →Stellar.

Prediction markets trade the probability of future events. These events range from elections, weather changes and price fluctuations to the occurrence of natural disasters or the sale or purchase of companies. The value of a bet reflects the probability of a future event occurring. In the environment of →startup companies, they refer to markets that do not yet exist due to innovative products or services that are still being developed.

Refers to the number of a gift card, membership card or payment card. They usually comprise 10–19 digits and contain the →issuer identifier number (IIN) as a key element, which is a six- or eight-digit number used to identify the cardholder. In addition, PANs may include up to twelve further individual identification digits and a check digit.

Privacy coins are crypto →coins that hide the identity of the user. They may be traded identically to other →cryptocurrencies and stored in →wallets. Compared to widespread public →cryptocurrencies such as →Bitcoin, privacy coins strive for a strong anonymization instead of →pseudonymization. Examples include methods such as zero knowledge proofs (→ZKP) and currencies such as →Zcash or →Zerocoin. In many cases, privacy coins also have lower →liquidity due to a lower dissemination and are often associated with money laundering concerns (→AML).

Compared to →public blockchains, the validation and write permissions are centralized in one organization with private blockchains. In general, they are useful when public transparency is not desired. In consequence, possible applications are mainly within companies (e.g., data management, auditing) (→enterprise blockchain). This enables the organization to exert governance and to control the participants in the network and their permissions. For example, read permissions can may be restricted to any extent. To benefit from the advantages of distributed infrastructures such as distributed ledgers (→DLT), potential areas of application require a certain minimum number of participating →nodes or organizational units, which is present in large corporate structures as well as in international settings. Often used synonymously is the term →permissioned blockchain, which denotes a restricted group of participants, but also exists in a decentralized variant as public permissioned blockchain (e.g., at →Corda). A well-known framework for private blockchains is →Hyperledger.

Similar to →P2P lending and →crowdlending, private lending is a loan from a group of non-institutional investors or from single non-institutional investors. For investors, it offers the possibility of achieving a higher return than with other investments. It allows borrowers to obtain capital if they do not qualify for conventional bank loans. Typically, →digital platforms bring lenders and borrowers together and potential borrowers provide information about how much money they need and why they need the money. Investors typically decide independently on whether they invest or not.

The private key or secret key that only the respective user knows. In →cryptography, it is used in →asymmetric encryption procedures to encrypt and decrypt messages. The private key enables users to decrypt data encrypted with the public key, to generate →digital signatures or to authenticate themselves (→authentication, →identity management).

The automation of processes is a major goal of →digitalization efforts in the business environment. It aims at improving process efficiency (in terms of time and cost), process quality (in terms of error rate and →customer experience), resource utilization (in terms of workforce and technology) and →compliance due to the necessary formalization of work processes. Process automation may occur in all areas of financial service providers (for banks see the →bank model for an overview of acitivities in banks) as well as in full and partial automation. Full automation requires a high level of process standardization and is primarily present in repetitive processes (e.g., operations, administration, finance), while partial automation is used for activities with a higher variance and demands on human judgement as within management or value-added processes (e.g., sales, management, marketing). Process automation may be achieved by eliminating →media breaks between →application systems as well as by implementing workflows in the →application systems. In the first case, a software (→robot) assumes the task of transferring data between →application systems (→RPA), while in the second case the process is configured directly in an integrated →application system (e.g., a →core banking system or a workflow management system). Ideally, the processes should be redesigned or restructured prior to automation, however, this is not a mandatory requirement.

Process mining combines the field of process management with the field of →business analytics, in particular, the techniques of data mining. It allows the analysis of (operational) business processes and yields detailed data about how business processes are executed in reality. Very often, the reality diverges from how processes are designed and lead to the presence of multiple process variants. Process mining then yields insights into the number of process variants (process discovery), the process run-through time, the frequency of execution or the personnel employed. For this purpose, process mining →applications access the time and event data (event logs) in →application systems, (e.g., →ERP, →core banking systems). Tools for process mining come from the scientific sector (e.g., ProM, Signavio) and increasingly also from professional providers (e.g., Celonis, ProcessGold).

While from a technical point of view a processor is an instruction set controlled computer chip (e.g., central processing unit, CPU), the term is used in the banking context for a service provider that processes →electronic payment transactions. These processors can may act as service providers for both the →issuer as well as the →acquirer. Other functions offered by the processors in the card business include the control of information exchange and the crediting of payments to the respective clearing accounts.

→Consensus mechanism in →blockchain networks that combines the concepts of →PoW and →proof-of-stake. In this procedure, the →miners first have to create a new block based on the →PoW procedure. However, this block does not contain any transactions, but only the address of the successful →miner. In a second step, a random group of →validators is selected to verify the added transactions. They are rewarded for validating transactions and are more likely to be selected if they posess more →coins (→proof-of-stake).

→Consensus mechanism that requires the prior →authorization of →nodes and is similar to →proof-of-stake. The →algorithm selects a →node between these participants based on its activity and requires less computation power than →proof-of-work mechanisms. It is used in the →cryptocurrency VeChain, where blocks are generated by trusted participants who have to disclose their identity in a →KYC process.

→Consensus mechanism in →blockchain networks, which is based on the capital expended. Similar to →proof-of-stake, PoB is based on the invested stakes, but destroys (“burns”) them afterwards to avoid the →double spending problem and to attain a longer-term commitment to the respective →cryptocurrency. The mechanism has received only little adoption since the elimination of →coins, which have been created in the energy-intensive →PoW process, is regarded as a major downside.

→Consensus mechanism in →blockchain networks that aims to avoid the disadvantages of the →PoW mechanism. Instead of being based on invested computing power, the procedure PoC uses the →nodes’ capacity available for storing possible future →hash values. Similar terms for this mechanism are proof-of-space and proof-of-storage while the latter does not use cloud storage for →hash values.

Essential milestone in development projects, which “proves” the basic feasibility of a solution. It is an important step for →startup companies when approaching the market or investors (→VC) but is also established for the validation of requirements and for the enhancement of a solution. The PoC often involves prototypes as well as pilot partners and customers.

→Consensus mechanism in →blockchain networks, which is present in →permissioned blockchain networks to decide on the →mining rights or the →nodes that add transactions in a network. Since PoET assumes that all →nodes are trustworthy, each participant requires an →authentication before →mining rights are allocated via a lottery mechanism. This way, the procedure reduces resource utilization and energy consumption. PoET is, for example, used in the →Hyperledger system.

→Consensus mechanism in →blockchain networks based on the activity of the →nodes in a →blockchain network. Transaction frequency and transaction volume serve as the basis for measuring the activity. Although PoI avoids the disadvantages of the →PoW mechanism and specifically rewards active users, the procedure has only been limited to a few →cryptocurrencies (e.g., →Nem).

→Consensus mechanism that is similar to the →proof-of-stake procedure but emphasizes the property rights of physical asset as potential stakes.

→Consensus mechanism, which is similar to the →proof-of-stake procedure but uses collateralized →coins or →tokens (e.g., deposited US dollars in the →cryptocurrency →USD Coin) as stake objects. The term has also emerged in the area of decentralized finance (→DeFi), where it requires →crypto exchanges to hold a certain amount of reserve currency to contain the risk of insolvency.

→Consensus mechanism in →blockchain networks, where the participants deposit a stake, which may be an amount of →coins or →tokens (so-called token-stake). The amount correlates with the number of tickets in a lottery where many tickets increase the likelihood of winning. Similar to a lottery these voting rights are included in the allocation as shares (more stakes = more potentially winning tickets) and a random →algorithm subsequently determines the “winner”. The other →nodes then validate the result and reclaim their stake while the successful →node also receives a transaction fee. Instead of competition like in →mining (→PoW), the procedure is based on a random mechanism which has become known as →forging. There are several variations of the PoS mechanism (e.g., →PoA, →PoO, →PoR) with delegated PoS (→DPoS) being the most widespread. Due to the lack of →mining, PoS is considered to be significantly more energy and time efficient. Estimates assume a 99% reduction in energy consumption compared to →PoW, which explains why numerous →cryptocurrencies have adopted the PoS mechanism (e.g. →Cardano, →Polkadot, see appendix) or are switching to it (e.g., →Ethereum with the Eth2.0 extension).

→Consensus mechanism in →blockchain networks, which determines the node that adds blocks based on invested computing power. Network →nodes participate in solving the calculation of a random number (→nonce), which has been added by the system to the →hash value of prior transactions. This cryptographic puzzle needs to be solved within a defined timeframe (e.g., ten minutes in the classical →Bitcoin system) otherwise the system will propose a new value. In principle, any network participant that makes its computing power available to the network can participate in →mining, however, the calculation task (i.e., →mining) requires highly performant infrastructure. In practice only large server farms or pools of several servers (→mining pool) will be successful in this endeavor. As soon as at least 51% of the participating →nodes have confirmed the correctness of the calculation, a transaction is considered validated. The successful →miner adds the new blocks to the chain and receives remuneration in the form of →block rewards. Although the PoW mechanism solves the trust problem in distributed networks without a trusted third party (→TTP) being involved, the time and energy required for the process are considered to be major drawbacks. The most important alternative to PoW is the →proof-of-stake mechanism, which is likely to replace the currently widespread PoW mechanism (used in approximately 70% of all →cryptocurrencies) in the long term.

Similar to the →fintech notion, proptech combines the initial syllables of “property” and “technology” to denote digital →innovations in the real estate sector. It is closely related to →contech and provides a link to →fintech, as numerous solutions for financing real estate, investing in real estate assets or for the →sharing economy, are relevant in this domain.

In social life, a protocol defines the schedule of events (e.g., receptions, press conferences). In computer science it describes agreements for data transmissions, in particular regarding data formats and functions used. For example, the e-mail protocol (simple mail transfer protocol, SMTP) outlines the data format consisting of a header (contains recipient, sender, copy recipient etc.) and a body (contains free text in ASCII character set) and the computer ports used, codes for the status of the message transfer and possible encryption procedures. Other protocols for message transmission are the ISO/OSI and the internet protocol TCP/IP (contains HTTPS, FTP). →Blockchain protocols specify, for example, the structure and flow of transactions (→Bitcoin transaction), the →consensus mechanism, and the use of →DApps or →smart contracts.

While anonymization aims at making linkages between data and a specific person impossible, pseudonymization uses an →algorithm to modify the data in the sense of the →GDPR. It differs from anonymization since a reference between the data and a specific person is possible by using additional data or by applying the →algorithm.

In this type of →blockchain system, all users may actively participate in public blockchain systems such (e.g., →Bitcoin, →Ethereum or →Eos). This means that all users are able to read data stored in the →blockchain, which makes public blockchains suitable for use cases that aim at widespread diffusion, e.g., payment transactions or public registers. →Private and →permissioned blockchains, which are relevant in the business environment (for example, in the interbank area or in →sourcing) in contrast require the membership to a specific group or organization.

A public key is component of →asymmetric encryption procedures where each network participant has a public and a →private key. The public key is used for encryption and the →private key for decryption. Both keys are essential elements in moste →cryptocurrencies.

→Business model in the insurance industry that denotes a digital-only strategy and is synonymous to →neo insurers. Similar to →neo banks PDIs offer their digital products and services (often in a limited range) via electronic channels without operating physical presences. Among the examples are Friday, Getsafe or Lemonade.

In contrast to classical computer technology, which is based on the processing of binary data in bits, quantum mechanics transmits signals by means of so-called qubits, which may assume several states. Depending on the specific implementation, qubits have high requirements, since they require a superposition state coupled to very low temperatures and are also highly fragile in this state. At the same time, the microwaves used for signal transmission to the qubits are extremely fast and thus exceed the processing speed of classical computer technologies by orders of magnitude. Although the first steps of quantum computers have been realized by Google, IBM or Microsoft, there productive use cases of this technology are still lacking. However, high expectations for the processing of data-intensive applications (→big data) are associated with quantum technology, which should enable new applications in the areas of artificial intelligence (→AI, →AI application areas). In the financial sector, securities trading, portfolio management or risk analysis are considered as promising areas, since the effort involved in calculating probabilities is significant in these areas. At the downside of this high computing power are also risks in the area of encryption (→cryptography), since the security of →asymmetric encryption mechanisms is based on computationally intensive prime number calculations. Should quantum computers be able to perform these calculations in a short time and thus break the encryption, this would have a considerable impact on the security of today’s →cryptocurrencies.

The two-dimensional bar or pattern code is used for fast data acquisition as well as data storage and transmission. One application are of QR codes form is the processing of payment transactions (so-called QR code payments). Enhancements include the Micro QR code, the Secure QR code (SQRC), the iQR code and the Frame QR code. Originally, the QR code was used to mark assemblies and components in the logistics of Toyota Group.

