electronic banking research paper

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• Published: 18 June 2021

Financial technology and the future of banking

• Daniel Broby   ORCID: orcid.org/0000-0001-5482-0766 1  

Financial Innovation volume  7 , Article number:  47 ( 2021 ) Cite this article

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This paper presents an analytical framework that describes the business model of banks. It draws on the classical theory of banking and the literature on digital transformation. It provides an explanation for existing trends and, by extending the theory of the banking firm, it illustrates how financial intermediation will be impacted by innovative financial technology applications. It further reviews the options that established banks will have to consider in order to mitigate the threat to their profitability. Deposit taking and lending are considered in the context of the challenge made from shadow banking and the all-digital banks. The paper contributes to an understanding of the future of banking, providing a framework for scholarly empirical investigation. In the discussion, four possible strategies are proposed for market participants, (1) customer retention, (2) customer acquisition, (3) banking as a service and (4) social media payment platforms. It is concluded that, in an increasingly digital world, trust will remain at the core of banking. That said, liquidity transformation will still have an important role to play. The nature of banking and financial services, however, will change dramatically.

Introduction

The bank of the future will have several different manifestations. This paper extends theory to explain the impact of financial technology and the Internet on the nature of banking. It provides an analytical framework for academic investigation, highlighting the trends that are shaping scholarly research into these dynamics. To do this, it re-examines the nature of financial intermediation and transactions. It explains how digital banking will be structurally, as well as physically, different from the banks described in the literature to date. It does this by extending the contribution of Klein ( 1971 ), on the theory of the banking firm. It presents suggested strategies for incumbent, and challenger banks, and how banking as a service and social media payment will reshape the competitive landscape.

The banking industry has been evolving since Banca Monte dei Paschi di Siena opened its doors in 1472. Its leveraged business model has proved very scalable over time, but it is now facing new challenges. Firstly, its book to capital ratios, as documented by Berger et al ( 1995 ), have been consistently falling since 1840. This trend continues as competition has increased. In the past decade, the industry has experienced declines in profitability as measured by return on tangible equity. This is partly the result of falling leverage and fee income and partly due to the net interest margin (connected to traditional lending activity). These trends accelerated following the 2008 financial crisis. At the same time, technology has made banks more competitive. Advances in digital technology are changing the very nature of banking. Banks are now distributing services via mobile technology. A prolonged period of very low interest rates is also having an impact. To sustain their profitability, Brei et al. ( 2020 ) note that many banks have increased their emphasis on fee-generating services.

As Fama ( 1980 ) explains, a bank is an intermediary. The Internet is, however, changing the way financial service providers conduct their role. It is fundamentally changing the nature of the banking. This in turn is changing the nature of banking services, and the way those services are delivered. As a consequence, in order to compete in the changing digital landscape, banks have to adapt. The banks of the future, both incumbents and challengers, need to address liquidity transformation, data, trust, competition, and the digitalization of financial services. Against this backdrop, incumbent banks are focused on reinventing themselves. The challenger banks are, however, starting with a blank canvas. The research questions that these dynamics pose need to be investigated within the context of the theory of banking, hence the need to revise the existing analytical framework.

Banks perform payment and transfer functions for an economy. The Internet can now facilitate and even perform these functions. It is changing the way that transactions are recorded on ledgers and is facilitating both public and private digital currencies. In the past, banks operated in a world of information asymmetry between themselves and their borrowers (clients), but this is changing. This differential gave one bank an advantage over another due to its knowledge about its clients. The digital transformation that financial technology brings reduces this advantage, as this information can be digitally analyzed.

Even the nature of deposits is being transformed. Banks in the future will have to accept deposits and process transactions made in digital form, either Central Bank Digital Currencies (CBDC) or cryptocurrencies. This presents a number of issues: (1) it changes the way financial services will be delivered, (2) it requires a discussion on resilience, security and competition in payments, (3) it provides a building block for better cross border money transfers and (4) it raises the question of private and public issuance of money. Braggion et al ( 2018 ) consider whether these represent a threat to financial stability.

The academic study of banking began with Edgeworth ( 1888 ). He postulated that it is based on probability. In this respect, the nature of the business model depends on the probability that a bank will not be called upon to meet all its liabilities at the same time. This allows banks to lend more than they have in deposits. Because of the resultant mismatch between long term assets and short-term liabilities, a bank’s capital structure is very sensitive to liquidity trade-offs. This is explained by Diamond and Rajan ( 2000 ). They explain that this makes a bank a’relationship lender’. In effect, they suggest a bank is an intermediary that has borrowed from other investors.

Diamond and Rajan ( 2000 ) argue a lender can negotiate repayment obligations and that a bank benefits from its knowledge of the customer. As shall be shown, the new generation of digital challenger banks do not have the same tradeoffs or knowledge of the customer. They operate more like a broker providing a platform for banking services. This suggests that there will be more than one type of bank in the future and several different payment protocols. It also suggests that banks will have to data mine customer information to improve their understanding of a client’s financial needs.

The key focus of Diamond and Rajan ( 2000 ), however, was to position a traditional bank is an intermediary. Gurley and Shaw ( 1956 ) describe how the customer relationship means a bank can borrow funds by way of deposits (liabilities) and subsequently use them to lend or invest (assets). In facilitating this mediation, they provide a service whereby they store money and provide a mechanism to transmit money. With improvements in financial technology, however, money can be stored digitally, lenders and investors can source funds directly over the internet, and money transfer can be done digitally.

A review of financial technology and banking literature is provided by Thakor ( 2020 ). He highlights that financial service companies are now being provided by non-deposit taking contenders. This paper addresses one of the four research questions raised by his review, namely how theories of financial intermediation can be modified to accommodate banks, shadow banks, and non-intermediated solutions.

To be a bank, an entity must be authorized to accept retail deposits. A challenger bank is, therefore, still a bank in the traditional sense. It does not, however, have the costs of a branch network. A peer-to-peer lender, meanwhile, does not have a deposit base and therefore acts more like a broker. This leads to the issue that this paper addresses, namely how the banks of the future will conduct their intermediation.

In order to understand what the bank of the future will look like, it is necessary to understand the nature of the aforementioned intermediation, and the way it is changing. In this respect, there are two key types of intermediation. These are (1) quantitative asset transformation and, (2) brokerage. The latter is a common model adopted by challenger banks. Figure  1 depicts how these two types of financial intermediation match savers with borrowers. To avoid nuanced distinction between these two types of intermediation, it is common to classify banks by the services they perform. These can be grouped as either private, investment, or commercial banking. The service sub-groupings include payments, settlements, fund management, trading, treasury management, brokerage, and other agency services.

How banks act as intermediaries between lenders and borrowers. This function call also be conducted by intermediaries as brokers, for example by shadow banks. Disintermediation occurs over the internet where peer-to-peer lenders match savers to lenders

Financial technology has the ability to disintermediate the banking sector. The competitive pressures this results in will shape the banks of the future. The channels that will facilitate this are shown in Fig.  2 , namely the Internet and/or mobile devices. Challengers can participate in this by, (1) directly matching borrows with savers over the Internet and, (2) distributing white labels products. The later enables banking as a service and avoids the aforementioned liquidity mismatch.

The strategic options banks have to match lenders with borrowers. The traditional and challenger banks are in the same space, competing for business. The distributed banks use the traditional and challenger banks to white label banking services. These banks compete with payment platforms on social media. The Internet heralds an era of banking as a service

There are also physical changes that are being made in the delivery of services. Bricks and mortar branches are in decline. Mobile banking, or m-banking as Liu et al ( 2020 ) describe it, is an increasingly important distribution channel. Robotics are increasingly being used to automate customer interaction. As explained by Vishnu et al ( 2017 ), these improve efficiency and the quality of execution. They allow for increased oversight and can be built on legacy systems as well as from a blank canvas. Application programming interfaces (APIs) are bringing the same type of functionality to m-banking. They can be used to authorize third party use of banking data. How banks evolve over time is important because, according to the OECD, the activity in the financial sector represents between 20 and 30 percent of developed countries Gross Domestic Product.

In summary, financial technology has evolved to a level where online banks and banking as a service are challenging incumbents and the nature of banking mediation. Banking is rapidly transforming because of changes in such technology. At the same time, the solving of the double spending problem, whereby digital money can be cryptographically protected, has led to the possibility that paper money will become redundant at some point in the future. A theoretical framework is required to understand this evolving landscape. This is discussed next.

The theory of the banking firm: a revision

In financial theory, as eloquently explained by Fama ( 1980 ), banking provides an accounting system for transactions and a portfolio system for the storage of assets. That will not change for the banks of the future. Fama ( 1980 ) explains that their activities, in an unregulated state, fulfil the Modigliani–Miller ( 1959 ) theorem of the irrelevance of the financing decision. In practice, traditional banks compete for deposits through the interest rate they offer. This makes the transactional element dependent on the resulting debits and credits that they process, essentially making banks into bookkeeping entities fulfilling the intermediation function. Since this is done in response to competitive forces, the general equilibrium is a passive one. As such, the banking business model is vulnerable to disruption, particularly by innovation in financial technology.

A bank is an idiosyncratic corporate entity due to its ability to generate credit by leveraging its balance sheet. That balance sheet has assets on one side and liabilities on the other, like any corporate entity. The assets consist of cash, lending, financial and fixed assets. On the other side of the balance sheet are its liabilities, deposits, and debt. In this respect, a bank’s equity and its liabilities are its source of funds, and its assets are its use of funds. This is explained by Klein ( 1971 ), who notes that a bank’s equity W , borrowed funds and its deposits B is equal to its total funds F . This is the same for incumbents and challengers. This can be depicted algebraically if we let incumbents be represented by Φ and challengers represented by Γ:

Klein ( 1971 ) further explains that a bank’s equity is therefore made up of its share capital and unimpaired reserves. The latter are held by a bank to protect the bank’s deposit clients. This part is also mandated by regulation, so as to protect customers and indeed the entire banking system from systemic failure. These protective measures include other prudential requirements to hold cash reserves or other liquid assets. As shall be shown, banking services can be performed over the Internet without these protections. Banking as a service, as this phenomenon known, is expected to increase in the future. This will change the nature of the protection available to clients. It will change the way banks transform assets, explained next.

A bank’s deposits are said to be a function of the proportion of total funds obtained through the issuance of the ith deposit type and its total funds F , represented by α i . Where deposits, represented by Bs , are made in the form of Bs (i  =  1 *s n) , they generate a rate of interest. It follows that Si Bs  =  B . As such,

Therefor it can be said that,

The importance of Eq. 3 is that the balance sheet can be leveraged by the issuance of loans. It should be noted, however, that not all loans are returned to the bank in whole or part. Non-performing loans reduce the asset side of a bank’s balance sheet and act as a constraint on capital, and therefore new lending. Clearly, this is not the case with banking as a service. In that model, loans are brokered. That said, with the traditional model, an advantage of financial technology is that it facilitates the data mining of clients’ accounts. Lending can therefore be more targeted to borrowers that are more likely to repay, thereby reducing non-performing loans. Pari passu, the incumbent bank of the future will therefore have a higher risk-adjusted return on capital. In practice, however, banking as a service will bring greater competition from challengers and possible further erosion of margins. Alternatively, some banks will proactively engage in partnerships and acquisitions to maintain their customer base and address the competition.

A bank must have reserves to meet the demand of customers demanding their deposits back. The amount of these reserves is a key function of banking regulation. The Basel Committee on Banking Supervision mandates a requirement to hold various tiers of capital, so that banks have sufficient reserves to protect depositors. The Committee also imposes a framework for mitigating excessive liquidity risk and maturity transformation, through a set Liquidity Coverage Ratio and Net Stable Funding Ratio.

Recent revisions of theory, because of financial technology advances, have altered our understanding of banking intermediation. This will impact the competitive landscape and therefor shape the nature of the bank of the future. In this respect, the threat to incumbent banks comes from peer-to-peer Internet lending platforms. These perform the brokerage function of financial intermediation without the use of the aforementioned banking balance sheet. Unlike regulated deposit takers, such lending platforms do not create assets and do not perform risk and asset transformation. That said, they are reliant on investors who do not always behave in a counter cyclical way.

Financial technology in banking is not new. It has been used to facilitate electronic markets since the 1980’s. Thakor ( 2020 ) refers to three waves of application of financial innovation in banking. The advent of institutional futures markets and the changing nature of financial contracts fundamentally changed the role of banks. In response to this, academics extended the concept of a bank into an entity that either fulfills the aforementioned functions of a broker or a qualitative asset transformer. In this respect, they connect the providers and users of capital without changing the nature of the transformation of the various claims to that capital. This transformation can be in the form risk transfer or the application of leverage. The nature of trading of financial assets, however, is changing. Price discovery can now be done over the Internet and that is moving liquidity from central marketplaces (like the stock exchange) to decentralized ones.