Consortium of companies with approximately 300 members to develop an →enterprise blockchain solution based on →Corda. Potential use cases are discussed for numerous industries (e.g., banking, insurance, healthcare, trade finance) as well as for →digital assets. In the financial sector, the solutions include, for example, lending, →crowdlending, →regtech solutions such as reporting or electronic central bank money (→CBDC).

Technology for automatic identification and localization of objects using radio labels and contactless readers. An RFID system consists of a data medium (transponder or tag), a writing/reading device with an antenna and a →gateway for forwarding the data to operational →application systems. The RFID transponder is activated by the reader using weak electromagnetic waves and, depending on the technology, data may also be written on the RFID tag. There are two types of transponder technology: (1) Passive transponders lack an own power supply and draw their energy from the energy field of the reader. (2) Active transponders have their own power (battery or rechargeable battery) and own wireless networking equipment. The use of RFID opens up the way for numerous new applications, such as contactless payments at the point of sale (→PoS) or baggage tracing at airports. Integrated solutions require the RFID readers to be connected to the operational →application systems via →gateways, which enables data in →ERP systems (e.g., stock levels, tracking information) to be updated in real-time.

Real-time payments can be credited to the payee’s account within a few seconds (<10 s) (settlement). This enables the payee to immediately and irrevocably dispose of the received amount of money at all points of sale or →ATM terminals. Examples are SEPA Instant Credit Transfer or →TARGET Instant Payment Settlement Network in Europe or the →IMPS in India. In the USA, The Clearinghouse is a system run by banks, while the public system FedNow is not expected to be available beyond existing →ACH systems until 2023.

A network used for inter-bank payment processing that executes gross payments (i.e., without clearing with other (counter) payments) in real-time (i.e., directly and without intermediate storage) (→real-time processing). RTGS differ from →ACH systems since they typically clear payments against each other at a certain time or at the end of the day. Examples include →TARGET (Euro zone), →SIC (Switzerland) and Fedwire (USA). While these are centrally operated systems, more recent approaches are based on decentralized →blockchain technology. One example is →Ripple, which focuses on international (i.e., cross-border) payments, and the →DLT system →Hyperledger (ECB/BOJ, 2017), which was used with positive results in the Stella project by the European Central Bank (ECB) and the Bank of Japan.

In contrast to →batch processing, data processing in real-time means that function calls (i.e., the activation of program modules via interfaces) and data transfers in →application systems are executed without delay and within defined time intervals to ensure low latency times. For this purpose, real-time systems link the location of data use and the location of data creation Real-time is opposite to batch systems known from →business analytics, where updates occur periodically or at certain times (e.g., at night). A typical use case is when, customers can check the current processing status of an order (e.g., a credit transfer) in their →online banking system which is always up to date. Other examples include real-time credit transfers (→RTP) or online account balance inquiries or credit checks. Contrary to technical real-time systems (e.g., a machine operating system), the temporal (latency) interval is not exactly defined in the business context of use, i.e., both a processing time in the range of milliseconds, such as on financial exchanges, and in the minute range as with credit checks or →cryptocurrencies would correspond to the real-time understanding. Real-time processing may be seen as an important design feature of →digitalization and is subject to numerous →fintech solutions.

A model that represents a certain aspect of reality according to specific characteristics and that is valid for a class of applications across individual organizations. As a reference model, the →bank model shows all process and task areas of universal as well as private banks and forms a starting point for analyzing →business models, the (electronic) support and design of business processes and process variants as well as the assessment of standard software (e.g., →core banking system). In →business information systems, numerous approaches for reference models as well as mechanisms for instantiating or adapting these models to specific organizations have been developed.

Regtech refers to technologies in the field of regulatory affairs. The use of technologies such as →big data, →blockchain technologies or artificial intelligence (→AI) is intended to support financial service providers in the →compliance with regulations (e.g., →GDPR, →MiFID, →PSD2). Solutions include b-next, DHC Vision and Targens.

In contrast to the general and technology-oriented term of a →sandbox, the regulatory →sandbox is an environment that offers beneficial conditions for →startup companies in the sense of an →incubator. For example, not all regulatory requirements of the state or the federal government are directly applicable to companies in the startup phase, which can develop in a less regulated environment. The aim is to promote →innovation and to foster competitive advantages.

→Data structure used in the →cryptocurrency →Polkadot, whose →mainchain acts as a relay between several other →data structures (→para-chain) and thus contributes to the →interoperability of →blockchain and →DLT frameworks.

Refers to contactless payment in →mobile banking, especially via the use of mobile devices such as smartphones. →Virtualization not only applies to the medium of exchange money itself, but also of the associated infrastructure. For example, smartphones may also serve as virtualized card terminals.

Refers to invoking an →application system or application module via a function interface (→API). This call is made via the network (remote) and allows to use the functionality of the target system. RPC is the basis for the distribution of application functionality and a core component of the concepts of →cloud computing and →API banking.

Architectural style that is underlying the use of →API, which stipulates that web resources may be addressed via a defined content structure. This structure contains, for example, the commands (e.g., get, post, put, delete) as well as control and user data in a machine-readable format such as →JSON. REST is recognized as easy or lightweight approach to integrate content from (internal or external) resources into web pages (e.g., map, stock price or weather data). The use of REST to call →web services has led to the term RESTful web services and, in the context of →API, to the name RESTful API.

Consumer strategy that has received widespread adoption with the internet, which is known to shift purchasing power to customers. Various forms of →digital platforms (e.g., →electronic markets, →e-commerce) allow customers an efficient and comprehensive market overview, which they use to inform themselves prior to purchasing goods in physical stores. This behavior is also observed in the financial sector, where (potential) customers are likely to be more informed and thus require skilled advisors within the branch offices.

Organizational unit remaining with a company that has outsourced activities (→outsourcing) to a third-party provider (→TTP). A RO represents an interfacing organizational unit, which has sufficient knowledge to negotiate service level agreements (→SLA) with service providers, to mediate between users of the service in their organization and the service provider as well as to monitor the ongoing performance of service provisioning. ROs are essential for →fintech companies since their →startup status requires them to source services from existing service providers (→TTP). The counterpart to RO on the service provider’s side is the →service desk as a single point of contact (→SPoC) for the →outsourcing company.

This key performance indicator (→KPI) is widespread in the field of investment calculation and is determined for single investments from the capital employed, or the cost of capital and the profit achieved, or the profit for the period. Variations that are also used in the →startup sector are return on equity (ROE) and return on assets (ROA) (see Fig. 8).

A →KPI used to measure the innovative capacity of companies, which relates the effort required to develop new products and services to gross profits (see Fig. 9). Typically, the KPI is negative in the early phases due to a lack of sales but should move into positive territory once the →innovation is launched.

Ripple is an →open source →protocol developed by Ripple Labs (originally Opencoin) for a global payment network based on cashless transactions in multiple currencies (e.g., Dollar, Euro, Yen, →Bitcoin). The focus is on payments among banks worldwide, which requires →liquidity in the respective foreign currencies and an efficient execution the payment transactions. At present, Ripple is able to process 1500 →TPS and requires an average time of four seconds for executing a transaction. Ripple uses the →coin →Xrp and has developed various applications, in particular xRapid for ensuring →liquidity in international payments (banks hold →Xrp instead of own nostro accounts), xCurrent for enabling payment execution in real-time (→real-time processing), as well as xVia, which allows to attach documents (e.g., invoices) to the transactions.

These advanced portfolio optimization systems are also known as →robo advisors and combine the terms “→robot” and “advice”. They refer to an electronic advisor on a website or a (mobile) →application that supports clients in investing or borrowing money to varying degrees similar to an asset manager. The functionality may comprise simple recommendations without prior knowledge of the client, recommendations based on already existing client data (e.g., in the case of pending credit extensions) as well as (active) automated portfolio restructuring depending on predefined parameters. In addition, recommendations may be based on questions that users need to answer to select investment or credit products. Typically, providers charge a fee for such portfolio management, which they specify as a percentage (often < 1%) and for the desired investment amount. Because of its focus on client interaction and portfolio management tasks, robo advisory is not identical to →RPA, which aims to reduce media breaks in business processes. Technologically, →robo advisors are often based on artificial intelligence (→AI, such as →NLP or →deep learning) in combination with a text- and/or language-based →chatbot. Examples of providers in the robo advisory market segment that has emerged since 2010 are Betterment, Oskar, True Wealth or Wealthfront. Meanwhile numerous established financial service providers (→incumbent) also offer robo advisory solutions. So far, despite lower fees, these systems have only been able to establish themselves in niches (e.g., for smaller investment amounts) and as a supplement to existing customer advisory services, but not as a substitute in the advice-intensive investment business. However, future growth may be expected with a growing sophistication of the systems, an increasing familiarity with digital solutions and the generational change (→generation) in general.

Machine that performs activities similar to activities that were formerly performed by humans. In the case of physical robots, these are used by industrial companies in manufacturing or by service companies in contact with customers or patients. For example, numerous financial service providers have conducted experiments with the “Pepper” robot for customer interaction in branch offices (→AI application areas). With the increasing process automation, the term robot has also been used for software (→robotics). The robot (or the robot software) then executes one or more automation artifacts sequentially or simultaneously, whereby several licenses are often required for simultaneous execution. To enable robots to access the operational →application systems (e.g., →ERP, →core banking system), companies usually run them as virtual employees (→RPA).

In contrast to robotic process automation (→RPA), the use of →robots in →desktop automation considers human action (so-called bot-human interaction), and aims at an accompanying automation (so-called attended automation). The →robot assumes the role of a →virtual assistant that supports the (human) users in real-time (→real-time processing) with recommendations for action or information from various systems or databases. Similar to →RPA, RDA does not require any adaptations to existing systems or processes, as is typically the case when introducing workflow solutions.

This specific →application software takes over tasks that were previously performed manually (e.g., typing data from one application system and re-entering it into another). The software, also known as a “robot” (→bot) (e.g., from BluePrism) or UiPath), mimics the user and independently processes predefined activities and assumes the roles and tasks of employees. The type of support provided by the →bot may be attendant (i.e., the robot works alongside employee without disturbing them) or unattendant (i.e., the business process is fully automated without human interaction). The application areas of RPA include →screen scraping, rule-based work, knowledge-based work, and cognitive applications (→cognitive computing). As shown in Fig. 10, the RPA solution builds on existing workflows and technical platforms and focuses on the user interface (or user interface), which may be characterized along the processing complexity and the type of data capture. The higher the processing complexity and the more unstructured the data, the more the RPA solution tends toward cognitive, thereby applying artificial intelligence (→AI) or machine learning (→ML) techniques. Simple →screen scraping focuses on structured electronic data and extracts this data (e.g., last name, first name, customer number) from an →application system and then enter it into a another →application system like a human worker. Advanced methods have sophisticated processing rules and are also able to process data in weak or even unstructured form. In the →fintech environment, they are used, for example, in →robo advisory or →wealthtech solutions.

Denotes the use of hardware- and/or software-based →robots to automate entire business processes or specific activities within these processes. Due to the immaterial nature of the financial industry, mainly software-based →robots have seen adoption (e.g., →RDA, →RPA, →robo advisory), while hardware-based →robots like the Pepper robot (→AI application areas) more or less remained innovative eyecatchers.

Following the two interpretations of →robots, the term either refers to hardware or software →robots. The combination of “robot” with “automation” denotes the (re)design of a solution (e.g., a business process, an individual task) by applying →robots, for example, →RPA or →robo advisory. Similar to →digital transformation, robotization may be seen as a a transformation process where an existing situation is improved by implementing (hardware and/or software) robots.

Describes the go-to-market or integration of a new product, →service or software. The roll-out occurs after development and testing have taken place and is often referred to as deployment for software products. If businesses, such as →startup or →fintech companies, release their first product or if →incumbents introduce a new →business model, it is more likely a →launch.

As a →main-chain, it manages a number of →sub-chains, which serve specific application purposes. For example, a →sub-chain might interact with →IoT devices that have something in common (e.g., similar environment, functional purpose).

In the field of transaction processing, routing determines the next step after a task has been finished. It is often conducted by value added service providers (→VAS) which act as →gateways. For example, routing is widespread in →electronic payment transactions and occurs when the routing of a transaction from the →acquirer to the →issuer is selected within a payment network.

Best known method of →asymmetric encryption, named after the surnames of its founders Ronald Linn Rivest, Adi Shamir and Leonard Max Adleman, and created in 1977. Due to the shorter key lengths, however, →blockchain systems such as →Bitcoin use the →ECDSA method instead of RSA, which is widespread for encrypting files and messages.

A method used in →cryptography that is intended to provide additional security for →hash values. Since random characters are added to the hash calculation, it is known as “salting the hash”.

Isolated sandbox environments mainly serve development and testing purposes. Actions or measures occuring within the sandbox have no effect on the external environment (e.g., production). Two forms are often present in the →fintech context: (1) A →regulatory sandbox is provided by regulators and allows innovative products, →services and →business models to be tested. (2) A technological sandbox is an environment where digital solutions (→MVP) are tested regarding their functionality, e.g., with pilot users. →Fintech companies and meanwhile also →incumbents work with sandboxes to test new developments and to prepare products or →services for the market.

Refers to the ability of a system to change in size, usually towards expansion. The term is used in a business and technical context. (1) From a business point of view, scalability denotes the ability of a →business model to grow at low or negligible marginal costs while increasing profits. Especially →digital or →platform-based →business models feature settings where growth of revenues and investments are not correlating equally. Rather, →platforms with immaterial products (e.g., software, financial services) are primarily based on →IT resources and standardized processes due to the lack of physical production and logistics activities. As a result, growing user numbers and product ranges may be handled with little additional effort. (2) From a technical point of view, scalability refers to the ability of →application systems and technical infrastructures to cope with a higher transaction volume without compromising performance (→TPS). For example, well-known →blockchain frameworks such as →Bitcoin and →Ethereum are less scalable than centralized credit card networks (→EMV). Numerous improvements are aimed at increasing scalability. These include approaches of →on-chain scaling, such as the Bitcoin improvement proposal (→BIP) or the Eth 2.0 extension, as well as →off-chain scaling (so-called second layer solutions) with external networks such as the →Lightning Network for →Bitcoin or Plasma for →Ethereum.

Global framework for enterprise-wide scaling of agile practices (→agility), which is widespread in software development in larger organizations that feature numerous stakeholders and projects. SAFe comprises the three conceptual levels (1) portfolio, (2) program and (3) team. These break down activities from the overall organization (portfolio) to larger groups of about 100 people (program) and finally to smaller groups of up to ten people (teams).

Refers to the design of a typical credit card →payment system with the involved roles and market participants. As scheme bundles jointly defined rules, regulations and standards for the provision and execution of operative payment processes using one or more types of payment methods. In practice, a distinction is made between national (domestic) and international schemes. The former comprises the country-specific settlement systems, such as Girocard and the latter include schemes of Visa, MasterCard or American Express (→EMV). The credit card schemes feature both the →four-corner model (→acquirer and →issuer are different players with Mastercard and Visa) and the →three-corner model (→acquirer and →issuer are the same company with American Express and Diners Club). Under a two-corner model, the merchant would issue the card, accept it in its own outlets and finally process it through its own systems. This reduced model demonstrates that with →PSD2 neither →acquirer nor →issuer will have to hold a →banking license.

Also known as web scraping or web harvesting, on-screen scraping comprises programs for extracting visible text or data from user interfaces of →application systems. In process automation via robotic process automation (→RPA) systems, such methods are used when electronic interfaces (→API) are not available or the creation or adaptation of interfaces is too costly.

Originating from the sport of rugby when the game is (re)started and all players crowd around the ball, the Scrum methodology has received large attention in project management. Here, Scrum refers to an →iterative approach, which is used in particular in agile software development (→agility). The methodology combines the qualities of team cohesion and disciplined adherence to rules. It comprises three roles (product owner, Scrum master, →dev team), four artifacts (product backlog, sprint backlog, increment, definition of done) and five ceremonies (sprint, sprint planning, daily Scrum, sprint review, sprint retrospective) (see Fig. 1). The goal is to define the development tasks and to list them in a backlog, which is then planned to be addressed in sprints of several days. During these intervals, increments of the entire solution are developed until it is finished. Today, Scrum is applied in many projects beyond software development with the Scrum master being responsible for coordination with the development team (so-called →dev team) and acting as a mediator to other Scrum stakeholders.

This term summarizes measures that aim at the successful presentation of a website in digital media, which are primarily pursued marketing purposes. The goal is that businesses are listed among the top results when users conduct searches on electronic →platforms or search engines. It is based on the observation that users focus on the top listed results and avoid scrolling down long lists. SEO optimizes the keywords in web pages that search engines use for indexing as well as the number of backlinks (or referencing of the page on other pages) since they are also considered by the →algorithms of search engines. Since →fintech companies strongly rely on digital presences, SEO measures are an important element in their marketing strategies, in particular in the consumer segments (i.e., B2C, C2C).

Refers to the fourth phase of venture capital (→VC) financing. In this second stage, the focus is on penetrating the national market and, if necessary, on preparing for internationalization. It also features growth regarding the range of services offered, workforce, corporate growth or the development of new market segments. For the first time, the break-even point is of importance for the →startup company. Since first market successes have already been achieved and investment risks can be better assessed, →startup companies are considered much more attractive for venture capital (→VC) and private equity companies in this phase.

An →authentication procedure developed by MasterCard, to ensure security for online payment transactions.

The →protocol for secure →electronic payments was developed in 1996 in particular for electronic card transactions jointly by the credit card companies Mastercard and Visa as well as by →IT companies such as IBM and Microsoft. SET is based on various encryption methods (e.g., →asymmetric encryption) to ensure the security or trustworthiness of the transaction as →digital signatures. However, with the advent of →3D Secure solutions, the importance of SET has declined.

A physical security module of the smartphone or SIM card, that is responsible for encryption and →tokenization. Unlike host card emulation (→HCE), the secure element does not require an online connection.

Identification code in Germany for securities where WKN stands for “Wertpapierkennnummer”, the German term for securities identification number. WKN was launched in 1995 and consists of six digits, which since 2003 may also contain capital letters. With codings like WKN existing in multiple countries, the international →ISIN is expected to replace these national numbering systems in the longer term. For example, the Deutsche Bank share has the WKN 514000 and the →ISIN DE0005140008. With the advent of →tokens as →digital assets, a similar system is emerging in this area with the →ITIN.

Similar to an →IPO, an STO aims to issue security →tokens that are subject to regulation. Compared to →utility tokens, →security tokens are thus considered investment instruments. Many of these →tokens are based on Ethereum’s →ERC-20 standard, which is enhanced by →KYC and →compliance functions (e.g., ERC-1404, ERC-1410).

In the →fintech context, a seed has two interpretations. On the one hand, a seed refers to one of the early phases of venture capital financing (→VC). Seed financing or seed financing denotes the financing of an idea and the research and development process up to the development of prototypes or company concepts. On the other hand, the term is found in the context of →blockchain systems and refers to a password being generated when setting up a →wallet. The seed is also used to access the →wallet and to recover it in case of problems. It is a sequence of random numbers that the system reformulates into several words or selects combinations from a list of 2048 predefined words, which allows humans to better memorize the coding.

Describes the execution of activities by users (e.g., customers) themselves. Analogous to the principle of →e-commerce where users select products from an electronic catalog or auction system, self-advisory comprises systems where users select and configure (financial) services (and possibly also providers). Among the supporting systems are →bots, configurators and →robo advisory. For example, after stating their investment goals, available capital and risk tolerance on a website or app, the →algorithms in the advisory system then suggests an investment strategy tailored to the user’s needs. The user may then agree and implement this strategy directly online.

→Wallets are used in →cryptocurrency systems for the →private key, which is necessary for managing →coins and →tokens and for executing transactions. While a service provider (e.g., block-chain.info) provides the →wallet in the case of a →custodial wallet, the user in the self-hosted non-custodial wallet model takes over this task and retains complete control (and responsibility) of the → private key.

→Digitalization creates opportunities for users to access a provider’s services directly without supporting third parties (e.g., advisors, intermediaries). Self-service is known since the 1980s where electronic shopping (→e-commerce), →online banking and personal finance management (→PFM) systems emerged. Over the years, they have reached more maturity and were complemented by other self-service →platforms, in particular, social media for exchanging information directly between users (→P2P). Numerous →fintech business models are based on comprehensive self-service functions and deliberately avoid customer contact via branch offices or via call centers (e.g., →PFM, →P2P lending, →neo insurance, →self-advisory). Among the motives are cost considerations on the provider side and benefits regarding convenience and speed on the customer side.

This technology in →identity management allows individuals to manage their personal data themselves. While this is also possible by means of a centralized approach (e.g., by a financial service provider or the state), SSI are linked with a decentralized approach that follows the belief that individuals should keep the sovereignty over their data and on devices of their choice. Decentralized infrastructures (→DLT) are a suitable infrastructure for decentralized identifiers (→DID). Since these infrastructures link transparency with anonymity, they are also solutions to contain money laundering (→AML) or illegal transactions through →KYC. Examples for SSI systems are Blockstack, Civic, Sovrin or uPort.

Refers to the analysis of feelings, moods or opinions using analytical procedures (→business analytics) as well as artificial intelligence (→AI) technologies. The focus is on the automated recognition of language (→NLP) and text in order to derive market developments or customer opinions in the sense of →collective intelligence. Examples in the →fintech area include Alphasense, Sentifi and Yukka Lab.

Direct debit is a procedure that allows creditors to debit an amount from the debtor’s account. In the context of →SEPA, SDD has existed since February 2014. It distinguishes transactions between businesses (B2B) and transactions involving private individuals (B2C) where the SEPA mandate replaces the direct debit authorization. Similar to →SCT, SDD uses the →IBAN of the parties involved and, outside the Euro zone, also the →BIC.

A transfer is a book-entry transfer of a sum of money from the account of the payer (remitter) to the account of the payee. SCT is a standardized transfer within the →SEPA area with transfers also being possible in other countries, e.g., Switzerland, Monaco and San Marino. Within →SEPA, the →IBAN is sufficient, but for payments to neighboring countries such as Switzerland, originators also need to specify the →BIC.

The terms Series A, B and C denote the stages of development when companies raise capital. The main differences between the stages are the degree of maturity of the companies, the type of investors involved, the purpose of raising capital and the type of allocation. After a company has already achieved initial success, Series A financing serves to expand the product and user base, e.g., to scale the product across different markets. In this round, it is important to demonstrate a →business model that promises long-term profit. Series A investors are primarily →VC firms and rarely →business angel investors.

Similar to →Series A, Series B rounds aim to take companies beyond the development phase to the next level and increase market reach. During this phase, attention is given to investment in new employees and marketing. In addition to Round A, there are →VC companies that specialize in investments from Series B onwards.

Series C is the third development step of a →startup company from external sources. At this stage, the company is a “young adult” whose owners have convinced →VC companies or other institutional investors that they may expect a profitable and sustainable business. Many companies end up raising funds with Series C.

In a Series D financing round, negotiations with investors will be more complex than in previous rounds (→Series A to C). Characteristics of Series D include companies that have identified a new expansion opportunity before going public (→IPO) and now need a further push to get there. Alternatively, some companies decide to remain private for longer than previously planned.

Depending on the →business model, further financing rounds in the financing cycle of a →startup company are conceivable, similar to Series C. Companies that reach this stage may proceed for reasons similar to →Series D. They either have not met expectations, they decide to remain private or they require more help before going public.

Depending on the context of use, there are two main interpretations of the term service. (1) First, a service denotes an economic activity that has an intangible character or output, that follows the principle of “use instead of possession”, that relies on a close interaction between service provider and user, and that is not able to be (physically) stored. Financial and IT services correspond to these characteristics and are therefore highly suitable for →digitalization. (2) Second, a service is a technological component that is characterized by a defined interface and functionality and may be used separately or in combination with other modules. Providers of →core banking systems are seeking more flexible →application systems with service-oriented architectures (→SOA, →web service), which should also contribute to the connectivity of internal as well as external systems. Among the recent developments are the concepts of →API-banking and →open banking, which are based on the →REST technology.

Describes a component-oriented architecture concept for →application systems (e.g., →core banking systems). The functionalities are divided into defined modules (→service) which are coupled via interfaces (→API) and corresponding technological standards (→REST, →web service). Following the two interpretations of the term →service, a SOA comprises a business and a technological perspective. The former denotes the division of operational processes into functionally delimited areas and the latter the technological implementation in application architectures as well as the standards (→web service) and →platforms used. A key →platform element are service directories, which support the administration and coupling of the individual modules. This is an important prerequisite for the creation of →business networks in the financial sector and the current concepts of →open banking. In the banking sector, numerous industry representatives have participated in the definition of the →BIAN service architecture and in the insurance sector in that of →BiPRO.

Organizational unit that a service provider makes available to its customers as a single point of contact (→SPoC). In →outsourcing, service desks are established by the service providers who channel the customer’s requirements (often from the →retained organization) via ticket systems to the appropriate parties to address the issue. For →fintech companies that use multiple sales channels or offer services jointly with other →fintech companies (e.g., →bancassurance), establishing service desks has become an important organizational measure.

Agreement on the provision of predefined →services between two actors, usually the service provider and the service user. SLAs define and govern the procurement of services in internal and external →sourcing relationships. The contents of SLAs include the precise specification of service parameters (e.g., availability, error frequency, response time) and the definition of consequences (e.g., penalities) in the event of deviations from the agreed upon service levels. The aim is to reduce information asymmetries or the potential for conflict between service providers and service users. SLAs are relevant for →fintech companies if they purchase services from third-party providers (→TPP) on the one hand and pursue cooperation strategies with established providers (→incumbent) or with other →fintech providers on the other. One example are the service bundles in the area of →bancassurance.