Alongside these trends, in considering what the bank of the future will look like, it is necessary to understand the unregulated lending market that competes with traditional banks. In this part of the lending market, there has been a rise in shadow banks. The literature on these entities is covered by Adrian and Ashcraft ( 2016 ). Shadow banks have taken substantial market share from the traditional banks. They fulfil the brokerage function of banks, but regulators have only partial oversight of their risk transformation or leverage. The rise of shadow banks has been facilitated by financial technology and the originate to distribute model documented by Bord and Santos ( 2012 ). They use alternative trading systems that function as electronic communication networks. These facilitate dark pools of liquidity whereby buyers and sellers of bonds and securities trade off-exchange. Since the credit crisis of 2008, total broker dealer assets have diverged from banking assets. This illustrates the changed lending environment.

In the disintermediated market, banking as a service providers must rely on their equity and what access to funding they can attract from their online network. Without this they are unable to drive lending growth. To explain this, let I represent the online network. Extending Klein ( 1971 ), further let Ψ represent banking as a service and their total funds by F . This state is depicted as,

Theoretically, it can be shown that,

Shadow banks, and those disintermediators who bypass the banking system, have an advantage in a world where technology is ubiquitous. This becomes more apparent when costs are considered. Buchak et al. ( 2018 ) point out that shadow banks finance their originations almost entirely through securitization and what they term the originate to distribute business model. Diversifying risk in this way is good for individual banks, as banking risks can be transferred away from traditional banking balance sheets to institutional balance sheets. That said, the rise of securitization has introduced systemic risk into the banking sector.

Thus, we can see that the nature of banking capital is changing and at the same time technology is replacing labor. Let A denote the number of transactions per account at a period in time, and C denote the total cost per account per time period of providing the services of the payment mechanism. Klein ( 1971 ) points out that, if capital and labor are assumed to be part of the traditional banking model, it can be observed that,

It can therefore be observed that the total service charge per account at a period in time, represented by S, has a linear and proportional relationship to bank account activity. This is another variable that financial technology can impact. According to Klein ( 1971 ) this can be summed up in the following way,

where d is the basic bank decision variable, the service charge per transaction. Once again, in an automated and digital environment, financial technology greatly reduces d for the challenger banks. Swankie and Broby ( 2019 ) examine the impact of Artificial Intelligence on the evaluation of banking risk and conclude that it improves such variables.

Meanwhile, the traditional banking model can be expressed as a product of the number of accounts, M , and the average size of an account, N . This suggests a banks implicit yield is it rate of interest on deposits adjusted by its operating loss in each time period. This yield is generated by payment and loan services. Let R 1 depict this. These can be expressed as a fraction of total demand deposits. This is depicted by Klein ( 1971 ), if one assumes activity per account is constant, as,

As a result, whether a bank is structured with traditional labor overheads or built digitally, is extremely relevant to its profitability. The capital and labor of tradition banks, depicted as Φ i , is greater than online networks, depicted as I i . As such, the later have an advantage. This can be shown as,

What Klein (1972) failed to highlight is that the banking inherently involves leverage. Diamond and Dybving (1983) show that leverage makes bank susceptible to run on their liquidity. The literature divides these between adverse shock events, as explained by Bernanke et al ( 1996 ) or moral hazard events as explained by Demirgu¨¸c-Kunt and Detragiache ( 2002 ). This leverage builds on the balance sheet mismatch of short-term assets with long term liabilities. As such, capital and liquidity are intrinsically linked to viability and solvency.

The way capital and liquidity are managed is through credit and default management. This is done at a bank level and a supervisory level. The Basel Committee on Banking Supervision applies capital and leverage ratios, and central banks manage interest rates and other counter-cyclical measures. The various iterations of the prudential regulation of banks have moved the microeconomic theory of banking from the modeling of risk to the modeling of imperfect information. As mentioned, shadow and disintermediated services do not fall under this form or prudential regulation.

The relationship between leverage and insolvency risk crucially depends on the degree of banks total funds F and their liability structure L . In this respect, the liability structure of traditional banks is also greater than online networks which do not have the same level of available funds, depicted as,

Diamond and Dybvig ( 1983 ) observe that this liability structure is intimately tied to a traditional bank’s assets. In this respect, a bank’s ability to finance its lending at low cost and its ability to achieve repayment are key to its avoidance of insolvency. Online networks and/or brokers do not have to finance their lending, simply source it. Similarly, as brokers they do not face capital loss in the event of a default. This disintermediates the bank through the use of a peer-to-peer environment. These lenders and borrowers are introduced in digital way over the internet. Regulators have taken notice and the digital broker advantage might not last forever. As a result, the future may well see greater cooperation between these competing parties. This also because banks have valuable operational experience compared to new entrants.

It should also be observed that bank lending is either secured or unsecured. Interest on an unsecured loan is typically higher than the interest on a secured loan. In this respect, incumbent banks have an advantage as their closeness to the customer allows them to better understand the security of the assets. Berger et al ( 2005 ) further differentiate lending into transaction lending, relationship lending and credit scoring.

The evolution of the business model in a digital world

As has been demonstrated, the bank of the future in its various manifestations will be a consequence of the evolution of the current banking business model. There has been considerable scholarly investigation into the uniqueness of this business model, but less so on its changing nature. Song and Thakor ( 2010 ) are helpful in this respect and suggest that there are three aspects to this evolution, namely competition, complementary and co-evolution. Although liquidity transformation is evolving, it remains central to a bank’s role.

All the dynamics mentioned are relevant to the economy. There is considerable evidence, as outlined by Levine ( 2001 ), that market liberalization has a causal impact on economic growth. The impact of technology on productivity should prove positive and enhance the functioning of the domestic financial system. Indeed, market liberalization has already reshaped banking by increasing competition. New fee based ancillary financial services have become widespread, as has the proprietorial use of balance sheets. Risk has been securitized and even packaged into trade-able products.

Challenger banks are developing in a complementary way with the incumbents. The latter have an advantage over new entrants because they have information on their customers. The liquidity insurance model, proposed by Diamond and Dybvig ( 1983 ), explains how such banks have informational advantages over exchange markets. That said, financial technology changes these dynamics. It if facilitating the processing of financial data by third parties, explained in greater detail in the section on Open Banking.

At the same time, financial technology is facilitating banking as a service. This is where financial services are delivered by a broker over the Internet without resort to the balance sheet. This includes roboadvisory asset management, peer to peer lending, and crowd funding. Its growth will be facilitated by Open Banking as it becomes more geographically adopted. Figure  3 illustrates how these business models are disintermediating the traditional banking role and matching burrowers and savers.

The traditional view of banks ecosystem between savers and borrowers, atop the Internet which is matching savers and borrowers directly in a peer-to-peer way. The Klein ( 1971 ) theory of the banking firm does not incorporate the mirrored dynamics, and as such needs to be extended to reflect the digital innovation that impacts both borrowers and severs in a peer-to-peer environment

Meanwhile, the banking sector is co-evolving alongside a shadow banking phenomenon. Lenders and borrowers are interacting, but outside of the banking sector. This is a concern for central banks and banking regulators, as the lending is taking place in an unregulated environment. Shadow banking has grown because of financial technology, market liberalization and excess liquidity in the asset management ecosystem. Pozsar and Singh ( 2011 ) detail the non-bank/bank intersection of shadow banking. They point out that shadow banking results in reverse maturity transformation. Incumbent banks have blurred the distinction between their use of traditional (M2) liabilities and market-based shadow banking (non-M2) liabilities. This impacts the inter-generational transfers that enable a bank to achieve interest rate smoothing.

Securitization has transformed the risk in the banking sector, transferring it to asset management institutions. These include structured investment vehicles, securities lenders, asset backed commercial paper investors, credit focused hedge and money market funds. This in turn has led to greater systemic risk, the result of the nature of the non-traded liabilities of securitized pooling arrangements. This increased risk manifested itself in the 2008 credit crisis.

Commercial pressures are also shaping the banking industry. The drive for cost efficiency has made incumbent banks address their personally costs. Bank branches have been closed as technology has evolved. Branches make it easier to withdraw or transfer deposits and challenger banks are not as easily able to attract new deposits. The banking sector is therefore looking for new point of customer contact, such as supermarkets, post offices and social media platforms. These structural issues are occurring at the same time as the retail high street is also evolving. Banks have had an aggressive roll out of automated telling machines and a reduction in branches and headcount. Online digital transactions have now become the norm in most developed countries.

The financing of banks is also evolving. Traditional banks have tended to fund illiquid assets with short term and unstable liquid liabilities. This is one of the key contributors to the rise to the credit crisis of 2008. The provision of liquidity as a last resort is central to the asset transformation process. In this respect, the banking sector experienced a shock in 2008 in what is termed the credit crisis. The aforementioned liquidity mismatch resulted in the system not being able to absorb all the risks associated with subprime lending. Central banks had to resort to quantitative easing as a result of the failure of overnight funding mechanisms. The image of the entire banking sector was tarnished, and the banks of the future will have to address this.

The future must learn from the mistakes of the past. The structural weakness of the banking business model cannot be solved. That said, the latest Basel rules introduce further risk mitigation, improved leverage ratios and increased levels of capital reserve. Another lesson of the credit crisis was that there should be greater emphasis on risk culture, governance, and oversight. The independence and performance of the board, the experience and the skill set of senior management are now a greater focus of regulators. Internal controls and data analysis are increasingly more robust and efficient, with a greater focus on a banks stable funding ratio.

Meanwhile, the very nature of money is changing. A digital wallet for crypto-currencies fulfills much the same storage and transmission functions of a bank; and crypto-currencies are increasing being used for payment. Meanwhile, in Sweden, stores have the right to refuse cash and the majority of transactions are card based. This move to credit and debit cards, and the solving of the double spending problem, whereby digital money can be crypto-graphically protected, has led to the possibility that paper money could be replaced at some point in the future. Whether this might be by replacement by a CBDC, or decentralized digital offering, is of secondary importance to the requirement of banks to adapt. Whether accommodating crytpo-currencies or CBDC’s, Kou et al. ( 2021 ) recommend that banks keep focused on alternative payment and money transferring technologies.

Central banks also have to adapt. To limit disintermediation, they have to ensure that the economic design of their sponsored digital currencies focus on access for banks, interest payment relative to bank policy rate, banking holding limits and convertibility with bank deposits. All these developments have implications for banks, particularly in respect of funding, the secure storage of deposits and how digital currency interacts with traditional fiat money.

Open banking

Against the backdrop of all these trends and changes, a new dynamic is shaping the future of the banking sector. This is termed Open Banking, already briefly mentioned. This new way of handling banking data protocols introduces a secure way to give financial service companies consensual access to a bank’s customer financial information. Figure  4 illustrates how this works. Although a fairly simple concept, the implications are important for the banking industry. Essentially, a bank customer gives a regulated API permission to securely access his/her banking website. That is then used by a banking as a service entity to make direct payments and/or download financial data in order to provide a solution. It heralds an era of customer centric banking.

How Open Banking operates. The customer generates data by using his bank account. A third party provider is authorized to access that data through an API request. The bank confirms digitally that the customer has authorized the exchange of data and then fulfills the request

Open Banking was a response to the documented inertia around individual’s willingness to change bank accounts. Following the Retail Banking Review in the UK, this was addressed by lawmakers through the European Union’s Payment Services Directive II. The legislation was designed to make it easier to change banks by allowing customers to delegate authority to transfer their financial data to other parties. As a result of this, a whole host of data centric applications were conceived. Open banking adds further momentum to reshaping the future of banking.

Open Banking has a number of quite revolutionary implications. It was started so customers could change banks easily, but it resulted in some secondary considerations which are going to change the future of banking itself. It gives a clear view of bank financing. It allows aggregation of finances in one place. It also allows can give access to attractive offerings by allowing price comparisons. Open Banking API’s build a secure online financial marketplace based on data. They also allow access to a larger market in a faster way but the third-party providers for the new entrants. Open Banking allows developers to build single solutions on an API addressing very specific problems, like for example, a cash flow based credit rating.

Romānova et al. ( 2018 ) undertook a questionnaire on the Payment Services Directive II. The results suggest that Open Banking will promote competitiveness, innovation, and new product development. The initiative is associated with low costs and customer satisfaction, but that some concerns about security, privacy and risk are present. These can be mitigated, to some extent, by secure protocols and layered permission access.

Discussion: strategic options

Faced with these disruptive trends, there are four strategic options for market participants to con- sider. There are (1) a defensive customer retention strategy for incumbents, (2) an aggressive customer acquisition strategy for challenger banks (3) a banking as a service strategy for new entrants, and (4) a payments strategy for social media platforms.