Sharding denotes the separation of a database on several server instances. As a concept for distributed databases sharding is also found in the context of →DLT systems. Sharding promises an increased reliability and →scalability due to the distribution of the database over several computer resources, while the coordination effort required for splitting and linking the databases also increases. It was adopted in the area of →blockchain systems, since in the original →Bitcoin or →Ethereum systems the entire →blockchain was unable to process more transactions than each individual →node. With sharding, transaction processing is distributed across multiple nodes, which significantly increases transaction performance (→TPS). Especially with →PoW →consensus mechanisms, sharding increases the risks such as →double spending, since potential attackers only require a fraction of the hash performance. An example of sharding within the →blockchain field is →Ethereum’s use of Ethereum Shards.

Denotes →business models that are based on the sharing of resources, such as labor, real estate or vehicles or other objects. A main intention is to attain economic and ecological benefits by (re)using resources instead of acquiring them (→PAYU). The sharing economy is enabled by →digital platforms which link both sides (service consumer, service providers) and support the entire transaction processing digitally, often by means of mobile devices. Examples include the well-known providers Airbnb for accommodation, Wework for office space, Upwork for work orders or gigs (hence the terms gig worker or gig economy), Uber and Lyft for mobility services or the →crowdlending and →crowdfunding approaches in the →fintech sector. As is usual with transaction-oriented →digital platforms, digital financial services (e.g., →electronic payments, insurance services) are integrated in these →platforms to enable integrated billing and/or insurance.

Concept that aims at improving the integration and →interoperability of distributed ledger systems (→DLT). It securely transfers →tokens and other →digital assets from a →blockchain into a separate →blockchain and moves them back into the original →blockchain if required. The →two-way-peg method connects the sidechain with the associated →mainchain and enables the exchangeability of assets. Sidechains increase flexibility by allowing developers to experiment with beta versions or software updates before they enter the →mainchain. An example is the →cryptocurrency →Polkadot, which uses the term →parachain for this purpose.

Strategy that aims at maximizing a single key performance indicator (→KPI), e.g., profit as the primary goal.

A single-dealer or single-bank platform is a →front-end system linked to the →core banking system that combines electronic and customer-oriented trading. Users or bank clients can access →OTC trading and other markets through an SDP via a single user interface. In addition, an SDP collects and consolidates information from various sources (e.g., →liquidity, prices) in order to provide the user with aggregated information. Single and →multi-dealer platforms may coexist at the same institution.

The initiative for a European payment area was introduced in 2008 and aims at processing payment transactions between the member states without →media breaks. In addition to data and message standards (e.g., →BIC, →IBAN, →ISO 20022) as well as procedures (e.g., →SCT, →SDD, SEPA Cards Framework, →PSD2, →MiFID), which are to be implemented by banks and companies, SEPA also includes an infrastructure (e.g., →EBA Clearing) and regulatory institutions (e.g., European Payments Council, EPC).

Designates a central point of contact (→POC) in an organization, often a person, for a specific topic, problem or a defined activity. In →outsourcing, for instance, this is the service provider’s service center or →service desk.

In technological systems, a SPoF denotes an element that is critical for operation since in case of failure, the entire system ceases operation. This is typically the case with centralized architecture concepts, such as centralized servers (→cloud computing) and centralized →digital platforms: if the central node fails or is corrupted, then all processes and services conducted via this →platform are affected. A higher degree of reliability is provided with the distribution of resources, which is a main feature of distributed or decentralized architecture concepts (→DLT).

Term from data management for the source of truth, which denotes a universally valid data that claims to be free of errors. In addition, SPoT refers to a centralized data platform that is accessed by other systems to enable that modifications of data are automatically incorporated into other systems. A SPoT is one of the foundations for ensuring consistent master data within organizations and is often a goal pursued with the introduction of →core banking systems. With the rise of distributed ledger systems (→DLT), decentralized alternatives for implementing a SPoT have emerged, which may complement or even replace the centralized systems. An important functionality to achieve SPoT in distributed environments are →consensus mechanisms.

Single-sign-on is an →authentication and session service that allows users to access multiple →application systems with a single login. The SSO service manages the →authentication in the various systems and allows users to switch between these →applications during the same session. For users, this increases the ease of use and for businesses it allows to track user processes across applications to identify potentials for process improvements (→process mining) and for automating manual activities (→RPA). In the financial sector, SSO is present in personal finance management systems (→PFM) when users access services from several banks or financial service providers (→multi-bank) via a (usually two-factor-based) login.

Among the established indicators for measuring the size of enterprises are the number of employees, turnover and the balance sheet total. The European Union reports that 99% of all enterprises within the EU belong to the SME segment and distinguishes three SME categories: (1) For micro enterprises, the number of employees is less than 10 and the turnover and balance sheet total is < two million €. (2) For small enterprises, the number of employees is between 10 and less than 50 employees and the turnover and balance sheet total is between 2 million € and <10 million €. (3) In medium-sized enterprises, the number of employees is between 50 and less than 250 with turnover between 10 million and <50 million €. This means that most →fintech businesses will fall within the SME category, whereas the successful →unicorns typically have left this segment. While the requirement for the number of employees is mandatory, only one of the criteria for sales and total assets needs to apply. Finally, the classification of SMEs also depends on the industry and market.

Refers to an approach in the field of data science that postulates the dominance of →algorithms over data. While →big data claims to become more powerful with a high quantity, variability and diversity of data, small data assumes that suitable algorithms can also generate recommendations for action from smaller amounts of data on the basis of probabilities.

Smart contracts refer to program code that formalizes rules in analogy to legal contracts. They form a key element for mapping and executing business logic in distributed ledger systems (→DLT) such as →Ethereum or →Ripple and are considered an essential element of the automation of financial processes in decentralized environments (→DeFi), i.e., without the participation of traditional intermediaries like banks. Obviously, the formalization of business logic in smart contracts requires a certain level of standardization in the processes, which is more likely for tasks in the back-office than in the front-office. This applies to transaction processes like claims management in the insurance industry as well as to compliance checks in general. Figure 2 shows the creation of a smart contract in the Solidity programming language, whereby each user is entitled to make deposits to the Piggybank account, whereas withdrawals are only possible for the account owner with a minimum amount of 1 ETH.

Fig. 2
Example of a smart contract (see Hellwig et al., 2020, p. 76)

Among the promises of →digitalization are to automate business processes to increase efficiencies and to improve quality measures (e.g., errors, defects per million operations). Digitalized or digitally supported processes (e.g., via workflow management systems or →robotics) are the basis for applying “smartness” and to render processes “intelligent”. This is mainly done with artificial intelligence (→AI), which adds adaptive (i.e., past behavior determines future behavior and depends on the context) and predictive capabilities to the processes.

With →digitalization, information technology (→IT) is added to physical products. The resulting →cyber-physical products or →data-driven products are able to record their status and, in combination with intelligent control (→AI), to adapt to specific situations and to include past behavior from one or more users. The potentials of “smart” or “intelligent” products, such as vehicles or machines, include the connection with →smart services in order to realize sharing models (→sharing economy) or concepts of predictive maintenance.

Refers to a →data-based service that is billed via the pay-as-you-use principle (→PAYU) and differs from classic →IT-based service, which are rather static and standardized. In contrast, smart services are characterized by →personalization with regard to the user and/or usage context. They incorporate personal and/or situation-specific data that they receive via mobile devices (e.g., smartphones, tablets, →wearables). Although the distinction is not clear-cut, the addition of “smart” to →data-driven services implies the use of artificial intelligence techniques (→AI) that allow greater interactivity with users (e.g., via →chatbot) and include learning skills. Smart services are often referred to as complex service systems, since a smart car-sharing service, for example, also requires a connection to a navigation service, a parking service and a →payment service.

Many →fintech companies in the banking sector are using mobile technologies—in particular smartphones—as primary interaction channels with customers. This distinguishes them from traditional →direct banks, which have grown with →online banking via the internet. Examples of smartphone banks are Monzo, N26, Neon, Revolut, Starling or Yapeal. Since these providers often pursue digital only strategies, they lack physical branch offices and rely on call centers, →apps and →chatbots for customer contact. This obviously leads to effects of rationalization, why smartphone banks (as well as →direct banks) often feature cost advantages over established competitors (→incumbent). However, the digital only model is also known to show shortcomings in customer service (→customer experience) due to lacking phone numbers, poor skills of →chatbots or call center staff and slow or even no responsiveness to email inquiries.

A term used in two respects to describe both a sustainable →business model and the use of social media technologies. In the first sense, social banks pursue the so-called triple bottom line principle, which recognizes people, the environment and profit (→ESG) as three cornerstones. The aim is to reduce the negative effects on the scarce resources and to achieve transparency in all business activities. Customers should be informed how their money is being used (e.g., who and what exactly was financed, what the losses and profits are and who the beneficiary is) and banks should report regularly how they have achieved these objectives. Ultimately, social banks try to differentiate themselves from traditional banks that pursue a →single bottom line strategy, e.g., primarily maximizing profits. In the second sense, social banking refers to the use of social media technologies to support banking processes. This includes, for example, advising clients in communities (“from clients for clients”), publishing investment recommendations (→social trading) or the general exchange of information on financial issues. To support social banking, the →Social CRM concept provides a broad approach along the activities marketing, sales and service.

The concept of customer relationship management (CRM) pertains to the customer-oriented processes marketing, sales and service. Businesses conduct interactions with customers via channels, which typically comprise branch offices, call centers as well as digital presences on the internet. With the rise of social media an additional interaction channel has emerged and Social CRM denotes the use of social media for CRM purposes. As shown in Fig. 3, numerous content categories in social networks (social web) may be analyzed on social media (i.e., open, internal or access-restricted social media platforms that the company operates itself or operates on external hosted →platforms) and included in the CRM system. Conversely, CRM initiates interactions with customers or responds to customer inquiries via social media. Numerous companies in the financial sector have embraced Social CRM strategies, e.g., for identifying market developments, customer preferences and moods (→sentiment analysis), for →social trading, for customer service or for payment processes (→social media payment). The implementation of Social CRM is based on the use of specific →applications that extract, analyze and forward data from social media (→social data) via interfaces (→API). For example, critical complaints from customer postings may be automatically identified using text mining methods and then forwarded to the responsible department via workflow systems. In addition to an electronic extraction of data from social media platforms, this requires an integration with the company’s →CRM systems.

Fig. 3
Areas of Social CRM (based on Alt & Reinhold, 2020, p. 15)

Social data is created by public or private messages provided during interactions in social media. Data includes the message content itself (e.g., from postings, blogs, microblogs, or podcasts), the metadata about the content (e.g., message ID, subject, sender, reference to other postings) and the user (e.g., profile name, demographic data, location data, user language), as well as other data such as the intentions (e.g., likes, dislikes, star ratings) and links (e.g., →followers). Social data is primarily used for aggregation (→data aggregation) and subsequent analysis, among other things to obtain data on customer behavior (e.g., for improved product placement, advertising or advice). Due to their value for business processes (→Social CRM), social data are an important source of revenue for social media platforms and service providers. However, the rules of data protection (→GDPR) must be observed when accessing data, which requires a clear limitation to a specific purpose or an explicit consent of the customer (→opt-in).

Social sign-in is a form of single sign-on (→SSO) based on existing social network services. Users can authenticate themselves for other services by logging in to these services using their Facebook, Instagram or Twitter credentials.

Refers to the use of social media to initiate payment transactions. →Payment service providers link the user’s social media account directly to an →e-wallet and debit or refund a payment amount (settlement) according to the specifications of the debtor or creditor. Transactions may occur both between individuals (→P2P) and between individuals and companies (B2B, C2C, C2B, B2C). Due to their user population and their global reach, social media payments like Facebook Pay or →WeChat Pay are alternatives to existing means of →electronic payments. In addition, Facebook has been a major driver of the →Diem →cryptocurrency, which was an attempt to establish an own →virtual currency.

Refers to the use of social media for investment advice, asset management or investment strategy for private investors. For example, investors share their opinions on an investment strategy in social networks where other participants may post comments and replicate them with their own assets or modify their own trading strategies. In a broader sense, social trading refers to the exchange of unregulated trading information via social networks for investment decisions. Typical types of trading are copy trading, where network member A imitates a trading transaction of network member B, and mirror trading, where network member A follows all activities of network member B, i.e., A completely reproduces the investment strategy of B. Examples of social trading providers are Wikifolio and eToro.

Behavior where one or more individuals follow or adapt to the actions of others within a group. Participants in social networks may, for example, strive for (positive) evaluations, feedback or confirmation by other participants. This may occur through purchased, fake, electronic (→bots) or authentic participants. Marketing understands social validation as a kind of social chain reaction that leads other users to similar behavior, i.e., after a user leaves a positive review for a product or a company, other, even unaffiliated users are more likely to buy this product or work with this company. Since this type of advertising is often cheaper and more targeted, it is favored by many →startup companies.

Describes the process of confirming the identity of content and subscribers using →collective intelligence (→wisdom of crowds) rather than precise electronic identities (→eID). In the financial sector, the analysis of this data is also used for credit assessment. An example is Lenddo.com.

Cooperative organization founded in 1973 by >200 banks worldwide in Belgium to develop and operate an electronic communications network between banks. Today, SWIFT links >11,000 banks in >200 countries and processes >30 million messages daily. For this purpose, SWIFT operates four computer centers (in Hong Kong, The Netherlands, Switzerland and the US) and organizes a data network for secure communication between the connected institutions (so-called SWIFTNet). SWIFT has also standardized important data and messages for electronic message interchange (→EDI) in payment transactions (e.g., →BIC code) and securities trading (e.g., ISO 15022) or contributed to their development. Future fields of development include the use of →blockchain technology and →ISO 20022 standards.

A term frequently used in the field of open software (→open source), which refers to changes in software systems (→fork) where the new and older versions remain compatible. Compared to →hard forks, soft forks in networks such as the →blockchain are characterized by downward compatibility, so that the network nodes (→nodes) can operate with both the older and the new software.

Web-based method of software delivery where a software vendor hosts and maintains the hardware and software infrastructure (→cloud computing). In contrast to traditional →on-premise software, users may remotely access the application and are not required to invest in hardware or the hosting and maintenance of the software. Since the software functionality is offered as a →service, users will not purchase an unlimited license, but pay an annual or monthly license fee (subscription model). This fee usually includes the license and the support of the software together with the operation of the “underlying” hardware. It relieves users to make upfront investments in licenses or hardware and allows them to terminate the contract after a defined cancellation period. Most contemporary →application systems, in particular from →fintech businesses follow the SaaS paradigm (e.g., →banking-as-a-service, →blockchain-as-a-service).

With the →digitalization of business processes (→smart process), products (→smart product) and →business models, the role of software has increased in comparison to hardware. In addition to the technological-driven concept of →software-defined networking, SDB is application-oriented and characterizes the increased importance of software development to master the →digital transformation. It means that competencies and structures (e.g., →DevOps) regarding software development as well as in the cooperation with corresponding service providers are required. Businesses in the financial sector are particularly affected by this “softwarization” since design elements within this industry are information-based. In consequence, many →fintech companies consider themselves as →IT-companies rather than financial services companies, which brings →big tech companies in a position to also offer financial services.

Describes the decoupling of hardware and software in a network environment. The concept is based on the →virtualization of resources and allows the integration of different end devices on one network (mostly, the internet) →protocol, the provision of location-independent virtual workplaces and data storage in the cloud (→cloud computing). In the financial sector, SDN is regarded as an approach for established banks (→incumbent) and →startup companies alike to integrate multiple end devices cost-efficiently and securely (→multi−channel, omni-channel) or to provide →services such as →business analytics across multiple systems. In adddition, the centralized management of virtual resources is valuable from a →compliance perspective.

Describes a software development environment consisting of a programming language, a runtime environment and a compiler as well as program libraries. SDKs in the →blockchain frameworks exist for →Corda (e.g., Tokens SDK), →Ethereum (e.g., OpenZeppelin SDK) or →Hyperledger (e.g., Fabric SDK).

Object-oriented programming language built on JavaScript for developing →smart contracts in →blockchain frameworks such as →Ethereum. In addition to Solidity, Clarity is a programming language that uses the →blockchain system stacks 2.0 to complement →Bitcoin with the functionality of →smart contracts and →DApps (→Blockchain x.0).

In contrast to →pool mining, solo mining denotes a single actor who participates in the →PoW →consensus mechanism procedure. When successful, this actor may claim the entire →block rewards and is not required to share them with other collaborating miners. However, solo →miners will require a high-performance computing infrastructure to achieve a competitive →hash rate.

While sourcing originates from the logistics sector and is concerned with the procurement of goods, a wider interpretation extends this meaning on the procurement of resources, such as computing services or business processes. In this wider sense, sourcing strategies may differ along four dimensions: (1) the type of the resources (e.g., the sourcing of technological infrastructure, →applications (→cloud computing) or processes (→BPO)), (2) the direction of sourcing (e.g., →insourcing, →outsourcing), (3) the location of the sourced service (e.g., onshoring, nearshoring, offshoring), and (4) the scope of sourcing (e.g., minimum, partial and maximum outsourcing), the latter being measured in steps of <20%, 20 to 80%, and >80% by the degree of in-house production. In particular, young →fintech companies with limited resources depend on external partners and sourcing relationships for →collaboration. →Service level agreements are typically used to define and control these relationships.

A company established for investment purposes whose only business activity is the acquisition of companies. For this purpose, they raise funds on the stock market and enable investments over a maximum period of 2 years in companies that they subsequently intend to merge with. In contrast to traditional →IPOs, the process is less complex and more time-efficient. The concept has also become known in the area of decentralized finance (→DeFi), as the processes (such as repayments to investors if no suitable investment objects are found) may be automated (or digitalized) using →smart contracts.

The combination of the words “coin” and “stability” designates →cryptocurrencies that are not subject to exchange rate fluctuations or feature only minor fluctuations. Stable coins thus intend to avoid a disadvantage of →Bitcoin as a →virtual currency. In particular, it aims to increase confidence in the respective currency, as it will become more similar to legal tender, especially regarding the currency function of value retention. Since the →cryptocurrency is linked to a reference currency, the base value of this reference object of the (e.g., a →token, an existing country or a →fiat currency, physical commodities such as gold, or another →cryptocurrency) determines volatility. Stable coins already exist in countries such as Brazil, China, Sweden, Singapore, and Venezuela.

In →cryptocurrencies that use proof-of-stake (→PoS) as →consensus mechanism, staking refers to the process of locking →coins or →tokens in a →wallet and to receiving rewards for contributing this way to the operation of the distributed network. Thus, staking is for →PoS-based systems what →mining is for proof-of-work (→PoW) based systems.

→Coin generated by a →cryptocurrency using the →proof-of-stake mechanism. An overview of widespread staking coins may be found in the tables on top30 cryptocurrencies in the Appendix.

According to the definition used in financial management, a company with an innovative idea evolves in case of success along several phase, in particular, the the →seed (development of prototypes or business concepts), the foundation (clarification of financing, →startup phase), the first phase (start of production and market launch) and several financing stages (→Series A-F). Since formal characteristics such as the age of the company or the number of employees are often not appropriate due to the uncertain evolution of startups, metrics such as the degree of →innovation, the →scalability of the →business model, the participation of →venture capitalists or →business angels or the life cycle phase, are commonly used.

Refers to financing in the →startup phase and thus the second phase of →VC financing after →seed financing. If successful, this is followed by the →first-stage financing phase.

The startup phase marks the phase of building up the company. Depending on the status of the →digital transformation and the technological field of application, extensive R&D activities occur in this phase, such as preparing production, sales and distribution as well as the market launch.

→Cryptocurrency that provides an →open source solution for payment transactions or the exchange of →tokens. It uses the Stellar consensus protocol (→SCP) as →consensus mechanism. The network consists of about 60 nodes and is able to handle a large number of transactions efficiently since no →mining is required.

The →protocol for →Stellar’s →consensus mechanism is based on so-called quors (a series of →nodes), which achieve a secure →consensus by exchanging signatures. The intended features of SCP are decentralized control, low latency, flexible trust and high security.

An identification standard for securities issued by the London Stock Exchange, which is incorporated into the →ISIN as the national identification number (→NSIN) for England and Ireland. A SEDOL has seven digits, six of which are alphanumeric and one numeric check digit. The conversion into the →ISIN is possible by adding the →ISO country code and two zeros as well as a final check digit. Figure 4 shows an example of an HSBC fund.

Fig. 4
Structure of SEDOL (left) and transfer to ISIN (right)

Denotes a function of a currency (→virtual currency) that aims a maintaining the value associated with the currency. It is also used in the field of →digital currencies for →cryptocurrencies that are backed by →fiat currencies or other reliable assets. These →stable coins are expected to feature less volatilatility and, thus, serve as a “safe haven” for investors.

Refers to the direct transmission of electronically recorded data or messages between two or more →application systems without →media breaks. The concept of electronic data interchange (→EDI) dates back to the 1970s and leads to an increase in processing speed as well as a reduction in manual (human) errors. According to the goals of →electronic business, STP is an essential prerequisite for integrated and cross-company processes. Sometimes (e.g., in the insurance industry) the term dark processing is also used for STP, since with a complete STP the execution is completely automated or not visible.

As part of the →PSD2 regulation, SCA is a requirement associated with the →two-factor authorization procedure (→2FA) to ensure the security of →electronic payments.

This concept aims to establish →blockchains for individual application settings, where linkages among →cryptocurrencies are important. It follows the idea that the sub-chains increase the performance of a →blockchain (i.e., the →mainchain or →rootchain) and allows higher efficiency among less participants (→private blockchain). To avoid that a small number of participants corrupts the system, links (so-called anchors regularly integrate hashes in the →mainchain) exist to a larger →mainchain, which will typically be a →public blockchain.

Refers to enhancements of the →P2P model in computer networks that aim to use selected peer members (e.g., with powerful computing resources) as →nodes that support in organizing the network. In super peer networks like voice-over-IP services (VoIP) such as Skype, calls are not conducted via a central server, but via nodes (supernodes) between the individual users. Similarly, the super peer idea has been adopted with →master nodes in →blockchain networks.

In particular in multinational supply chains, a variety of suppliers as well as logistics service providers are involved. Including financial strategies in the management of these supply chains affects the procedure and timing of payments among this parties. Several fintech →business models have emerged in the field of supply chain finance that aim at improving working capital in the supply chain, to reduce administrative costs due to digitalized processes and to achieve favorable financing terms, for example, suppliers might be paid upfront (e.g., within 2 days).

This incentive-based remuneration system for employees of a company aims to avoid that employees leave the company. Following the sweet equity model, discounted equity shares are offered to employees as a binding bonus arrangement by the investors (e.g., the founders of a →startup). In the case of a management buy-out, managers may acquire capital shares, for example, at preferential conditions from the co-financing investment company, provided that certain basic conditions, such as ensuring business continuity or initiating measures to avoid customer churn, are met.

Switzerland’s national clearing system is operated by SIX Group, a joint effort by Swiss banks, and operates both as a →ACH and a →RTGS. SIC was established in the 1980s and is today the main actor for processing →electronic payments in Switzerland. In 2021, SIX has announced together with the Swiss national bank, to establish a dedicated networking infrastructure referred to as Secure Swiss Finance Network (SSFN), which creates a secure communication environment for over 300 banks and financial service providers that are connected to SIC.

In the field of computing networks, switches connect resources within a network and routers connect networks and switches. In the context of →electronic payments, switching is part of →routing transaction information to the corresponding recipient as part of the payment value chain (→payment service). Switching is necessary when the →acquiring bank needs to determine the appropriate →issuing bank and the appropriate clearing and settlement mechanism (→CSM). Switching also includes the conversion of data formats and operates as a →gateway that converts external formats into an in-house format for →authorization and settlement.

An encryption method (→cryptography) where the sender and receiver are using the same →private keys for encryption. Among established procedures are the advanced encryption standard (→AES) and the message authentication code (→MAC).

→Cryptocurrency from the decentralized finance (→DeFi) environment, which is built on →Ethereum and supports the trading of synthetic financial products (e.g., derivatives based on tangible or intangible assets).

Tablet advisory describes the use of mobile devices such as tablets or smartphones to support financial service providers in advising customers. It aims to increase →customer experience with the interactivity and →personalization of the →applications on these devices (e.g., →robo advisors), but also to increase the efficiency of the advisory process. Especially the use of table advisory in the physical advisory situation often enables a more intuitive access to understanding the developed financial solution, as advisors develop the offer interactively with the customer, which makes it easier to follow and to understand what is being offered.

→Data structure based on the concept of directed acyclic graphs (→DAG), which is used in the →cryptocurrency →Iota.

→Service offered by the →ECB since 2017 for processing real-time payments (→real-time processing) between banks in the Euro area according to the SEPA instant credit transfer scheme. Participants include central and commercial banks.

Companies that are concerned with providing infrastructural services for →e-commerce and →mobile commerce. These include, for example, →authentication services (e.g., 3DS authentication, risk assessment or scoring) or specific →identity verification procedures (e.g., →video ID procedures). TAP complement the roles of →issuers and →acquirers in the →four-corner model.

Using a →consensus mechanism without →mining, this software provides functionalities for a secure and consistent replication of an application on many systems. For security reasons, Tendermint should work even if up to one third of the systems fail. Consistency means that every non-failing machine has access to the same transaction log (→protocol) and calculates the same facts. Secure and consistent replication is important in →DLT systems and for fault tolerance in many use cases (e.g., currencies, elections).