Each of these strategies has to be conducted in a competitive marketplace for money demand by potential customers. Figure  5 illustrates where the first three strategies lie on the tradeoff between money demand and interest rates. The payment strategy can’t be modeled based on the supply of money. In the figure, the market settles at a rate L 2 . The incumbent banks have the capacity to meet the largest supply of these loans. The challenger banks have a constrained function but due to a lower cost base can gain excess rent through higher rates of interest. The peer-to-peer bank as a service brokers must settle for the market rate and a constrained supply offering.

The money demand M by lenders on the y axis. Interest rates on the y axis are labeled as r I and r II . The challenger banks are represented by the line labeled Γ. They have a price and technology advantage and so can lend at higher interest rates. The brokers are represented by the line labeled Ω. They are price takers, accepting the interest rate determined by the market. The same is true for the incumbents, represented by the line labeled Φ but they have a greater market share due to their customer relationships. Note that payments strategy for social media platforms is not shown on this figure as it is not affected by interest rates

Figure  5 illustrates that having a niche strategy is not counterproductive. Liu et al ( 2020 ) found that banks performing niche activities exhibit higher profitability and have lower risk. The syndication market now means that a bank making a loan does not have to be the entity that services it. This means banks in the future can better shape their risk profile and manage their lending books accordingly.

An interesting question for central banks is what the future Deposit Supply function will look like. If all three forms: open banking, traditional banking and challenger banks develop together, will the bank of the future have the same Deposit Supply function? The Klein ( 1971 ) general formulation assumes that deposits are increasing functions of implicit and explicit yields. As such, the very nature of central bank directed monetary policy may have to be revisited, as alluded to in the earlier discussion on digital money.

The client retention strategy (incumbents)

The competitive pressures suggest that incumbent banks need to focus on customer retention. Reichheld and Kenny ( 1990 ) found that the best way to do this was to focus on the retention of branch deposit customers. Obviously, another way is to provide a unique digital experience that matches the challengers.

Incumbent banks have a competitive advantage based on the information they have about their customers. Allen ( 1990 ) argues that where risk aversion is observable, information markets are viable. In other words, both bank and customer benefit from this. The strategic issue for them, therefore, becomes the retention of these customers when faced with greater competition.

Open Banking changes the dynamics of the banking information advantage. Borgogno and Colangelo ( 2020 ) suggest that the access to account (XS2A) rule that it introduced will increase competition and reduce information asymmetry. XS2A requires banks to grant access to bank account data to authorized third payment service providers.

The incumbent banks have a high-cost base and legacy IT systems. This makes it harder for them to migrate to a digital world. There are, however, also benefits from financial technology for the incumbents. These include reduced cost and greater efficiency. Financial technology can also now support platforms that allow incumbent banks to sell NPL’s. These platforms do not require the ownership of assets, they act as consolidators. The use of technology to monitor the transactions make the processing cost efficient. The unique selling point of such platforms is their centralized point of contact which results in a reduction in information asymmetry.

Incumbent banks must adapt a number of areas they got to adapt in terms of their liquidity transformation. They have to adapt the way they handle data. They must get customers to trust them in a digital world and the way that they trust them in a bricks and mortar world. It is no coincidence. When you go into a bank branch that is a great big solid building great big facade and so forth that is done deliberately so that you trust that bank with your deposit.

The risk of having rising non-performing loans needs to be managed, so customer retention should be selective. One of the puzzles in banking is why customers are regularly denied credit, rather than simply being charged a higher price for it. This credit rationing is often alleviated by collateral, but finance theory suggests value is based on the discounted sum of future cash flows. As such, it is conceivable that the bank of the future will use financial technology to provide innovative credit allocation solutions. That said, the dual risks of moral hazard and information asymmetries from the adoption of such solutions must be addressed.

Customer retention is especially important as bank competition is intensifying, as is the digitalization of financial services. Customer retention requires innovation, and that innovation has been moving at a very fast rate. Until now, banks have traditionally been hesitant about technology. More recently, mergers and acquisitions have increased quite substantially, initiated by a need to address actual or perceived weaknesses in financial technology.

The client acquisition strategy (challengers)

As intermediaries, the challenger banks are the same as incumbent banks, but designed from the outset to be digital. This gives them a cost and efficiency advantage. Anagnostopoulos ( 2018 ) suggests that the difference between challenger and traditional banks is that the former address its customers problems more directly. The challenge for such banks is customer acquisition.

Open Banking is a major advantage to challenger banks as it facilitates the changing of accounts. There is widespread dissatisfaction with many incumbent banks. Open Banking makes it easier to change accounts and also easier to get a transaction history on the client.

Customer acquisition can be improved by building trust in a brand. Historically, a bank was physically built in a very robust manner, hence the heavy architecture and grand banking halls. This was done deliberately to engender a sense of confidence in the deposit taking institution. Pure internet banks are not able to do this. As such, they must employ different strategies to convey stability. To do this, some communicate their sustainability credentials, whilst others use generational values-based advertising. Customer acquisition in a banking context is traditionally done by offering more attractive rates of interest. This is illustrated in Fig.  5 by the intersect of traditional banks with the market rate of interest, depicted where the line Γ crosses L 2 . As a result of the relationship with banking yield, teaser rates and introductory rates are common. A customer acquisition strategy has risks, as consumers with good credit can game different challenger banks by frequently changing accounts.

Most customer acquisition, however, is done based on superior service offering. The functionality of challenger banking accounts is often superior to incumbents, largely because the latter are built on legacy databases that have inter-operability issues. Having an open platform of services is a popular customer acquisition technique. The unrestricted provision of third-party products is viewed more favorably than a restricted range of products.

The banking as a service strategy (new entrants)

Banking from a customer’s perspective is the provision of a service. Customers don’t care about the maturity transformation of banking balance sheets. Banking as a service can be performed without recourse to these balance sheets. Banking products are brokered, mostly by new entrants, to individuals as services that can be subscribed to or paid on a fee basis.

There are a number banking as a service solutions including pre-paid and credit cards, lending and leasing. The banking as a service brokers are effectively those that are aggregating services from others using open banking to enable banking as a service.

The rise of banking as a service needs to be understood as these compete directly with traditional banks. As explained, some of these do this through peer-to-peer lending over the internet, others by matching borrows and sellers, conducting mediation as a loan broker. Such entities do not transform assets and do not have banking licenses. They do not have a branch network and often don not have access to deposits. This means that they have no insurance protection and can be subject to interest rate controls.

The new genre of financial technology, banking as a service provider, conduct financial services transformation without access to central bank liquidity. In a distributed digital asset world, the assets are stored on a distributed ledger rather than a traditional banking ledger. Financial technology has automated credit evaluation, savings, investments, insurance, trading, banking payments and risk management. These banking as a service offering are only as secure as the technology on which they are built.

The social media payment strategy (disintermediators and disruptors)

An intermediation bank is a conceptual idea, one created solely on a social networking site. Social media has developed a market for online goods and services. Williams ( 2018 ) estimates that there are 2.46 billion social media users. These all make and receive payments of some kind. They demand security and functionality. Importantly, they have often more clients than most banks. As such, a strategy to monetize the payments infrastructure makes sense.

All social media platforms are rich repositories of data. Such platforms are used to buy and sell things and that requires payments. Some platforms are considering evolving their own digital payment, cutting out the banks as middlemen. These include Facebook’s Diem (formerly Libra), a digital currency, and similar developments at some of the biggest technology companies. The risk with social media payment platform is that there is systemic counter-party protection. Regulators need to address this. One way to do this would be to extend payment service insurance to such platforms.

Social media as a platform moves the payment relationship from a transaction to a customer experience. The ability to use consumer desires in combination with financial data has the potential to deliver a number of new revenue opportunities. These will compete directly with the banks of the future. This will have implications for (1) the money supply, (2) the market share of traditional banks and, (3) the services that payment providers offer.

Further research

Several recommendations for research derive from both the impact of disintermediation and the four proposed strategies that will shape banking in the future. The recommendations and suggestions are based on the mentioned papers and the conclusions drawn from them.

As discussed, the nature of intermediation is changing, and this has implications for the pricing of risk. The role of interest rates in banking will have to be further reviewed. In a decentralized world based on crypto currencies the central banks do not have the same control over the money supply, This suggest the quantity theory of money and the liquidity preference theory need to be revisited. As explained, the Internet reduces much of the friction costs of intermediation. Researchers should ask how this will impact maturity transformation. It is also fair to ask whether at some point in the future there will just be one big bank. This question has already been addressed in the literature but the Internet facilities the possibility. Diamond ( 1984 ) and Ramakrishnan and Thakor ( 1984 ) suggested the answer was due to diversification and its impact on reducing monitoring costs.

Attention should be given by academics to the changing nature of banking risk. How should regulators, for example, address the moral hazard posed by challenger banks with weak balance sheets? What about deposit insurance? Should it be priced to include unregulated entities? Also, what criteria do borrowers use to choose non-banking intermediaries? The changing risk environment also poses two interesting practical questions. What will an online bank run look like, and how can it be averted? How can you establish trust in digital services?

There are also research questions related to the nature of competition. What, for example, will be the nature of cross border competition in a decentralized world? Is the credit rationing that generates competition a static or dynamic phenomena online? What is the value of combining consumer utility with banking services?

Financial intermediaries, like banks, thrive in a world of deficits and surpluses supported by information asymmetries and disconnectedness. The connectivity of the internet changes this dynamic. In this respect, the view of Schumpeter ( 1911 ) on the role of financial intermediaries needs revisiting. Lenders and borrows can be connected peer to peer via the internet.

All the dynamics mentioned change the nature of moral hazard. This needs further investigation. There has been much scholarly research on the intrinsic riskiness of the mismatch between banking assets and liabilities. This mismatch not only results in potential insolvency for a single bank but potentially for the whole system. There has, for example, been much debate on the whether a bank can be too big to fail. As a result of the riskiness of the banking model, the banks of the future will be just a liable to fail as the banks of the past.

This paper presented a revision of the theory of banking in a digital world. In this respect, it built on the work of Klein ( 1971 ). It provided an overview of the changing nature of banking intermediation, a result of the Internet and new digital business models. It presented the traditional academic view of banking and how it is evolving. It showed how this is adapted to explain digital driven disintermediation.

It was shown that the banking industry is facing several documented challenges. Risk is being taken of balance sheet, securitized, and brokered. Financial technology is digitalizing service delivery. At the same time, the very nature of intermediation is being changed due to digital currency. It is argued that the bank of the future not only has to face these competitive issues, but that technology will enhance the delivery of banking services and reduce the cost of their delivery.

The paper further presented the importance of the Open Banking revolution and how that facilitates banking as a service. Open Banking is increasing client churn and driving banking as a service. That in turn is changing the way products are delivered.

Four strategies were proposed to navigate the evolving competitive landscape. These are for incumbents to address customer retention; for challengers to peruse a low-cost digital experience; for niche players to provide banking as a service; and for social media platforms to develop payment platforms. In all these scenarios, the banks of the future will have to have digital strategies for both payments and service delivery.

It was shown that both incumbents and challengers are dependent on capital availability and borrowers credit concerns. Nothing has changed in that respect. The risks remain credit and default risk. What is clear, however, is the bank has become intrinsically linked with technology. The Internet is changing the nature of mediation. It is allowing peer to peer matching of borrowers and savers. It is facilitating new payment protocols and digital currencies. Banks need to evolve and adapt to accommodate these. Most of these questions are empirical in nature. The aim of this paper, however, was to demonstrate that an understanding of the banking model is a prerequisite to understanding how to address these and how to develop hypotheses connected with them.

In conclusion, financial technology is changing the future of banking and the way banks intermediate. It is facilitating digital money and the online transmission of financial assets. It is making banks more customer enteric and more competitive. Scholarly investigation into banking has to adapt. That said, whatever the future, trust will remain at the core of banking. Similarly, deposits and lending will continue to attract regulatory oversight.

Availability of data and materials

Diagrams are my own and the code to reproduce them is available in the supplied Latex files.

Adrian T, Ashcraft AB (2016) Shadow banking: a review of the literature. In: Banking crises. Palgrave Macmillan, London, pp 282–315

Allen F (1990) The market for information and the origin of financial intermediation. J Financ Intermed 1(1):3–30

Article   Google Scholar  

Anagnostopoulos I (2018) Fintech and regtech: impact on regulators and banks. J Econ Bus 100:7–25

Berger AN, Herring RJ, Szegö GP (1995) The role of capital in financial institutions. J Bank Finance 19(3–4):393–430

Berger AN, Miller NH, Petersen MA, Rajan RG, Stein JC (2005) Does function follow organizational form? Evidence from the lending practices of large and small banks. J Financ Econ 76(2):237–269

Bernanke B, Gertler M, Gilchrist S (1996) The financial accelerator and the flight to quality. The review of economics and statistics, pp1–15

Bord V, Santos JC (2012) The rise of the originate-to-distribute model and the role of banks in financial intermediation. Federal Reserve Bank N Y Econ Policy Rev 18(2):21–34

Google Scholar  

Borgogno O, Colangelo G (2020) Data, innovation and competition in finance: the case of the access to account rule. Eur Bus Law Rev 31(4)

Braggion F, Manconi A, Zhu H (2018) Is Fintech a threat to financial stability? Evidence from peer-to-Peer lending in China, November 10

Brei M, Borio C, Gambacorta L (2020) Bank intermediation activity in a low-interest-rate environment. Econ Notes 49(2):12164

Buchak G, Matvos G, Piskorski T, Seru A (2018) Fintech, regulatory arbitrage, and the rise of shadow banks. J Financ Econ 130(3):453–483

Demirgüç-Kunt A, Detragiache E (2002) Does deposit insurance increase banking system stability? An empirical investigation. J Monet Econ 49(7):1373–1406

Diamond DW (1984) Financial intermediation and delegated monitoring. Rev Econ Stud 51(3):393–414

Diamond DW, Dybvig PH (1983) Bank runs, deposit insurance, and liquidity. J Polit Econ 91(3):401–419

Diamond DW, Rajan RG (2000) A theory of bank capital. J Finance 55(6):2431–2465

Edgeworth FY (1888) The mathematical theory of banking. J Roy Stat Soc 51(1):113–127

Fama EF (1980) Banking in the theory of finance. J Monet Econ 6(1):39–57

Gurley JG, Shaw ES (1956) Financial intermediaries and the saving-investment process. J Finance 11(2):257–276

Klein MA (1971) A theory of the banking firm. J Money Credit Bank 3(2):205–218

Kou G, Akdeniz ÖO, Dinçer H, Yüksel S (2021) Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach. Financ Innov 7(1):1–28

Levine R (2001) International financial liberalization and economic growth. Rev Interna Tional Econ 9(4):688–702

Liu FH, Norden L, Spargoli F (2020) Does uniqueness in banking matter? J Bank Finance 120:105941

Pozsar Z, Singh M (2011) The nonbank-bank nexus and the shadow banking system. IMF working papers, pp 1–18

Ramakrishnan RT, Thakor AV (1984) Information reliability and a theory of financial intermediation. Rev Econ Stud 51(3):415–432

Reichheld FF, Kenny DW (1990) The hidden advantages of customer retention. J Retail Bank 12(4):19–24

Romānova I, Grima S, Spiteri J, Kudinska M (2018) The payment services directive 2 and competitiveness: the perspective of European Fintech companies. Eur Res Stud J 21(2):5–24

Modigliani F, Miller MH (1959) The cost of capital, corporation finance, and the theory of investment: reply. Am Econ Rev 49(4):655–669

Schumpeter J (1911) The theory of economic development. Harvard Econ Stud XLVI

Song F, Thakor AV (2010) Financial system architecture and the co-evolution of banks and capital markets. Econ J 120(547):1021–1055

Swankie GDB, Broby D (2019) Examining the impact of artificial intelligence on the evaluation of banking risk. Centre for Financial Regulation and Innovation, white paper

Thakor AV (2020) Fintech and banking: What do we know? J Financ Intermed 41:100833

Vishnu S, Agochiya V, Palkar R (2017) Data-centered dependencies and opportunities for robotics process automation in banking. J Financ Transf 45(1):68–76

Williams MD (2018) Social commerce and the mobile platform: payment and security perceptions of potential users. Comput Hum Behav 115:105557

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ORIGINAL RESEARCH article

E-banking adoption: an opportunity for customer value co-creation.

• 1 Department of Marketing, University of Castilla-La Mancha, Ciudad Real, Spain
• 2 Faculty of Management and Communication, Universidad Internacional de la Rioja, Logroño, Spain

The development of information and communication technologies offers innovative opportunities to establish business strategies focused on customer value co-creation. This situation is especially notable in the banking industry. e-Banking activities can support competitive advantages. However, the adoption of e-banking is not yet well-established among consumers. In this sense, the technology acceptance model (TAM) is considered essential in studying consumer behavior applied to adopt a particular technology. According to the TAM model, this study analyses the factors which influence bank customers to adopt e-banking to facilitate their banking services and support the process of value co-creation. Consequently, the authors examine five main aspects of the technology adoption model to provide a broad understanding of bank customers’ consumption of e-banking. A partial least squares structural equation modeling (PLS-SEM) analysis is conducted to evaluate proposed relationships between factors and customers’ e-banking adoption.

Introduction

The rapid growth and development of information and communication technologies (ICT) have enabled companies to create value in a digital environment ( Schreieck and Wiesche, 2017 ). Currently, the adoption of innovation in the organization’s strategy is an essential requirement to create value. The term value co-creation has a principal role in easing this innovation. O’Hern and Rindfleisch (2010) conceptualize value co-creation as a collaborative activity, in which consumers actively participate and choose components of a different product or service proposition. Thus, in the digital era, value creation has become the co-creation of value between customers and companies ( Hosseini et al., 2020 ).

Internet and technological development have changed how financial services are offered and used ( Malaquias and Hwang, 2019 ). Banks and many financial institutions suggest alternative innovative electronic channels for maintaining a competitive advantage and satisfying customer expectations. Mobile devices and destock have increasingly become tools that customers implement through e-banking to pay for products and services ( Zhang et al., 2018 ). Therefore, e-banking can adapt to clients’ needs, such as performing banking activities, without physically visit an office or an ATM ( Malaquias and Hwang, 2019 ). For this reason, e-banking has considerable value for many financial organizations and customers ( Baabdullah et al., 2019 ).

The introduction and growth of Internet services, which offer better possibilities of interaction with companies, allow consumers to participate in the development and/or improvement of products/services, resulting in value. Consequently, organizations are concerned about attracting customers who want to contribute their ideas to the collaborative process ( Chepurna and Criado, 2018 ). The banking context is particularly interesting in analyzing the transition toward a value co-creation strategy ( Mostafa, 2020 ). The fierce competition in the banking arena has facilitated e-banking as the most cutting-edge electronic-based and self-service distribution channel ( Malaquias and Hwang, 2019 ). e-Banking is conceptualized as a distribution and communication channel which allows customers to interact with a bank to conduct transactions economically and efficiently, mainly through electronic tools, e.g., tablets or smartphones ( Singh and Srivastava, 2020 ). The use of e-banking offers a wide variety of services for customers, which provide them with value and create a competitive advantage over competitors, such as account checking, bill payment, transferences, or mobile phone text message notifications ( Mostafa, 2020 ). As an example of this incremental service innovations, Bankia is modernizing their communication channels to increase the value offered to customers. Bankia has been recognized as the first Spanish bank with an official verified WhatsApp account to communicate with either current customers or prospects. This action is part of its business strategy “Digital Humanism” as a new way of relating to customers based on a closer, agile, and direct actions ( Bankia, 2020 ).

The massive usage of the Internet and electronic gadgets have captured the attention of researchers to e-banking. Previous studies (e.g., Glavee-Geo et al., 2017 ; Singh and Srivastava, 2020 ) show that previous works have studied the factors that encourage the adoption of e-banking ( Mostafa, 2020 ). However, the adoption rate of e-banking is below the expectation and still in the adoption phase, even though e-banking services offer several outstanding services to users ( Shankar et al., 2020 ). Therefore, this study aims to develop an empirical model based on technology adoption, applied in e-banking to understand the behavior of the users. Specifically, some variables included in the technology acceptance model (TAM) will be examined as factors that stimulate the adoption of e-banking and become an opportunity for customer value co-creation.

For this reason, this research provides a series of contributions that can help identify decisive factors in the use of e-banking and encourage customer value co-creation through interaction with electronic services. In this setting, this study focuses on the following questions: What are the factors that affect a consumer’s use of e-banking? What factors are most important in the consumer’s intention to use e-banking? What type of e-banking is most in-demand, and what strategies around the use of e-banking could the banks and financial institutions follow to increase its use? How can the use of e-banking contribute to customer value co-creation? Through partial least squares structural equation modeling (PLS-SEM) approach and the use of the importance-performance map analysis (IPMA), this research field provides insights and recommendations to help the banking industry adopt and use e-services by consumers to support the process of value co-creation.

To achieve the proposed objective, the study is organized as follows. First, the conceptual framework, the proposed model, and its hypotheses are presented. Then, the methods used and the results of the study are described. Finally, the conclusions and limitations of the study are presented.

Conceptual Framework

Co-creation and the banking market.

The banking industry is a leader in providing consumers with opportunities to access products and services through advanced technology ( Malar et al., 2019 ). The development of ICT has allowed banks to have a relationship with customers, shifting away from physical interaction with a bank branch to interactive and virtual environments ( Martovoy and Santos, 2012 ). Some authors, such as Andreu et al. (2010) , specify the consequences of direct interactions between a company and its customers to achieve value co-creation. Other researchers, such as Payne et al. (2008) , highlight that organizations must adopt a customer relationship approach to support value creation. Co-creation requires companies’ ability to connect with customers and market orientation to be closer to them ( Ind and Coates, 2013 ). Consequently, the company-client relationship must be active, providing interactive experiences and activities guided by decisive practices while taking advantage of customers’ unconscious behavior. In this sense, customers are encouraged to participate in the process and meet their own needs.

Following the study of Grönroos (2011) , consumers ought to perceive usefulness or benefit using self-service and involvement in the process to be motivated. In the banking sector, there is a generalized interest in providing easy and fast services, maintaining the quality of products, and services toward the customer. Furthermore, the advent of new technologies, products, and services encourages new needs and demands by customers ( Hosseini et al., 2020 ). Ease access to information and the differentiation of products and services offered by the Internet creates higher expectations among customers. Consequently, an innovation that appears in a specific part of the work may be effortlessly accessed in other parts of the world and desired by any person ( Mainardes et al., 2017 ). Another feature of electronic services is accessibility to consumers. Some studies indicate that banking services are linked to this new and demanding customer profile. Consequently, the new services provided by banks arise from customers’ needs, characterizing the continuous sharing of ideas and value co-creation in the banking sector ( Oliveira and von Hippel, 2011 ; Akter et al., 2020 ).

Based on the study of Medberg and Heinonen (2014) , direct contact with the company and e-services create new ways of relationship and involvement with customers, positively affecting the company’s financial performance (e.g., decreasing of operating costs, increase on investment return). Furthermore, this way of interacting with customers has boost competitiveness in the banking industry, requiring an agile adaptation from each financial organization. It is proven that, when a bank includes a new or enhanced service to customers, competitors follow this innovation through the launch of the same or improved service. Thus, co-creation characterizes the innovation and betterment of services provided by banks. This fact encourages customers’ active participation in the co-creation practice through several benefits: easer credit approval, lower charges, or commitment to the bank ( Mostafa, 2020 ). Hence, value co-creation should drive to reciprocally favorable outcomes for both consumers and businesses.

Adoption of Technology and e-Services Banking

In recent years, the development of Information Technology and the Internet has brought about changes in the performance of traditional services. Thus, e-banking has changed the conventional practices of banks and financial institutions and has captured the attention of both academics and practitioners ( Wang et al., 2017 ). The adoption of e-banking is considered an innovative distribution channel for financial services due to rapid advances in e-banking applications and intense competence ( Sikdar et al., 2015 ; Yaseen and El Qirem, 2018 ). Thus, understanding the adoption and use of e-banking has become a central research field. The literature indicates that the most relevant strength of the TAM, developed by Davis et al. (1989) , is its generalizability and applicability in different contexts ( Yaseen and El Qirem, 2018 ). This model is specifically indicated to study the intention to adopt specific technologies. Thus, the TAM applies models to study the acceptance and intention to use information system tools such as mobile commerce (e.g., Natarajan et al., 2018 ), m-banking (e.g., Mostafa, 2020 ; Shankar et al., 2020 ) and e-banking ( Yoon and Steege, 2013 ; Salimon et al., 2017 ; Yaseen and El Qirem, 2018 ; Ahmad et al., 2019 ), among others. The original TAM considers perceived usefulness and perceived ease of use has a significant role in the technology acceptance process ( Davis et al., 1989 ). On one side, perceived ease of use is defined as the degree to which a person believes that using a particular system is effortless, both physically and mentally. On the other side, perceived utility is described as the degree to which consumers believe that using a system will increase their performance ( Davis et al., 1989 ; Mostafa, 2020 ). Some previous studies in technology acceptance demonstrate that perceived ease of use has a positive effect, mediated by perceived usefulness on the intention to use technology ( Natarajan et al., 2018 ).