Similar to →Bitcoin or →Ripplecoin, Tether is a non-unregulated →cryptocurrency that supports a 1:1 to the US Dollar, the Japanese Yen or the Euro traded →stable coin. Tether was founded in 2014 under the name Realcoin, but changed to Tether shortly thereafter and its →USDT token was tradable (e.g., via the →crypto exchange, →Binance) as of 2015.

Tezos is both a →cryptocurrency and an →open source platform. It is supported by the Swiss non-profit Tezos Foundation with a global community of →validators, researchers and developers. The →Token XTZ is classified as a →utility token and serves as the basis for →tokenization initiatives as well as for the remuneration of →validators (→baking). Tezos aims at providing planning security for investors since only →validators decide on enhancements and avoid that →hard forks take place.

→Cryptocurrency based on →Ethereum, whose →ERC-20 →token Theta is used in the fields of video streaming and computer gaming. It allows users to share videos via the →DApp Theta.tv, which is integrated into numerous Android smartphones and also includes payment functionalities.

In the area of credit scoring, a thin file refers to a limited creditworthiness, i.e., a individual person or legal entity with a short credit history. Thin files face difficulty in obtaining approval for loans or other forms of financing due to this missing history in dealing with loan repayments. As young entrepreneurs or →startup companies typically face a thin file situation, credit agencies often use alternative data for their credit assessments, e.g., payment transaction history, pension payments, rent payments or information from social media.

These third-party providers (→TPP) also issue payment cards to customers without managing the bank account. The card-issuing institution (→TPP) does not have to be the same institute as the provider managing the account (→issuer).

Third-party payment service providers are third-pary providers (→TPP) that specialize on payment services in compliance with the →PSD2 regulation. The term TPPSP includes payment initiation services (→PISP) and account information services (→AISP). Using the account holder’s personal access data, both types of service providers gain access to the account holder’s payment account. Payment initiation services initiate transfers to third parties, while account information services query the account balance and/or transactions.

Third-party providers who offer specialized services, for example in →outsourcing relationships and networks (→business network, →ecosystem). Numerous roles are present, for example, in the area of payment transactions (→acquirer, →issuer, →NSP, →PSP, →TPPSP) offer as defined in the →payment services supervision act (→PSD2). TPPs for →payment services comprise providers of account information and payment initiation services (→AISP, →PISP) as well as providers in the area of security services, which offer services such as →identity management, →authentication or key custody (→private key, →TTP).

This refers to the final phase of venture capital (→VC) financing. In the case of →startup businesses, this stage includes to the provision of capital after the company has left the loss area or is about to or already in the profit zone and requires further financing to penetrate the market (→Series A to F).

Compared to the →four-corner model, this architecture variant reduces the number of actors, since →issuer and →acquirer are bundled in one company and do not act as independent institutions (see Fig. 5). A well-known example of such a more closed network is American Express.

Fig. 5
Actors and activities in the three-corner model (based on Huch, 2013, p. 39)

Denotes a sequence of characters assembled according to certain rules. Tokens may be found in the field of knowledge processing, which breaks down texts into tokens for further processing (e.g., text mining), in the field of encryption, where tokens represent non-sensitive equivalents of sensitive data, and in the field of →digital assets, a digital representation of economic values. In the financial sector, text mining methods are used in →Social CRM and encryption methods are used in payments. For example, tokens contain encrypted credit card data used for online payments and mobile or contactless payments (e.g., for data exchange between mobile device and merchant terminal and between →acquirer and payment network). They are managed on token servers of →token service providers (e.g., the credit card companies). Another type of token used in the financial sector are →virtual currencies, with physical coins already representing one type of token. However, the term has spread with →distributed ledger or →blockchain technology, where tokens represent the →digital assets that are exchanged. They may be interpreted as tokens or chips and are often used synonymously for →coins. Existing forms are →payment tokens (means of payment such as →Bitcoin, →Ether, which are often subject to →anti-money laundering regulations (→AML)), →utility tokens (prepaid royalty, not a means of payment or securities), and security or asset tokens (like a security, they represent assets or derivatives and are not a means of payment). The →utility and security tokens are often based on →payment tokens, which provide important basic functionalities as so-called protocol coins. For example, the →Tron and →Binance Coin tokens apply the →ERC-20 token and can therefore use blockchain 3.0 functionalities (→blockchain x.0). Tokens are sold in initial coin offerings (→ICO) as a form of financing where customers participate in the future product. For example, they obtain the assurance to receive shares/units after the →ICO occurred).

Following from the third area of →tokenization (i.e., tokens as digital assets), the broad notion of the token economy captures the impact of decentralized infrastructures on the economy, which includes new industry segments, markets and actors. It is based on the ability to digitalize aspects of virtual and physical objects (e.g., property rights, proof of origin, authenticity) and to make them amenable to being traded. The token economy is enabled by distributed ledger technologies (→DLT) and is attributed large potential due to improved process efficiencies and streamlined value chains with less actors (→disintermediation). An example is the field of decentralized finance (→DeFi) with various forms of →crowdfunding (e.g., →NFT).

Describes the phase of an →ICO in which the search for investors who participate in →tokens initiated by a community takes place. These investors receive a defined number of →tokens for their investment.

Contract that specifies the conditions for the purchase of →tokens, e.g., →ERC-20-based →tokens from →Ethereum. The contract includes the name of the →token, the purchase price, the terms of delivery, conditions to the buyer (e.g., a certain nationality), naming of risks, confidentiality rules or the regulation of exceptional cases (e.g., loss of keys, invalid →wallet address). Similar to service level agreements (→SLA), a TPA thus provides a legal basis for executing of →smart contracts.

These service providers are responsible for managing →tokens on a →tokenization server in the area of →electronic payments. They apply to the second area of →tokenization, i.e., the security tokens in →mobile banking. Well-known providers include →issuers or operators of payment networks such as →EMV. Figure 6 shows the integration of these TSP in the →four-corner model for →mobile payments. User store their credit card data on their →NFC-capable mobile devices in the →app of e-payment providers such as Apple Pay. The →app then transmits this data to the server of the e-payment provider (step 1 in Fig. 6), who forwards them to the TSP’s →tokenization server (step 2). From there, a request for verification of the card data is sent to the debtor bank (step 3) and after verification of the card data, the debtor bank sends the primary account number (→PAN) from the credit card back to the tokenization server (step 4), which tokenizes it and returns it to the server of the e-payment provider (step 5). The server in turn forwards the tokenized →PAN to the user’s →app (step 6), where it is permanently stored unless the user deletes it. If the mobile device recognizes an →NFC field at a point of interaction (→PoI), the user first needs to authenticate himself in the →app, e.g., via password, face recognition or fingerprint (→authentication), and may then use the stored card for payment. The →app sends the tokenized →PAN together with a transaction-specific security code and the payment data to the merchant terminal (step 7). This is followed by the traditional card-based processing in the →four-corner model (steps 8 to 15).

Fig. 6
Integration of the token service provider in the four-corner model

Corresponding to the three interpretations of a →token, there are also several conceptual understandings in the financial sector regarding tokenization. The first applies to the decomposition of texts in text mining. For example, this procedure is present in the area of →Social CRM to analyze unstructured data (such as annual reports and analysts’ reports or customer postings with →sentiment analysis). A second meaning refers to data security procedures based on →tokens, where a non-sensitive equivalent (i.e., the →token) replaces a sensitive data element. For example, →tokens (non-sensitive reference value) replace credit card number (sensitive data element) for credit card use. In payment transactions, the →token may then be passed on and used without restrictions and the need for additional security measures or certificates (e.g., →PCI compliance). The →token enables the merchants to store customer-specific data, such as the last four digits of the credit card number, in their systems and use it as an identity feature or preferred payment instrument in →one-click checkout procedures. The third concept conceives →tokens as →digital assets issued on a distributed ledger (→DLT). Tokenization describes the process of creating an unforgeable digital image of an asset and may be applied to numerous goods (e.g., shares, real estate or works of art). Corresponding tokenization services are offered by →crypto banks, but since →tokens may represent all types of property rights - from tangible or intangible objects to services or rights - a market segment is emerging that goes beyond today’s investment market and allows new forms of investment such as →crowdfunding.

Includes all direct (e.g., hardware and software procurement, development and maintenance costs) and indirect (e.g., downtime costs, →transaction costs) costs associated with owning a resource (e.g., hardware and software systems). The ownership lifecycle ranges from procurement through operation to maintenance and further development (e.g., due to regulatory requirements) and directly affects the cost burden of a company (→CIR). Besides establishing an overall view on these costs, the goal is to reduce TCO (e.g., via the use of →open source solutions) and to make fixed costs variable (e.g., via →outsourcing and →services).

A trading platform is a →digital platform with market functionalities (→electronic marketplace) for electronic economic transactions (→e-commerce). In the financial sector, there are established players (→incumbent) such as the financial exchanges (→electronic exchange), and younger players such as multi-trading facilities (→MTF) and over-the-counter markets (→OTC) as well as the →crypto exchanges. Trading platforms allow investors and traders to buy and sell securities, foreign exchange, options, futures, →cryptocurrencies and the like, online, either directly or via →financial intermediaries. Due to the large number of trading platforms, permanent and ubiquitous trading becomes possible and tends to contribute to a reduction of →transaction costs in the financial sector.

Clearing system that settles all Euro payments in the Euro area between the European Central Bank (ECB) and the central banks of the European countries that have introduced the Euro. The system connects the banks via the →SWIFT network and operates both as an automated clearing house (→ACH) as well as a real-time gross settlement system (→RTGS). Target2 has been in use since 2007 and the banks are connected to the system via the →SWIFT network. The replacement of TARGET by the T2 platform, has been announced for the end of 2021 and will also bring the adoption of the →ISO 20022 standard.

Characteristics of a →DAG based on the graph-based networking of transactions.

→Business model of financial service providers that focuses on the processing of financial transactions (e.g., payment transactions, securities, credit, insurance orders). The goal is to achieve a cost advantage in →back-office operations by realizing economies of scale, often by bundling the settlement activities of several banks. Since transaction banks focus on transaction execution, they not necessarily require a →banking license. This also allows →IT service providers to position themselves in this domain.

For transaction costs, two interpretations may be distinguished. (1) In a narrower and more colloquial sense, they describe the monetary costs of an economic transfer of goods between economic entities. In the financial sector, such transaction fees are, for example, the costs of a credit card transaction, which are incurred by the merchant as a percentage of the value of a transaction per transaction (→MSC) or the interchange fees (→IF) flowing from the →acquirer to the →issuer. (2) In a broader and industrial economic sense, they refer to all monetary and non-monetary expenses associated with an economic transaction on the part of the buyer and seller. This begins with the time required to review offers and vendors in the market and continues through the negotiation of price and contractual conditions to possible disputes on the enforcement of agreed clauses. In principle, it may be assumed that →digitalization with comparison platforms (→electronic market) and numerous →self-services will help to reduce transaction costs and thereby contribute to the networking of companies (→business network). Examples include cooperation between banks (→incumbent) and between banks and insurance companies (→bancassurance) as well as between banks and →fintech companies. The reductions in transaction costs are also reflected in the recent →ecosystems and →open banking strategies pursued by many actors in the financial industry.

After →authorization of a →digital payment, the merchant and the →issuer store information about the transaction in their systems, which indicates that a payment amount has been transferred from the cardholder’s account. This process involves the →issuer, the merchant, the network service provider (→NSP) and the merchant bank. To initiate the processing, the merchant has various options for communicating the information about the authorized transaction to his merchant bank. For example, the merchant may send the information directly to the →NSP via the →POS terminal, which prepares the data and transmits it to the merchant bank. Likewise, the merchant may directly transfer the payment information to the merchant bank on a specific date that was agreed upon in advance. Regardless of how the merchant handles the transaction, the →issuer authorizing the payment needs to simultaneously enter a note in the account management system until the account is debited. Once this information about the transaction has been received by the merchant bank, the clearing and settlement (→CSM) process starts. In the context of →ATM transactions, the cardholder’s account is debited immediately, i.e., in real-time.

This key metric (→KPI) reflects the performance of transaction-oriented →application systems and networks. It is relevant for transaction processing in →core banking systems (e.g., in payment transactions or stock exchange orders) as well as in networks of →SWIFT, credit card providers or →cryptocurrencies. For example, Visa states a maximum TPS of 65,000 (Visa, 2020) for its credit card system, while internet sources (Sedgwick, 2018) assume a maximum TPS of 1700 TPS for Visa. In contrast, the TPS of the →Bitcoin blockchain is currently around 4–7 and is therefore subject to various enhancements to increase performance (→BIP). Due to such enhancements →Dash reaches about 30–56 TPS, →Eos about 5000 TPS, and →Neo about 1000 TPS (De Kwaasteniet, 2018). A similar situation may be observed with →Ethereum, where the traditional TPS of 7–15 is expected to rise to 100,000 with the Eth 2.0 expansion (Simmons 2020).