In the context of e-banking, it is observed that perceived usefulness represents one of the critical aspects that explain behavior intention to use e-banking ( Malaquias and Hwang, 2019 ). For example, e-banking provides some unique services that are not available in offline banking, such as access to banking services at any time and from anywhere ( Yoon and Steege, 2013 ; Shankar and Jebarajakirthy, 2019 ). Similarly, previous studies show the influence of perceived ease of using e-banking on perceived usefulness and attitude (e.g., Deb and Lomo-David, 2014 ). Internet and mobile technology should improve convenience for customers, and its ease of use is critical in customer usage. Some authors (e.g., Riquelme and Rios, 2010 ) claim that adopting mobile banking is influenced by consumer’s perceived ease of use due to a complex system when it performs financial transactions. In this sense, the authors highlight that if consumers perceive the performance of a financial transaction as easy through mobile devices, they will have a more favorable attitude toward adopting mobile banking ( Zhang et al., 2018 ). Ahmad et al. (2019) argue that a client’s beliefs about the usability of the website or application affect his or her attitude toward the website or application. These authors state that the ease of use of e-banking systems is a critical factor in their adoption and evaluation by clients. Thus, the relationship between consumers’ attitudes toward the use of technology, an excellent example of this is e-banking, and perceived ease of use is studied (e.g., Zhang et al., 2018 ). Moreover, Mostafa (2020) argues that customers may negatively evaluate using e-banking if they believe e-banking technology is challenging to use and learn. Thus, the following hypotheses are proposed:

H1. Perceived ease of use positively influences on perceived usefulness of e-banking.

H2. Perceived ease of use positively influences on attitude toward using e-banking.

Another dimension included in the TAM model is the perceived usefulness. This concept and its role have been examined in e-banking works (e.g., Yoon and Steege, 2013 ; Salimon et al., 2017 ; Malaquias and Hwang, 2019 ). Perceived usefulness can be defined as a person’s belief about if the use of a specific technology will improve their task performance ( Davis et al., 1989 ; Natarajan et al., 2018 ). Authors such as Yoon and Steege (2013) state that perceived utility is a positive and determining element in e-banking usage. Similarly, this term is the principal factor that impacts consumers’ attitudes toward the use of technology ( Deb and Lomo-David, 2014 ). Consequently, customers will evaluate e-banking usage favorably if they perceive that e-banking has a relative advantage over other alternatives ( Mostafa, 2020 ). Recently, authors such as Ahmad et al. (2019) have highlighted the positive relationship of perceived usefulness with both attitudes toward using e-banking and user intention. According to the previous statements, the following hypotheses are formulated:

H3. Perceived usefulness positively influences on attitude toward using e-banking.

H4. Perceived usefulness positively influences on intention to use e-banking.

The concept of attitude toward the behavior reflects the degree to which an individual assesses a specific behavior as useful or not ( Ajzen, 1991 ). Venkatesh et al. (2003) interpret attitudes toward a specific innovation as results of an individual’s own beliefs about an objective and the evaluations associated with those beliefs. In TAM’s scope, positive attitudes toward innovative technologies have confirmed antecedents of intentions to adopt them ( Davis et al., 1989 ; Schierz et al., 2010 ). The association among attitude and intention to use has been broadly examined in the literature, particularly in the banking literature (e.g., Shaikh and Karjaluoto, 2015 ; Zhang et al., 2018 ; Ahmad et al., 2019 ; Mostafa, 2020 ).

Similarly, past research shows that attitude is an essential determinant of behavioral intention and a relevant antecedent of actual behavior. Consequently, the intention to adopt has been analyzed to understand people’s actual behavior ( Davis et al., 1989 ; Zhang et al., 2018 ). Yaseen and El Qirem (2018) conceptualize behavior intention to adopt e-banking services as a measure of the strength of an individual’s intention to perform a specific behavior. Also, authors such as Ahmad et al. (2019) explain behavioral intention to use e-banking as a precedent to the actual use of e-banking. Based on prior studies, the following hypotheses are proposed:

H5. Attitude toward using e-banking positively influences on intention to use e-banking.

H6. Intention to use e-banking positively influences on e-banking usage.

Based on the above, Figure 1 summarizes the hypotheses of the proposed conceptual model.

Figure 1. Model proposed on the e-banking usage with PLS-SEM.

Materials and Methods

Study design.

To test the proposed hypotheses, the authors carried out a study in Southern Europe’s banking industry. Specifically, the research was conducted in Spain due to the recent increase in e-banking in this country. e-Banking has experienced a growing acceptance in Spain in recent years, with more than 50% of digital banking population users. Some figures indicate that the number of Spain’s e-banking users increased to 28% between 2011 and 2019 ( Statista, 2020a ). Santander Group ranked first with more than 36 million digital customers during 2019, followed by BBVA with 31 million ( Statista, 2020b ).

A convenience sampling method was used to collect the data, taking e-banking users’ opinions as reference. A convenience sampling method was used to collect the data, taking e-banking users’ opinions as reference. Data was collected via an online survey from February to April 2020. Potential respondents in Spain were recruited through a national consumer panel. To measure each of the constructs, a self-administered survey has been used to analyze the e-banking usage of a set of well-known banks located in Spain. The application of PLS-SEM requires a minimum sample size. For this purpose, the statistical power is analyzed using G ∗ Power 3.1.9.7 ( Carranza et al., 2020 ). Thus, the statistical power value for this sample considering a medium effect size ( f 2 = 0.15) is 0.989, higher than the established minimum of 0.8 ( Cohen, 1988 ; Hair et al., 2019 ). Of 105 e-banking users (see Table 1 ), 45.7% of the sample collected is composed of men and 54.3% of women. Concerning age, the largest group is integrated by individuals between 24 and 33 years old, representing 32.4% of the sample. In addition, the accumulated percentage of consumers up to 43 years of age is 67.6%. Hence, the sample is predominantly made up of young adults and mid-aged e-banking users. Thus, this study coincides with previous studies in e-banking such as Zhang et al. (2018) , Malaquias and Hwang (2019) , Mostafa (2020) , Singh and Srivastava (2020) , where the samples are mostly composed of young people considered more likely to use digital technologies and media. Moreover, 35.3% of the respondents are employees, 43.8% are singles, and 37.1% are married. Concerning consumption factors, 93.3% of the sample uses e-banking to check their bank account balance, 49.5% make bank transfers through e-baking, and 15.2% manage invoices and taxes.

Table 1. Characteristics of the survey sample.

In order to measure the constructs included in this study and examine the proposed relationships, a structured questionnaire was used. Firstly, questions related to the frequency and habits of the use of electronic banking were included. Then, the variables associated with the attitude and behavior toward using e-banking were exposed. All these constructs were evaluated with multi-item scales confirmed by previous studies, using a Likert scale ranging from 1 to 5, except the construct intended to use, presented on a semantic differential scale (see Table 2 ). Thus, variables for perceived ease of use were based on Davis et al. (1989) and Venkatesh et al. (2003) . The attitude toward using e-banking was measured through a semantic differential scale using six items (five bipolar pairs of adjectives). Several authors, such as Stern and Salb (2015) , define the attitude as a formative construct characterized mainly by affective aspects and instrumental distinctions. According to the scales proposed by Davis et al. (1989) , Venkatesh et al. (2003) , and Carranza et al. (2020) in the area of technology acceptance, the attitude variable was measured using three significant items (unpleasant-attractive, unsatisfactory-satisfactory, boring-fun) and three instrumental items (bad-good, uninteresting-appealing, harmful-beneficial).

Table 2. Measurement of key concepts.

The perceived usefulness was measured using the Agarwal and Karahanna (2000) scale, following Mostafa’s (2020) work. Intention to use was measured using a single-item scale based on previous research, such as Bigné et al. (2008) . Three items adapted from Davis et al. (1989) and Dutot (2015) were used to measure e-banking usage. The last section of the questionnaire aims to collect information on the socio-demographic profile of e-banking users, such as gender, age, or occupation.

Statistical Analysis

The model was estimated using PLS-SEM. PLS-SEM is a technique of structural equation models based on variance. In this study, the use of PLS-SEM is recommended because (1) the study includes a formative construct (attitude toward using e-banking), (2) the model uses composite models ( Hair et al., 2019 ), and (3) PLS-SEM is applied in recent studies of TAM, in the field of e-banking, as well as in other different areas (e.g., Salimon et al., 2017 ; Carranza et al., 2020 ; Zollo et al., 2020 ). To estimate the proposed model, SmartPLS 3.2.9 was used. According to Hair et al. (2019) , a two-stage approach is used to evaluate the proposed model in this e-banking customers’ context. Thus, the measurement model is evaluated distinguishing the variables considered as a composite model in Mode A and Mode B, and then, the structural model is assessed.

Measurement Model

First, the standardized root mean square residual (SRMR) of the proposed model is calculated in order to assess the model fit ( Henseler et al., 2016 ). In this case, the SRMR value is 0.070, indicate an appropriate fit, given the accepted 0.008 cut-off point. To evaluate the measurement model, the reliability of the scales is studied for the construct’s perceived ease of use, perceived usefulness, intention to use, and e-banking usage (Mode A). Thus, the loadings of the indicators are examined, all of which are higher than 0.708. The evaluation of individual reliability is examined through the Dijkstra–Henseler’s rho (ρ A ) and the composite reliability (CR) being higher than 0.7 in all cases ( Hair et al., 2019 ). Therefore, all the variables included in the model reflect high internal consistency (see Table 3 ). Then, the average variance extracted (AVE) is used to evaluate convergent validity. In this case, all values of the AVE are within the established thresholds limits ( Fornell and Larcker, 1981 ). Lastly, all loadings are significant at 99.9% ( Hair et al., 2017 ). Concerning the analysis of the discriminant validity, the results obtained by the Fornell–Larcker criterion show a satisfactory degree of discriminant validity. However, Henseler et al. (2015) suggest construct thresholds below 0.9 for HTMT to establish discriminant validity. In this case, problems of discriminant validity between PEU and PU are detected. For that reason, the items causing the problem are studied and eliminated (see Table 4 ).

Table 3. Measurement model evaluation.

Table 4. Measurement model: discriminant validity.

To evaluate the validity of the attitude toward using e-banking, the variance inflation factor (VIF) is used to assess the lack of collinearity problems by the indicators (VIF < 5) (see Table 5 ). Finally, for the significance value of the weights, ATT4 and ATT6 are not significant. However, according to Hair et al. (2019) , since there are no collinearity problems and the loads are greater than 0.5, these indicators are not deleted.

Table 5. Measurement model: model composite Mode B.

Structural Model

After checking the reliability and validity of the measurement model, the proposed structural model is examined. To do this, the explanatory capacity of the model is evaluated using R 2 ( Hair et al., 2019 ). The R 2 values are 0.657 for perceived usefulness, 0.530 for attitude toward using e-banking, 0.462 for intention to use, and 0.324 for e-banking usage. After performing an analysis of the variance decomposition, the findings confirm that, of the 53% of the explained variance of attitude toward using e-banking, 29.1% is due to perceived ease of use and 23.9% to perceived usefulness. Similarly, of the 46.2% of explained variance of intention to use, 14.4% is due to perceived usefulness, and 31.8% is due to attitude toward using e-banking. Even though these results confirm significant relationships, the influence of consumers’ attitudes toward the intention to use e-banking is greater than the contribution of the perceived usefulness.

On the other hand, the path coefficients and their significance are evaluated to describe the significance of the structural relationships proposed in the model (see Table 6 ). Perceived ease of use appears to be positive and significant, at 99.9% in perceived usefulness. Thus, H1 is supported, being the most solid association of the model (β = 0.811). As proposed in H2 and H3, perceived ease of use and perceived usefulness are positively associated with the attitude toward using e-banking (β = 0.417 and 0.348, respectively). Similarly, perceived usefulness has a significant influence on the intention to use of e-banking, also confirming H4 (β = 0.248). Also, attitude toward using e-banking, in general, has a significant and positive effect on the intention to use e-banking. Thus, H5 is established (β = 0.485). Finally, the intention to use has a significant influence on e-banking usage. Therefore, H6 is also confirmed (β = 0.569) ( Hair et al., 2019 ). Thus, hypotheses H1, H2, H3, H4, H5, and H6 are accepted by the percentile method.

Table 6. Structural model evaluation.

After evaluating and confirming the proposed model, the effect size is evaluated ( Hair et al., 2019 ). Thus, the results show that (see Table 6 ), the perceived ease of use has a large effect size on perceived usefulness ( f 2 = 1.915). Likewise, the intention to use has a significant and large effect size on e-banking usage ( f 2 = 0.479). Finally, the model’s predictive relevance is analyzed. In this case, Stone–Geisser’s Q 2 shows that the scores are higher than naught (see Table 6 ).

To improve these results, the IPMA is used. The IPMA expands the reported PLS-SEM results for path coefficient estimates by adding a dimension to the analysis that considers the mean values of the latent variable scores ( Ringle and Sarstedt, 2016 ). In this case, the IPMA for e-banking users (see Figure 2 ) shows that intention to use is observed to be the most critical factor in determining e-banking usage. An increase of one point in the performance of intention to use by a total effect of 0.786. Attitude toward using e-banking has higher importance on e-banking usage but lower than the intention to use. Similarly, the attitude has a lower performance than the intention to use. The perceived ease of use is the factor with the lowest performance. Finally, perceived usefulness has the lowest importance in determining e-banking usage (see Figure 2 ).

Figure 2. Importance-performance map analysis (IPMA) for e-banking usage.

This study developed a research framework to understand the factors that contribute to e-banking usage and to benefit business strategies based on the co-creation of consumer value. The model provides a comprehensive view of the main factors influencing e-banking intentions and the elements that should be considered to increase usage.

The results obtained concerning the application of TAM in the context of e-banking confirm the presence of significant relationships among perceived ease of use and perceived usefulness by the customer, being the most real relationship of the proposed model. Similarly, the relationships between perceived usefulness and attitude toward using e-banking, perceived ease of use and attitude toward using e-banking are also contrasted. However, the importance that perceived ease of use acquires in the attitude toward using e-banking is slightly higher than the influence that perceived usefulness has on this variable. Similarly, the relationships between perceived usefulness and intention to use, and attitude toward using e-banking and intention to use are also contrasted with previous studies, such as Salimon et al. (2017) , Zhang et al. (2018) , and Malaquias and Hwang (2019) . Nevertheless, the results of the analysis of variance decomposition indicate that attitude toward using e-banking has relatively greater importance in intention to use compared to perceived usefulness. Therefore, an essential contribution of this research is the determination of attitude as a critical element in the determination of e-banking use intention. These results suggest that when e-banking users have a positive attitude toward using e-banking, it translates into a greater intention to use e-banking. Finally, the relationship between intention to use and e-banking usage is also verified, being the second strongest relationship of the model. In this sense, the results obtained by the IPMA analysis indicate that the intention to use is the variable with the highest performance and the greatest importance in determining the adoption of e-banking. However, the perception of ease of use, despite the great importance in determining the use of e-banking, is the variable with the lowest performance in the proposed model.

These findings offer important implications for banks and financial institutions. The techniques and results of this study allow banks to identify possible deficiencies and apply improvements to establish greater interaction with their clients. Also, this study offers bank managers new tools that encourage co-creation through e-banking services, helping to achieve a competitive advantage.

Based on the results obtained, bank managers should pay special attention to the perceived ease of use and perceived usefulness of their e-services, since they contribute significantly to the adoption of e-banking by consumers. Perceived ease of use of e-banking services is one of the most relevant factors in the adoption of e-banking by consumers. However, the IPMA indicates that it is the factor with the lowest performance. As a consequence, banks can improve the usability and simplicity of their e-services and the performance of a banking transaction to facilitate and increase the e-banking usage. Likewise, customer service can be provided to guide and help the efficient use of these applications. Specifically, some authors such as Mostafa (2020) recommend the use of chatbot to facilitate the use of e-banking and co-create. Concurrently, the findings have shown the great importance of attitude in generating intention to use e-banking by consumers. Therefore, banks should encourage this attitude in consumers through the ease of use and usefulness provided by e-services.

By and large, as technology and smartphone advance, consumers will continue to seek out more personalized and utilitarian services for their banking operations. Therefore, e-banking should be secure, and easy to learn and use. For this reason, providing reliable, user-friendly, and useful e-services are a crucial element in the interactions between consumer adoption of e-banking.

Limitations and Further Research

This study has some limitations that need to be addressed. The first limitation is the geographical location of the sample and the size of the sample. Future studies should incorporate a more significant number of online banking users covering a wider geographical area. Similarly, this study can increase the number of respondents between 34 and 53-year-old. Secondly, this study has not considered the moderating role of gender and age as socio-demographic variables. Previous authors, such as Natarajan et al. (2018) , consider age as a great relevance in studies of acceptance of mobile applications. Further research may assess the moderating role of this variable in the proposed model. Thirdly, this model is based exclusively on functional characteristics of technology adoption, such as perceived ease of use and perceived usefulness. In the area of e-banking, authors such as Zhang et al. (2018) highlight other types of more emotional factors for the study of the adoption of e-banking services such as enjoyment or trust. Likewise, Singh and Srivastava (2020) highlight the perceived security in the factors of adoption of e-banking. Thus, a future proposal could include a combination of functional and emotional elements in e-banking environments. Finally, further research could incorporate external variables associated with value co-creation, such as the confidence in the bank. Some studies, such as Mostafa (2020) , suggest that consumer confidence in the bank can intensify the positive effect of the attitude toward e-banking. If customers believe that their bank is honest and professional, their positive attitude toward the use of e-banking will result in a disposition to co-create value with the bank by sharing information or providing feedback.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

This work was financed by group grants from the University of Castilla–La Mancha and co-financed by the European Union through the European Regional Development Fund (Project reference: 2020-GRIN-28990). Research Group: Research and Modelling in Marketing and Tourism (RMMT).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Agarwal, R., and Karahanna, E. (2000). Time flies when you are having fun: cognitive absorption and beliefs about information technology usage. MIS Q . 24, 665–694. doi: 10.2307/3250951

CrossRef Full Text | Google Scholar

Ahmad, S., Bhatti, S. H., and Hwang, Y. (2019). E-service quality and actual use of e-banking: explanation through the technology acceptance model. Inf. Dev. 36, 503–519. doi: 10.1177/0266666919871611

Ajzen, I. (1991). The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211. doi: 10.1016/0749-5978(91)90020-T

Akter, S., Motamarri, S., Hani, U., Shams, R., Fernando, M., Babu, M. M., et al. (2020). Building dynamic service analytics capabilities for the digital marketplace. J. Bus. Res . 118, 177–188. doi: 10.1016/j.jbusres.2020.06.016

Andreu, L., Saìnchez, I., and Mele, C. (2010). Value co-creation among retailers and consumers: new insights into the furniture market. J. Retail. Consum. Serv. 17, 241–250. doi: 10.1016/j.jretconser.2010.02.001

Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Patil, P., and Dwivedi, Y. K. (2019). An integrated model for m-banking adoption in Saudi Arabia. Int. J. Bank Mark . 37, 452–478. doi: 10.1108/IJBM-07-2018-0183

Bankia (2020). Bankia Presenta el ‘Humanismo Digital’, Una Nueva Forma de Relacionarse Con Sus Clientes Basada en la Tecnología y las Personas. Available online at: https://www.bankia.com/es/comunicacion/noticias/bankia-humanismo-digital-clientes-tecnologia.html (accessed October 7, 2020).

Google Scholar

Bigné, E., Ruiz, C., Aldás, J., and Sanz, S. (2008). Influence of online shopping information dependency and innovativeness on internet shopping adoption. Online Inf. Rev . 32, 648–667. doi: 10.1108/14684520810914025

Carranza, R., Díaz, E., Martín-Consuegra, D., and Fernández-Ferrín, P. (2020). PLS–SEM in business promotion strategies. A multigroup analysis of mobile coupon users using MICOM. Ind. Manag. Data Syst. 120, 2349–2374. doi: 10.1108/IMDS-12-2019-0726

Chepurna, M., and Criado, J. R. (2018). Identification of barriers to co-create online: the perspectives of customers and companies. J. Res. Interact. Mark . 12, 452–471. doi: 10.1108/JRIM-01-2018-0018

Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences , 2 Edn. Hillsdale, NJ: Erlbaum.

Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Manage. Sci. 35, 982–1003. doi: 10.1287/mnsc.35.8.982

PubMed Abstract | CrossRef Full Text | Google Scholar

Deb, M., and Lomo-David, E. (2014). An empirical examination of customers’ adoption of m-banking in India. Mark. Intell. Plan. 32, 475–494. doi: 10.1108/MIP-07-2013-0119

Dutot, V. (2015). Factors influencing near field communication (NFC) adoption: an extended TAM approach. J. High Technol. Manag. Res . 26, 45–57. doi: 10.1016/j.hitech.2015.04.005

Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18, 39–50. doi: 10.1177/002224378101800104

Glavee-Geo, R., Shaikh, A. A., and Karjaluoto, H. (2017). Mobile banking services adoption in Pakistan: are there gender differences? Int. J. Bank Mark. 35, 1090–1114. doi: 10.1108/IJBM-09-2015-0142

Grönroos, C. (2011). Value co-creation in service logic: a critical analysis. Mark. Theory 11, 279–301. doi: 10.1177/1470593111408177

Hair, J. F., Risher, J. J., Sarstedt, M., and Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. Eur. Bus. Rev . 31, 2–24. doi: 10.1108/EBR-11-2018-0203

Hair, J. F., Sarstedt, M., Ringle, C. M., and Gudergan, S. P. (2017). Advanced Issues in Partial Least Squares Structural Equation Modeling. Thousand Oaks, CA: SAGE Publications.

Henseler, J., Hubona, G., and Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Ind. Manag. Data Syst . 116, 2–20. doi: 10.1108/IMDS-09-2015-0382

Henseler, J., Ringle, C. M., and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. J. Acad. Mark. Sci . 43, 115–135. doi: 10.1007/s11747-014-0403-8

Hosseini, M., Shajari, S., and Akbarabadi, M. (2020). Identifying multi-channel value co-creator groups in the banking industry. J. Retail. Consum. Serv. (in press). doi: 10.1016/j.jretconser.2020.102312

Ind, N., and Coates, N. (2013). The meaning of co-creation. Eur. Bus. Rev . 25, 86–95. doi: 10.1108/09555341311287754

Mainardes, E. W., Teixeira, A., and Romano, P.C.d.S (2017). Determinants of co-creation in banking services. Int. J. Bank Mark. 35, 187–204. doi: 10.1108/IJBM-10-2015-0165

Malaquias, R. F., and Hwang, Y. (2019). Mobile banking use: a comparative study with Brazilian and U.S. participants. Int. J. Inf. Manag . 44, 132–140. doi: 10.1016/j.ijinfomgt.2018.10.004

Malar, D. A., Arvidsson, V., and Holmstrom, J. (2019). Digital transformation in banking: exploring value co-creation in online banking services in India. J. Glob. Inf. Technol. Manag. 22, 7–24. doi: 10.1080/1097198X.2019.1567216

Martovoy, A., and Santos, J. (2012). Co-creation and co-profiting in financial services. Int. J. Entrep. Innov. Manag. 16, 114–135. doi: 10.1504/IJEIM.2012.050446

Medberg, G., and Heinonen, K. (2014). Invisible value formation: a netnography in retail banking. Int. J. Bank Mark . 32, 590–607. doi: 10.1108/IJBM-03-2014-0041

Mostafa, R. B. (2020). Mobile banking service quality: a new avenue for customer value co-creation. Int. J. Bank Mark . 38, 1107–1132. doi: 10.1108/IJBM-11-2019-0421

Natarajan, T., Balasubramanian, S. A., and Kasilingam, D. L. (2018). The moderating role of device type and age of users on the intention to use mobile shopping applications. Technol. Soc. 53, 79–90. doi: 10.1016/j.techsoc.2018.01.003

O’Hern, M., and Rindfleisch, A. (2010). Customer co-creation: a typology and research agenda. Rev. Mark. Res . 6, 84–106. doi: 10.1108/S1548-643520090000006008

Oliveira, P., and von Hippel, E. (2011). Users as service innovators: the case of banking services. Res. Policy . 40, 806–818. doi: 10.1016/j.respol.2011.03.009

Payne, A., Storkbacka, K., and Frow, P. (2008). Managing the co-creation of value. J. Acad. Mark. Sci . 36, 83–96. doi: 10.1007/s11747-007-0070-0

Ringle, C. M., and Sarstedt, M. (2016). Gain more insight from your PLS-SEM results: the importance-performance map analysis. Ind. Manage. Data Syst. 116, 1865–1886. doi: 10.1108/IMDS-10-2015-0449

Riquelme, H. E., and Rios, R. E. (2010). The moderating effect of gender in the adoption of mobile banking. Int. J. Bank Mark. 28, 328–341. doi: 10.1108/02652321011064872

Salimon, M. G., Bin Yusoff, R. Z., Sanuri, S., and Mokhtar, M. (2017). The mediating role of hedonic motivation on the relationship between adoption of e-banking and its determinants. Int. J. Bank Mark. 35, 558–582. doi: 10.1108/IJBM-05-2016-0060

Schierz, P., Schilke, O., and Wirtz, B. (2010). Understanding customer acceptance of mobile payment services: an empirical analysis. J. Electron. Commer. Res. Appl. 9, 209–216. doi: 10.1016/j.elerap.2009.07.005

Schreieck, M., and Wiesche, M. (2017). “How established companies leverage it platforms for value co-creation – insights from banking,” in Proceedings of the 25 the European Conference on Information Systems , Guimarães.