→Cryptocurrency founded in 2017 on the basis of →Ethereum and later constructed as an independent peer-to-peer network (→P2P), using the →proof-of-stake →consensus mechanism. It is organized according to the →DAO principle and differentiates itself through its free use and the claim to achieve a high performance of about 2000 transactions/second (→TPS) compared to other existing →blockchain frameworks.

Computing platform (e.g., based on Intel-CPUs) that features certain aspects (e.g., the transparency and verification of transactions and time logs), which are used in →consensus mechanisms. For example, the →PoET uses a random wait time for the construction of blocks (the →validator with the shortest waiting time creates a block), which is delivered by TEE.

A trustworthy third party is an organization that is trusted by the actors involved in an economic transaction. TTPs have emerged in the area of electronic identities (→electronic identity) or trust services (→custodian). Recent developments in the field of →DLT aim to replace intermediaries such as TTP with trust in the technological solution.

An →authentication procedure that is intended to provide a high level of security when accessing resources (→SCA), especially in the area of accounts. The →PSD2 regulation posts that at least two of the three characteristics listed are present for the verification of a transaction: (1) Knowledge that only the user has (e.g., username, password, one-time password, PIN, TAN), (2) possession of objects that only the user has (e.g., hardware token, bank card, key) or (3) biometric characteristics of the user (e.g., fingerprint, iris recognition, human voice). In addition, the features must be independent of each other, i.e., if one feature is not fulfilled, the reliability of another feature is not compromised, so that the →authentication data remains protected.

A process that denotes a binding of →coins between →mainchains and →sidechains and enables the transfer of →coins in both directions. The →coins of the →mainchains are temporarily stored, which enables to generate and use →coins on the →sidechain afterwards. If the →coins of the →sidechain are invalidated, the temporarily stored →coins may be reactivated.

Refers to persons or organizations without a bank account who usually pay in cash. They typically also lack other financial products such as insurance, pensions, investments, loans and therefore have no coverage by the financial system. Alternative financial services (→alternative finance) are also limited, such as cheques or payday loans (express credit), which means that this customer group is oftsen outside of the focus of financial service providers.

Describes the unbundling of existing value chains, which comes with a decrease of vertical integration in the financial industry. It is driven by innovative information technologies (→IT, →digitalization) and the emergence of →startup companies in the financial sector (→fintech). It leads to a fundamental change (→disruption) in traditional services or product offerings, for example by replacing established payment networks (e.g., →SWIFT) with →blockchain-based solutions, replacing or at least supplementing client advisors with →robo advisory systems, or replacing traditional forms of lending with →crowdlending. Unbundling is often related to the distinction of economies of scale, scope and skill. Thus, →fintech companies may bundle services of different providers (→multi-bank) from a customer perspective (economies of scope) or concentrate on a specific service offering (economies of skill). Due to the inherent economies of scale, →business models requiring high transaction volumes, such as in the field of payment transactions (e.g., →transaction bank, →virtual currency), represent a challenge for →startup companies. However, compared to existing providers (→incumbent) with historically grown (legacy) structures, →startup businesses tend to have lower administrative and overhead costs, but are often dependent on partnerships with other providers (→sourcing, →business network). The development often referred to as →rebundling also includes the intensified collaboration of banks (→incumbent) with →fintech companies, e.g., within the framework of →open banking solutions.

Refers to persons or organizations that have no or insufficient access to banking or other financial services at market rates. Similar to the →unbanked group, there is relevance to forms of →alternative finance and newer forms of →fintech business models (e.g., →micro-financing, →mobile banking).

In the insurance sector, underwriting refers to the mathematical assessment of risk to determine the appropriate premium for a specific risk. Digital underwriting often uses artificial intelligence (→AI) to calculate premiums in →real-time on the basis of comprehensive historical data.

Generic term for identifiers of electronic resources that follow a specific structure or schema. These include function calls of application components (→API, →RFC) and concepts such as →REST and →SOA, the unified resource locator (URL) widely used for web resources, or the unified resource name (URN) widely used for electronic documents. In the →fintech environment, URIs are present in the concepts of →API and →open banking. The example of a payment instruction with the syntax and data field definitions is shown in Fig. 7. The function call “payto” reflects the structure of the command with path (→IBAN), amount (EUR 200) and a message (“hello”). At the same time, this shows that an additional standard (in this case →IBAN) is required for uniform semantics of the data fields (alphanumeric or numeric characters), which are syntactically defined in a URI. If this is not the case, coordination on the meaning of the data fields is necessary between the communication partners (or systems) prior to the exchange of data.

Fig. 7
Example of a payment instruction as URI (see Dold and Grothoff 2020)

→Startup company whose values are not yet listed on the stock exchange, but which investors estimate to have a prior →IPO market capitalization of more than USD 1 billion. This growth is typically based on →venture capital money and often “unicorns“are not (yet) profitable, as they place gaining market share before generating returns. Successful examples from the →fintech sector are Coinbase, Klarna, Lemonade, N26, Revolut, →Ripple or Transferwise.

To ensure the uniqueness of a material or immaterial object, codes are being used that either determine the affiliation of an object to a certain class of objects or they identify a specific object on item level. In the business world and within the financial sector, a large variety of standardized identifier codes has emerged to render transaction processing among multiple involved actors more efficient and to avoid costly matching processes. Among the examples are →BIC, →IBAN, →ISIN, →ITIN or →SEDOL. UIDs are also added to physical resources via →crypto anchors to prevent fraud.

→Cryptocurrency based on →Ethereum’s →ERC-20 token in the field of decentralized finance (→DeFi). Uniswap uses →smart contracts for decentralized trading of →cryptocurrencies and positions itself as a decentralized marketplace (→DEX) vis-à-vis to centralized marketplaces such as →Binance. The swap character is reflected in the idea that users may offer →tokens and receive a fee in the form of UNI tokens after the transaction in return for providing →liquidity.

Specification for electronic data interchange (→EDI) in the financial industry based on XML syntax certified by →ISO. Also known as →ISO 20022, UNIFI defines the syntax of electronic messages primarily between the actors in payment transactions (→four corner model). As the →application systems of manufacturing and trading companies (→ERP), banks (→core banking system) and market infrastructure operators (e.g., →SWIFT, →electronic exchange) support the standard, UNIFI is an approach to make conversions between different formats more efficient and contributes to reduced →transaction costs in the inter-organizational setting (→business network, →ecosystem).

Describes a balancing procedure that is applied in the →cryptocurrency →Bitcoin, whereas →cryptocurrencies such as →Ethereum or →Eos use an account assignment model. UTXO denotes →coins that result from transactions and may be used in other →Bitcoin transactions (see Fig. 8). Accordingly, an input minus a transaction fee is either marked as already spent or as output that has not yet been spent (i.e., unspent). To avoid →double spending, only unspent →coins are allowed as input for new transactions and the value of the received values always needs to equal to or exceed the amount that should be spent.

Fig. 8
Example for an UTXO calculation (Hellwig et al., 2020, p. 8)

An →ERC-20-based →token used at the Bitfinex →crypto exchange, that serves to pay fees (e.g., for trading, custody, withdrawal) at that exchange.

→Cryptocurrency based on the →ERC-20 specification and designed as a →stable coin. The aim is to use established →fiat currencies in →blockchain applications. The →token is applied in several other →cryptocurrencies (e.g., →Eos, →Ethereum, →Tron), which explains why USD Coin is also called →multi-chain.

The design of the user interface of →application systems is part of the UX design, which aims at a positive user experience when interacting with the system. UX is based on the principles of software ergonomics for designing user interfaces that are intuitive and performant in accordance with the purpose of the →application. Approaches used in UX design are service blueprinting or the design of customer journeys (→CJ), personas and storyboards as well as methods such as eye tracking or A/B comparison group tests for assessments. Since the user interface is the main touch point with customers in many, often digital-only, →fintech models, it has strategic relevance for →customer experience. Businesses adopt approaches like →DevOps that involve customers closely with development and operations to combine continuous innovation with high levels of stability.

Designates rights to use a product or to purchase a →service (e.g., computing power on the Golem platform) based on →coins of a →cryptocurrency. Depending on the purpose, a utility token may also assume the function of a means of exchange and payment as well as a security (→virtual currency). Compared to →security or asset tokens, which include shares in companies, utility tokens are less regulated and applicable on a broader scale.

Similar to the →miners in →PoW systems, the validators are dedicated →nodes in a →DLT system that have implemented the proof-of-stake (→PoS) →consensus mechanism. As co-owners (shareholders) of the →cryptocurrency, validators are involved in generating new blocks and in decisions on the further development of the system. They thus assume an essential →governance role that is also present in the concept of decentralized autonomous organizations (→DAO).

Providers of value-added services have emerged from the field of network services (e.g., mapping of data fields, →routing of messages, management of keys) and have over time also covered higher (i.e., more business-oriented) functionalities. In the financial sector, VAS exist for example in the area of payment networks (→TPPSP, →TSP) and various →business models are currently emerging with the diffusion of →cryptocurrencies (e.g., regarding →mining, →business analytics or →interoperability).

→Cryptocurrency that focuses on applying →blockchain technologies in the field of supply chain management and includes the →tokens VET and VTHO. While the VET solution is designed to achieve resource transparency by integrating data from different →application systems and →IoT devices in the supply chain using the →PoW consensus mechanism, VTHO aims at confidential trading via the →proof-of-authority mechanism in the energy sector.

Commercial enterprise or a speculative act that involves a risk. Investors or company founders enter into this in the hope of making a profit.

Venture or risk capital is a form of equity financing associated with equity and external financing. It is used to finance young companies (→startup) and is characterized by a higher risk/return profile. Typically, VC investors are rather interested in supporting innovative ideas than in short-term profit making (→single bottom line).

→Venture capital or risk capital financing is a form of corporate financing for companies that are considered to be particularly risky. It includes equity or equity-like instruments, such as mezzanine capital or convertible bonds, known as private equity. The capital is provided in the various phases or financing rounds of a →startup company (→Series A–F).

Venture capitalists provide young companies (→startup) with venture capital (→VC) for their growth. Compared to other investors such as →business angels, they operate with higher investment amounts and only invest at a later stage. In addition, they tend to pursue primarily monetary goals and try to reduce the market risk by exerting control on the company by means of ownership shares.

These customers support →startup companies by purchasing their products instead of providing venture capital (→VC). The buyers of the products already become customers of a →startup company when the company is still in an early stage of development (→venture) and the product is not yet ready for the market (e.g., via a →crowdfunding →platform). In many cases, the promoters hope that this will give them a future innovation advantage.

Data for identifying things, people, or organizations that may be found in particular in the environment of decentralized identities (→DID) and can be structured according to verifiable credentials data model specification of the World Wide Web Consortium (W3C).

A procedure approved by the supervisory authorities (e.g., →BaFin) for the →legitimation of customers via video chat. As part of the →onboarding process, new customers show their ID document to a call center employee via a webcam or smartphone, who then checks the data and initiates the →authentication. Since identification is possible regardless of location, the procedure is used in particular by →fintech companies without physical presences (→smartphone bank). Examples of providers of Video ID procedures are IDNow or WebID.

The term has two interpretations. (1) First, it refers to a form of remote support where employees provide or receive supporting →services (e.g., in their home office). These support services are particularly relevant for smaller and online companies that require infrequent support and refrain from hiring permanent staff for this purpose. The tasks of these gig workers (→sharing economy) are often in the areas of marketing, PR, social media management or web design. (2) Second, virtual assistants are →application systems that provide automated support in the form of →chatbots or →robots. They are also found under the notion of →personal assistants and establish new interaction channels (e.g., in the area of consulting and customer service) in addition to a company’s website or are combined with an →app for mobile use.

With the rise of information technologies (→IT), a →digitalization of money has occurred that has led to electronic currencies, which are also referred to as →alternative currency, →digital currency or →electronic money. First approaches date back before current →cryptocurrencies like →Bitcoin when in 1982 the scientist David Chaum designed the eCash system and founded the company DigiCash in 1990, which no longer exists today. Compared to traditional currencies (→fiat money), virtual currencies lack a physical representation of money in the form of coins or banknotes, and in most cases (with the exception of the development of electronic central bank money, →CBDC) they are not under the control of a federal authority. Virtual currencies or prepaid credit balances as non-physical and electronically stored assets may be used flexibly for large and small amounts as well as for national or international transactions. Although many existing regulations were initially not applicable to virtual currencies, more recent approaches such as the European Union’s →e-money directive or Germany’s →crypto custody business license point at an increasing regulation. Virtual currencies are usually acquired using traditional methods, e.g., by transferring electronic funds to a bank account, →e-wallet, card or other storage media. In general, virtual currencies may perform similar functions to physical currencies (see Fig. 9). As means of payment, natural persons and legal entities can use virtual currencies as a medium of exchange, whereby the transfer, safekeeping or trading is completely electronic and usually occurs in real-time (→real-time processing). Although they are not a legally recognized means of payment, virtual currencies are accepted in various environments (→e-commerce, →electronic markets). With an increasing regulation of →crypto exchanges and support from other parties, →cryptocurrencies are likely to gain in importance as a means of payment. PayPal, for example, has already announced to support payments via →cryptocurrencies. Regarding the unit of account and the value retention function, virtual currencies feature important shortcomings. In particular, →cryptocurrencies are volatile in their exchange rate development and due to possible further developments (→forks) or the competition between the different →cryptocurrencies and →blockchain frameworks, their future existence is rather uncertain when compared to classical investments in scarce goods such as precious metals. However, due to the limitations of the money supply (e.g., 21 million →Bitcoins), →cryptocurrencies are increasingly suggested as investments in combination with scarce resources (e.g., gold, water) and crypto investments have been included in numerous funds or investment portfolios.