Shaikh, A. A., and Karjaluoto, H. (2015). Mobile banking adoption: a literature review. Telemat. Inform . 32, 129–142. doi: 10.1016/j.tele.2014.05.003

Shankar, A., and Jebarajakirthy, C. (2019). The influence of e-banking service quality on customer loyalty: a moderated mediation approach. Int. J. Bank Mark . 37, 1119–1142. doi: 10.1108/IJBM-03-2018-0063

Shankar, A., Jebarajakirthy, C., and Ashaduzzaman, M. (2020). How do electronic word of mouth practices contribute to mobile banking adoption? J. Retail. Consum. Serv . 52:101920. doi: 10.1016/j.jretconser.2019.101920

Sikdar, P., Kumar, A., and Makkad, M. (2015). Online banking adoption a factor validation and satisfaction causation study in the context of Indian banking customers. Int. J. Bank Mark. 33, 760–785. doi: 10.1108/ijbm-11-2014-0161

Singh, S., and Srivastava, R. K. (2020). Understanding the intention to use mobile banking by existing online banking customers: an empirical study. J. Financ. Serv. Mark. 25, 86–96. doi: 10.1057/s41264-020-00074-w

Statista (2020a). Tasa de Penetración de los Servicios de Banca Online en España. Available online at: https://es.statista.com/estadisticas/501217/tasa-de-penetracion-de-los-servicios-de-banca-online-en-espana/ (accessed July 28, 2020).

Statista (2020b). Número de Clientes Digitales de los Principales Bancos con Presencia Digital en España. Available online at: https://es.statista.com/estadisticas/506244/numero-de-clientes-digitales-de-los-principales-bancos-con-presencia-digital-en-espana/ (accessed July 29, 2020).

Stern, T., and Salb, D. (2015). Examining profile disclosure on online social networks: an affective, behavioural, and cognitive perspective. Int. J. Electron. Bus . 12, 162–184. doi: 10.1504/ijeb.2015.069106

Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Q . 27, 425–478. doi: 10.2307/30036540

Wang, M., Cho, S., and Denton, T. (2017). The impact of personalisation and compatibility with past experience on e-banking usage. Int. J. Bank Mark . 35, 45–55. doi: 10.1108/IJBM-04-2015-0046

Yaseen, S. G., and El Qirem, I. A. (2018). Intention to use e-banking services in the Jordanian commercial banks. Int. J. Bank Mark. 36, 557–571. doi: 10.1108/IJBM-05-2017-0082

Yoon, H. S., and Steege, L. M. B. (2013). Development of a quantitative model of the impact of customers’ personality and perceptions on internet banking use. Comput. Hum. Behav . 29, 1133–1141. doi: 10.1016/j.chb.2012.10.005

Zhang, T., Lu, C., and Kizildag, M. (2018). Banking “on-the-go”: examining customers” adoption of mobile banking services. Int. J. Qual. Serv. Sci . 10, 279–295. doi: 10.1108/IJQSS-07-2017-0067

Zollo, L., Carranza, R., Faraoni, M., Díaz, E., and Martín-Consuegra, D. (2020). What influences consumers’ intention to purchase organic personal care products? The role of social reassurance. J. Retail. Consum. Serv. (in press). doi: 10.1016/j.jretconser.2020.102432

Keywords : customer value co-creation, e-banking, e-services, technology acceptance model, PLS-SEM

Citation: Carranza R, Díaz E, Sánchez-Camacho C and Martín-Consuegra D (2021) e-Banking Adoption: An Opportunity for Customer Value Co-creation. Front. Psychol. 11:621248. doi: 10.3389/fpsyg.2020.621248

Received: 25 October 2020; Accepted: 21 December 2020; Published: 14 January 2021.

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Copyright © 2021 Carranza, Díaz, Sánchez-Camacho and Martín-Consuegra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Rocío Carranza, [email protected]

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• Open access
• Published: 07 July 2023

Unlocking the full potential of digital transformation in banking: a bibliometric review and emerging trend

• Lambert Kofi Osei   ORCID: orcid.org/0000-0001-7461-4839 1 ,
• Yuliya Cherkasova 2 &
• Kofi Mintah Oware 1  

Future Business Journal volume  9 , Article number:  30 ( 2023 ) Cite this article

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Metrics details

Every aspect of life has been affected by digitization, and the use of digital technologies to deliver banking services has increased significantly. The purpose of this study was to give a thorough review and pinpoint the intellectual framework of the field of research of the digital banking transformation (DBT).

Methodology

This study employed bibliometric and network analysis to map a network in a single study, and a total of 268 publications published between 1989 and 2022 were used.

Our findings demonstrate that the UK, USA, Germany, and China are the countries that have conducted most of the studies on the digital banking transformation. Only China and India are considered emerging economies; everyone else is looking at it from a developed economy perspective. Additional research reveals that papers rated with A* and A grades frequently publish studies on digital banking transformation. Once more, the analysis identifies key theoretical underpinnings, new trends and research directions. The current research trend points toward FinTech, block chain, mobile financial services apps, artificial intelligence, mobile banking service platforms and sustainable business models. The importance of emphasizing the need for additional research in these fields of study cannot be stressed, given the expanding popularity of blockchain technology and digital currency in the literature.

Originality

It appears that this is the first study that examines the theoretical studies of digital banking transformation using bibliometric analysis. The second element of originality is about the multiple dimensions of the impact of technology in the banking sector, which includes customer, company, bank, regulation authority and society.

Introduction

The advent of information communication technology (ICT) is believed to have caused a paradigm shift in all aspects of human life. Technology has therefore become a necessary, unavoidable demand for society and the business environment, from work automation to service digitalization, from cloud computing to data analytics, from virtual collaboration to smart homes. Almost every industry is undergoing constant transformation because to technology. In the past 20 years, digitalization has had an impact on a variety of sectors, presenting fresh business prospects and encouraging new systems of innovation [ 1 ].

The finance sector is actively experimenting and inventing with the power of technology's digitization. It is also one of the industries that have successfully embraced digitization. One of the most laudable digital developments of the finance sector is the widespread adoption of digital banking over traditional banking methods. Recently, potentially disruptive technological breakthroughs and Internet-based solutions appear to have been introduced to the banking industry, one of the most established and conservative sectors of the economy. Digital transformation in banking is essential to enhance how banks and other financial organizations learn about, communicate with and satisfy the needs of customers. An effective digital transformation starts with understanding digital client behavior, preferences, choices, likes, dislikes, and stated and unstated expectations, to be more precise. Many academics are interested in how information and communications technology is advancing and how it can affect the banking industry [ 2 ]. However, the bibliometric analysis conducted by academics utilizing VOS viewer is assumed to be the first to look at the digital banking transformation (DBT) studies from a performance analysis and science mapping perspective.

Large data sets from databases like Web of Science, Scopus index or Dimension are permitted for bibliometric study. The bibliometric analysis moves the banks' digital transformation survey from single to multi-dimensional outcomes. A quick search of DBT studies shows that the first journal was published in 1989, despite the earliest forms of digital banking being traced back to the advent of ATMs and cards in the 1960s. The quantum of increase after 2014, amounting to 203 articles, representing 76% of all published articles on the topic, compels this study to focus on this field of DBT studies. We contend that establishing the area's intellectual framework is more crucial than ever. As a result, we make a contribution by offering a relevant, distinctive and significant intellectual map of the literature on digital banking studies through quantitative and bibliometric analysis. In mapping the intellectual structure of DBT, our study sets out to address the following critical research questions:

Who are the predominant contributors (publication by year, journals, publishers, authors, publication, journal quality, country, and universities) to the DBT theory?

What are the country's collaboration and citation analysis of the impact of digitalization on banks?

What is digital banking theory's intellectual foundation (co-citation)?

What are emerging research themes/trends and future direction (bibliography coupling

and keywords analysis) to digital banking theory?

In response to the above four questions, this study has at least four significant additions to the literature on digital banking. First, we extend and build upon prior assessments of digital banking by offering a factual, quantitative perspective on the theory's historical development across time. Of course, this study considers notable contributors, the intellectual framework and theoretical groundwork of the discipline, the degree to which individuals are connected, and thematic subdomains. We show how digital banking has advanced by evaluating the significant offshoots from the original work by [ 3 ]. Second, we objectively assess how faithfully emerging subtopic literature streams acknowledge and build upon Burk and Pfitzmann’s seminal works. As a result, our paper is uniquely suited to detect significant gaps that might exist in subtopic areas, and we offer suggestions for improving literature unification. Thirdly, we show how scholars of digital banking have historically changed their study goals over time in response to gaps between theory and practice in order to determine how faithfully they have addressed these gaps. Finally, we contribute to the digital banking literature by identifying emerging digital banking research and study trends. Overall, we think that our research exposes chances to grow more effectively and collaboratively in the future by highlighting well-traveled roads that previous researchers have taken, identifying potential cracks that may leave the literature in a state of disarray, and so forth [ 4 ].

This study used bibliometric and network analysis to map a network that comprises authors, co-authors, keyword occurrences, journal citations and author names in a single study. The approach can give a thorough overview and pinpoint the field's intellectual hierarchy [ 5 ]. Furthermore, according to [ 6 ], bibliometric approaches are suitable for mapping the academic structure of a certain area because doing so enables researchers to recognize "'what,' 'where' and 'by whom' founded the field. We carry out a thorough bibliometric evaluation to meet the research objectives by carefully extracting the sample literature using the proper inclusion and exclusion criteria and selecting the search string. The first stage involved a descriptive analysis, while the second stage involved a comprehensive bibliometric analysis. Utilizing VOSviewer and Rstudio assistance, citation and co-citation analyses were carried out to determine the intellectual structure of the study on digital banking studies. Weighted citation measures were used to identify the lead publications from the clusters.

The format of our paper is as follows: A brief theoretical overview of the DBT literature, including its core principles, significant developments and limits, is given in section " Theoretical background ." Section " Methods " describes the research approach in depth, and section " Results " shows the results of our investigation. The limitations of our study and their consequences for theory and practice are discussed in section " Discussions and future research agenda ." Finally, we provide our final observations in section " Conclusion ."

Theoretical background

Society, economics, banks and banking are changing as a result of technological advancement. Banks are an unneeded remnant whose purpose is best provided by alternate arrangements, even though we still need banking. The value chain of traditional banking has been disintermediated by technology, and its business model has been severely altered. As a result, Fin-Tech adoption and digital technology collaboration are widespread, constant and profoundly changing company structures [ 7 ]. Nearly 90% of banks fear losing business to Fin-Tech, which has replaced traditional value chains with shorter multi-modal and multi-directional nodes, according to KPMG's 2017 annual reports. Digitalization permeates the contemporary world, and the banking industry is no different. Our lives seemed to have grown so ingrained with digital technology that we would feel empty without it. Banks of all sizes are investing a lot in digital initiatives to maintain their uniqueness and meet as many of their customers' needs as possible. Digitalization leads to more customization and closer to customers. It is called digital banking when a bank renders its services online, and customers can make transactions and other activities online. Since over 73% of consumers use products from numerous platforms, Lee and Shin [ 8 ] highlight that bank model disruption and ascribe this to ongoing innovation followed by disruptive challenges, with the possibility of losing market share to Fin-Techs omnipresent.Mobile technologies and social media digitize bank value chains simultaneously addressing and influencing client demands and expectations.

However, according to our knowledge, not much research has been done on the banking sector. Nevertheless, it is well known that the banking sector, which is frequently IT-intensive, requires special consideration due to its significance for the whole economy. Berger [ 2 ] emphasizes that the benefits of technology adoption may not convert into improved production, which is consistent with the literature mentioned above. According to Berger, rather than the organization itself, the advantages of technology might be passed on to consumers and other production-related elements. Sharing data allow banks to process information more efficiently while also achieving huge economies of scale in the processing of payments. For instance, banks have reportedly employed information processing to handle deposit and loan client information as well as to more accurately assess risks, according to Berger and Mester. Additionally, they have employed telecommunications technologies to expeditiously process payments and disseminate this data while consuming fewer resources (2003, p. 58). This would imply that cost productivity increased in the 1990s.