Fig. 9
Distinction between traditional and virtual currencies

In this case, information technology (→IT) is being used to create interactive virtual environment based on digital media in which physical laws can be modified. Virtual worlds or environments are based on three-dimensional visualizations that are transmitted via large screens in special rooms (e.g., caves, →CAVE) or via →wearables such as head-up displays. With the diffusion of VR, several variations have emerged, for example augmented reality (→AR) that extends physical reality with visualizations (e.g., via AR-or data glasses) or →mixed reality, which links real and virtual worlds. A recent form or VR that is strongly promoted by →big tech firms is →metaverse.

In the technological sense, virtualization describes the creation of a virtual version of something, for example, a server, a desktop, an →operating system, or a network. Usually this is done by separating software and hardware, by emulating the hardware with software (e.g., →HCE). The main objective is to manage system loads to improve →scalability and resource utilization. Virtualization is at the heart of →cloud computing, which—despite early concerns regarding data protection and security—has also spread for →fintech solutions. In addition to this technical view of virtualization, there is an organizational view that conceives firms with a high degree of →outsourcing as virtual. Thus, even small companies with few employees may achieve a significantly higher virtual size by →outsourcing their tasks to partners and by becoming part of a larger business →ecosystem.

As an area of computational linguistics, voice or speech recognition involves procedures (→NLP) that use input and output devices on the computer to make spoken language accessible for automatic data acquisition. Similar to text recognition methods, speech recognition methods rely on artificial intelligence (→AI) and may be found in automated customer interaction (→chatbot) as well as in the interpretation of customer conversations (→sentiment analysis).

An access-restricted user environment that only grants authorized users (→authorization) access to a defined number of data or services. It may be implemented as a protected environment on mobile devices for corporate applications (e.g., during mobile work) or to prevent minors from accessing certain content. In a broader sense, →ecosystems also form a walled garden if they are successful in creating entry barriers for competitors and thus in attaining customer and partner loyalty.

In the →fintech context, wallets or →e-wallets refer to an →application, which resembles a customer’s purse and enables the virtual storage of →electronic money such as →cryptocurrencies or personal digital documents. Wallets are an important element in →cryptocurrency transactions (see the example of a →Bitcoin transaction).

This data exchange format in →blockchain systems allows the exchange of →private keys between different →wallets by means of the base58Check encryption method.

The words “wealth” and “technology” have given rise to solutions for digitalized asset management (→DAM) and investment (i.e., wealth management). As a part of →fintech, wealthtech comprises digital solutions such as →robo advisory, digital →brokers, and internet-based investment applications. Since wealth management is an area of private banking, it is characterized by close personal relationships between bank advisors and their clients. For example, →family offices often offer comprehensive services that go beyond banking to comprise legal advice or support with organizing personal affairs. It has been observed that many approaches of →digitalization are not directly applicable with the wealthy clients who value personal relationships and disapprove waiting loops in call centers or standardized →chatbot interactions. However, solutions in the field of →robo advisory aim to leverage →digitalization to provide private banking services also to less wealthy customers. An example is Quirin bank in Germany.

Refers to computer (chips) or miniature electronic devices that people wear under, with or on their clothing. These include trackers for measuring bodily functions such as pulse, blood pressure or heart rate, as well as smartwatches for using electronic services (e.g., telephone, e-mail, navigation, →apps), glasses or headphones. In combination with →bots, they allow voice-based interactions with electronic services, for example, with financial service providers. In the insurance sector, wearables have spread to support flexible rates that are based on the user’s activity (→PAYU).

Technology that has emerged from the field of object orientation and component software to enable the design of flexible modular →application system architectures. The web service stack comprises a collection of technologies that allow application components or web resources with an encapsulated functionality to be called via a defined interface (→API, →RFC). Due to these standardized interfaces, individual components should be composed more flexibly towards larger →application systems or content in web pages should be composed flexibly from various sources. The web service concept comprises two main areas. On the one hand, these are the standards of the World Wide Web Consortium (W3C) in the context of service-oriented architectures (→SOA), which were developed at the beginning of the 2000s and include XML data formats for message transmission (so-called SOAP protocol), for describing and calling web services (web service description language, WSDL) and for cataloguing web services in directories (universal description, discovery and integration, UDDI). They were adopted particularly in the business application environment, as they comprise defined security functionalities (e.g., ensuring ACID requirements in the database area). On the other hand, →REST technologies have emerged as a more lightweight concept, which is considered to be less complex and more performant, but also less secure. REST is also present among →fintech solutions, both in the →front-end area (e.g., →PFM) and in the →back-end area (e.g., modular bank). The term →microservices, which is used in this context, emphasizes that these technological →services feature functionalities of finer granularity, which are implemented by means of →REST.

This combination of the World Wide Web (WWW) and the third generation has evolved with decentralized technologies, such as →blockchain and →distributed ledgers. It recognizes the early phase of the WWW from 1992 until the beginning of the 2000s as first distributed ledgers. It recognizes the early phase of the WWW from 1992 until the beginning of the 2000s as firstauthority from centralized →platform providers (e.g., →GAFA, →BATX) to the users themselves, thus leading to more decentralization and democratization in the web. Web3 questions the role of established third parties such as banks, insurance companies and exchanges by replacing them with structures and processes of decentralized finance (→DeFi). Among the examples are →electronic payments with →cryptocurrencies, →crowdfunding platforms, →crypto exchanges for fungible and non-fungible →tokens as well as decentralized organizations (→DAO). However, it is still an open question to which extent Web3 solutions will replace existing structures since decentralized solutions tend to favor →cybercrime and responsibilities (e.g., for liabilities or after-sales inquiries) in decentralized settings are often unclear.

Available since 2011 and comparable to WhatsApp, the WeChat messaging service is widely used worldwide, with approximately 1.2 billion users, primarily in China. A key functionality of WeChat Pay is the →wallet, which may be used for most types of →electronic payments. WeChat Pay’s main competitor in China and the market leader in →electronic payments is Alibaba Group’s →Alipay.

Originating from the media sector where records that can be individually designed are marked with white labels, the term is also used for electronic services that a provider offers in a standardized form to several customers, who in turn market or use them under their own name. Digital →services such as →online banking, personal finance management (→PFM) or →robo advisory solutions, use the bank’s brand name, company logo and choice of color. It thus makes them appear as solutions from that bank, although they are standard solutions from a third-party provider (→TPP), such as the Mangopay payment solution. A whitelabel strategy allows users to take advantage of numerous services from an →ecosystem and thus achieve a larger virtual company size (→virtualization).

Also called swarm intelligence, WoC refers to the intelligence of the masses, which is largely based on the extraction of knowledge from a multitude of data (→big data). Following the idea of →collective intelligence, it is expected that with an increasing number of opinions, the quality and significance of the cumulative estimate improves. The intelligence of the crowd means that individuals who independently collect, analyze and evaluate information benefit when sharing this information in social interactions since innovation and decision-making processes are strongly social in nature. Thus, the collective opinion of a group of individuals in the information age leads other individuals to access social media such as Wikipedia, Yahoo!, Quora, Stack Exchange, and other web resources as knowledge bases in the sense of trustworthy and even scientific sources (→network effect).

This →cryptocurrency features a one-to-one relationship from →Bitcoin (BTC) to traded →tokens built on →ERC-20. It enables the use of BTC in →wallets, →DApps as well as →smart contracts on the →Ethereum →blockchain.

This →cryptocurrency →token is traded one-to-one with →Ether (ETH) and based on →ERC-20. It is used for →real-time payments on →platforms (e.g., the decentralized →e-commerce system Opensea) that are based on ERC-20.

→Application system of Deutsche Börse for executing stock orders at →electronic exchanges. Introduced in 1997, the system allows registered traders to access the market from any location and supports the entire transaction process with an electronic →order book and →clearing system. This is particularly the case if the traders are →robots such as those found in high-frequency trading (→HFT). Numerous products of →fintech companies are listed on centralized exchange systems such as Xetra, e.g., →ETF or →ETP. In addition to the trading of financial products, Xetra is also used for trading energy products (e.g., on the European Energy Exchange, EEX).

→Coin issued by the →cryptocurrency →Ripple, which was initiated in 2012 and is mainly used to support international payment transactions (→cross-border payment). The generation of these →coins is based on the XRP Ledger Consensus Protocol, which is similar to →PBFT and comprises a small number of validation →nodes. Since →Ripple also holds large amounts of Xrp in an →escrow scheme and determines access to the network, Xrp may be conceived a →permissioned blockchain.

Zcash is a →cryptocurrency based on the original →Bitcoin code base. The goal is to improve the privacy of the users compared to other →cryptocurrencies, in particular →Bitcoin. Due to the underlying zero-knowledge proof concept (→ZKP), Zcash participants may decide for themselves which data they intend to make transparent. For example, encrypted data and the corresponding balances on the →blockchain are not visible. Payment disclosure and special view keys are used to exchange transaction details with trusted third parties (→TTP) for →compliance purposes or audits.

Within →cryptography, a knowledge-free proof or a knowledge-free →protocol refers to the communication between two or more parties (the prover and the verifier). The prover convinces the verifier with a predetermined probability that he knows an information, without disclosing this information itself. A prominent method is the Feige-Fiat-Shamir protocol that is also used in the context of →cryptocurrencies like →Zerocoin or →ZCash.

→Cryptocurrency based on →Bitcoin, which has been created to clear the transaction history that is associated with the linked blocks in a →blockchain system. It uses a collective →escrow pool to draw →coins and verifies transactions by means zero-knowledge proofs (→ZKP). Although originally proposed for use with the →Bitcoin network, Zerocoin may be integrated in other →cryptocurrencies as well.

A bank that would not continue to exist without state warranties, such as rescue packages as a type of guarantee or loans. Since the economic net assets after deduction of all assets and liabilities are negative, the zombie bank is de facto a bankrupt business.

Zombie loans are corporate loans that keep debtors alive by raising capital at favorable (e.g., extremely low) interest rates. These companies are unable to earn their own cost of capital over a longer period of time, and therefore would be bankrupt if the cost of raising capital were higher (e.g., in a normal interest rate environment). The loans therefore have an increased risk of default.

A company financed with venture capital (→VC) that requires additional funding to continue its growth but has already consumed the funds from previous rounds of financing. Although revenues exist, these are not sufficient for long-term profit-making and to sustain an independent existence. This makes it difficult for the venture capitalists to make a profitable exit or sell their shares. As a result, the investors and the →startup company tend to stick to the →business model and continue to invest, benefitting from low capital costs. Since the company remains in the market rather artificially, it acts to a certain extent as a “brainless” zombie company and harms the emergence of new →business models or →disruptions driven by market forces.

3D Secure is an XML-based →protocol that serves as an additional security check for online payment card transactions. The credit card company Visa was the first to use the “Verified by Visa” procedure to improve the security of →authentication for electronic card payments.

The number 42 is commonly encountered in the →fintech and →startup environment as a reply to the question of the meaning of life or of “why you do something the way you do it”. It originates from the science-fiction novel by Douglas Adams “Life, the Universe and Everything” from 1982.

The fifth-generation mobile communications technology provides an increased speed of data transfers compared to its predecessor technology 4G (LTE). While 4G reaches up to 100 Mbit/s, 5G should achieve up to 10 GBit/s. These improvements are the basis for new use cases, in particular in the areas of →pervasive computing and the internet of things (→IoT). As for most infrastructure goods, there is an interdependence between the availability of the network infrastructure and the availability of 5G-capable end devices on the one hand and 5G-capable applications and →services on the other hand. While the technological infrastructure is increasingly available, applications are still scarce and thereby harm →network effects. Potential applications in the financial sector could include →location- and usage-based services (→LVS, →PAYU) and →smart services, the seamless use of multiple interaction channels (→omni-channel) and real-time processing in →mobile banking (e.g., with regard to security and regulatory requirements such as in the area of →AML). Although 5G infrastructures have become only partly available, the next generation 6G is looming at the horizon and promises higher speeds of up to 1 Tbit/s.