Digital transformation has an impact on business processes and alters how banks conduct operations. A contributing aspect to the traditional relationship between customers and banks is digital transformation. Customers in particular have the right to use a variety of communication channels to engage in active and convenient engagement with banks and other customers via online customer support services. Most importantly, digital transformation enables banks to service a variety of consumers simultaneously, enhancing the bank's operational efficiency. In addition, the employee's job procedures are digitalized, reducing time and resources for both human resources and transaction execution. Thus, the bank will benefit from digital transformation by increasing output (raising the number of clients) and decreasing input expenses (reducing the number of employees and the time to make transactions).

The banking and FinTech industries will expand further in joint ventures, mergers and acquisitions toward convergence among banks, FinTech and technology organizations, and social media network providers as the new decade gets underway [ 9 ]. Digital technologies including blockchain, artificial intelligence (AI), data platforms, cybersecurity regulation technology and strategic collaborations will be well positioned to be retained in the banking business in a completely digitally changed financial environment [ 10 ]. Up until the advent of digital banking and the branch-based banking model in the early 1990s, traditional banking remained unaltered and unopposed. In the USA, Stanford Federal Credit Union opened the first online bank in 1994. The number of local bank branches has substantially decreased globally with the advent of online banking. Globally, the number of digital banks has been steadily rising at the same time. The first digital disruptor was ING Direct, which launched as an entirely online bank in 1996 and over the course of a little more than a decade attracted more than 20 million customers in nine countries without having to make any investments in physical infrastructure. In 2013, the FinTech bank "N26" received initial approval for a banking license. Amazon introduced an e-commerce-based checking account feature in 2021, while Facebook developed a social network-based banking service in 2020. By 2020, banking clients have been accustomed to using mobile banking apps, direct deposit to P2P payments and cloud-based banking platforms with AI.

To address our research issues in the present study, we employed two bibliometric analytic techniques. Since bibliometric analysis is quantitative, systematic, transparent and repeatable, it is strongly recommended for mapping the intellectual architecture of a literature stream [ 11 ]. The specifics of our research methodology and key conclusions are shown in Fig.  1 .

Flow chart of searching strategy and data collection process

To achieve its goals, this study suggests using publications and citations to analyze the performance of authors, institutions, countries and journals. Another unique approach used in this study is known as scientific mapping. Co-authorship analysis, clustering, citation analysis and keywords analysis are the approach factors [ 5 ]. Bibliometric approaches have been applied in recent investigations [ 12 , 13 ]. Then, we employ it to start the process of developing a bibliometric investigation [ 5 ]. The following actions are a part of the four-step process: data gathering and analysis, selecting the limiting criteria, data analysis, discussions and conclusions.

Defining the search terms

We started by conducting a methodical keyword search of the current literature on digital banking [ 14 ]. We extracted data from the Scopus index database. According to [ 15 ], Scopus has a larger journal than any other service that conducts data mining. As a result, this study made use of this database to mine data for its bibliometric analysis. To identify digital banking impact articles, we used the keyword methodology outlined by scholars who have recently conducted reviews of DBT. By concentrating primarily on work that has undergone thorough peer review, we aimed to maintain the academic integrity of our sample. Conference transcripts and book chapters were taken out of the analysis. Additionally, we excluded any non-English-language publications; 298 articles make up our final sample, which is deemed adequate for bibliometric study. These articles were published between 1989 and 2022. The keys words are: digital, bank, banking, business model, company, finance, economics and social sciences.

Keyword protocol applied in Scopus for extracting articles.

Data search and collection

As a result of several authors using the Scopus database for bibliometric analysis, it was chosen as the database from which the study's data were extracted [ 12 , 13 ]. In comparison with Web of Science and Dimension, the Scopus database has many indexed journals. The first stage of data extraction involved 295 publications with the titles "effect of digitalization on banks" and "digital transformation of banks" in June 2022. The following stage of the data processing was restricted to 268 English-language journals. The research is restricted to publications in the fields of banking, business management, accounting, economics, econometrics and finance. The last research search turned up 268 papers that were written between 1985 and 2022. Our literature review and bibliometric analysis are built on the foundation of the sample size of 268 articles. The method of data extraction is displayed in Table 1 .

This study raises different research questions covering contributors to DBT or impacts of digitalization on banks and banking, average journals and journal quality citation, digital banking intellectual foundations (co-citation), emerging research themes/trends and future direction (bibliography coupling and keywords analysis) in institutional theory.

Who are the predominant contributors to digital banking theory

This study responds to the first research question by addressing the dominant contributors to the DBT theory by using the following criteria: publication by year, journals, publishers, authors, publication, journal quality, country, and universities.

Publication by year

Figure  2 illustrates the number of DBT publications between 1989 and early 2022, recording 268 scientific publications. DBT received little attention from the scientific community in the early years from 1989 to 2005, recording as little as seven publications. The available data further show that publication increased slightly to sixty-seven (67) over a twenty (20) year period from 2006 to 2016. However, there was a dramatic change in this trend afterwards. Approximately 72 percent of these scientific publications, representing one hundred ninety-four (194) articles, occurred in the last six years. The figure further revealed that the years 2020 and 2021 alone accounted for 43 percent of all scientific publications in the field of DBT. Perhaps the havoc of Covid–19 and the strategic role of banks in successfully influencing the payment system architecture in particular resonated well with researchers to pay much attention to the field around this later period. While the quantity of publications has increased, publications within elite journals continue to grow. As recently as 2017, more over 40% of DBT research was published in prestigious publications. In fact, since 2017, the average annual proportion of publications in the top tier to all publications is 62 percent. As a result, our findings imply that the standard of published research has generally kept up with the volume of publications.

Trends in digital banking publication since 1989

Publication activity by country

Our findings also show that DBT research has a truly global reach, as shown by the participation of authors from 65 different countries. Figure  3 gives a graphic representation of the top countries publishing DBT research. For better clarity, the study limited Fig.  3 to cover countries with more than five publications. Although the publication of digital banking is international, it is interesting to notice that a significant portion of the work originates from a limited group of wealthy nations. More specifically, more than 46% of all published DBT studies come from the USA, UK, India, China, Germany, Netherlands, Hon Kong, Romania, Finland, Poland, Ukraine, Italy and Spain. Only China and India are from emerging economies. Figure  3 illustrates publication activities by country.

Top publishing countries on DBT

Publishing activity by journal

Two hundred thirteen different journals published the 268 articles in our sample. Table 1 lists the top publishing Journals. Based on publication count, we found that the leading journals for DBT include Financial Innovation, Journal of Cleaner Production, Journal of Economics and Business, International Journal of Information Management, Journal of Information Technology and Sustainability Journal. Our observation revealed that even though the Journal of Financial Innovation had only two publications, it claimed the top spot with two hundred and twelve citations total citation, given an average citation of one hundred and six. This study also used Australian Business School Council (ABDC) rating & ranking. Journal quality is rated and ranked by ABDC, with A* being the highest-quality journal, followed by A and B as the second- and third-best journals, respectively. According to the ABDC ranking, journal C is the lowest ranked. The data available to us have shown that the high-quality journals in class A and A* are publishing works on digital transformation. Three of the top five journals in our data are in the A class.

Publishing activity by author and organization

According to [ 16 ], bibliometric methodologies can be used to evaluate the intellectual influence of universities and their research personnel. To determine the sources of digital transformation in banking, we assessed the research output of individual academics and institutions. We found 598 distinct writers from 224 organizations publishing on the subject of banking digital transformation inside our dataset. The top publishing scholars and institutions are listed in Tables 2 and 3 . The descriptive statistics also show that [ 17 , 18 , 19 , 20 ] are the authors with the highest citation. In addition, the Financial University under the government of the Russian Federation, Comsats University—Islamabad, National Chiao Tung University—China and the State University of Management—Russia are the top four.

Country collaboration and citation analysis

Country collaborations of co-authors analysis.

The UK is the most productive nation in terms of publishing changes in digital banking. Australia, Canada, Indonesia and the Russian Federation have the lowest populations. Figure  4 demonstrates that, with seven linkages and 18 times as many co-authorships, the UK has the highest level of collaboration. Countries like China, Hong Kong and the Netherlands, each with six links, tie for second place. The inflow of overseas students completing second and third degrees in the UK and the US may be one reason there are more significant connections between the two countries [ 21 ]. Additionally, the UK and China are two other significant technology superpowers laying the groundwork for digitization. This might have inspired and drawn academics to carry out studies in the area.

Country collaboration of co-authors analysis

Citation analysis

The most read articles in the field of research on DBT were found through citation analysis. Citation analysis examines the connections between publications and finds the most significant publications in a given study area [ 5 ]. Similar studies that used citation analysis based on the Scopus database have also been looked at research [ 21 ]. The authors' and the study's primary focus are analyzed based on their citations in Table 4 . The Financial Innovation Journal and Journal of Cleaner Production publish the most-cited article. Liu et al. [ 22 ] and Yip et al. are the authors of these articles [ 23 ]. Even though publications on the evolution of digital banking began in 1989, the most highly cited papers are in 2016 and 2018, respectively.

Cluster analysis (results of reference co-citation analysis with reference map)

By conducting the co-citation analysis of references as previously described and grouping the references cited by papers on DBT into clusters, we next looked at the intellectual foundation and structure of the DBT to answer the third research question. The 268 papers in our sample used 8720 different references in total. Our examination of co-citations revealed five interconnected clusters with a total of 67 articles. At least 20 of the 268 papers in our sample, which contained all 67 of these reference articles, collectively cited them. In other words, these 67 publications are the quantitatively most significant references in the literature on the shift of banking into the digital age. Similarly, we used the weighted citation count provided by VOS viewer to ensure high-quality articles in cluster analysis. We looked at the top 5 articles in each cluster as presented in Table 5 , to find a common topic, and we labeled each theme accordingly, following [ 24 ]. We summarize the findings of the five most influential studies in each cluster. In the following sections, we give a quick overview of these reference clusters and how they integrate into the larger framework for digital banking (Fig. 5 ).

Co-citation network of the reference map

Cluster 1: Digital banking innovation

A cluster that established its boundaries improved its theoretical relevance and defined it as the first and most noticeable cluster to arise. Therefore, it makes sense that [ 25 ] are the most important tenet of this fundamental research stream. In 2022, digital transformation will continue to be a crucial trend in banking. The financial services sector is slowly changing as a result of technology, just like how it has affected other economic sectors. Physical bank branches have historically served as the primary point of contact for facilitating customer and retail banking transactions, according to [ 25 ]. Customers are continuing to transition from in-person to digital transactions as technology advances because of a complementary influence brought about by more access to digital banking services and an improved experience of new digital access, goods, services and functionality. They have developed a novel mapping technique for FinTech developments that assesses the extent of changes and transformations in four subfields of financial services: operations management, technological advancements, multiple innovations, and blockchain and other FinTech innovations. According to [ 26 ], the current wave of mergers and acquisitions in the financial services sector, combined with the broad availability of sophisticated technology, has increased competitiveness in the sector. Also, Henseler et al. [ 27 ] used discriminant validity assessment analysis to establish relationships between latent variables in business transformation. The digital banking revolution cannot go without challenges. All innovations encounter client resistance, claims [ 28 ] tested hypotheses using binary logit models comparing mobile banking adopters versus non-adopters, mobile banking postponers versus rejecters and Internet banking postponers versus rejecters using data from two comprehensive national surveys conducted in Finland ( n  = 1736 consumers). The value barrier is the main obstacle to the adoption of online and mobile banking, according to the study's findings. He also discovered that age and gender strongly influence decisions to adopt or reject. When [ 29 ] looked at the effect of cognitive age in explaining older people's resistance to mobile banking, they discovered that traditional and image barriers had an impact on usage, value and risk. All impediments, in turn, have an impact on resistance behavior. Furthermore, cognitive age was found to moderate these relationships. In order words, younger elders have limited or no resistance to DBT as opposed to elderly ones. All writers in this cluster agree that technology and evolving customer demands dramatically affect how banks operate in the twenty-first century. Indeed, the coronavirus outbreak has made it clear that banking institutions need to speed up their digital transitions. But the banking sector needs to modify its business models for front-facing and back-office operations to keep up with the changes and avoid potential upheavals. True digital banking and a complete transformation are built on implementing the most recent technology, such as blockchain cloud computing and Internet of Things (IoT).

Cluster 2: FinTech and RegTech in Banking

Scholars in this cluster preoccupied themselves with the concept of FinTech (Financial Technology) and RegTech (Regulatory Technology) thus the application of emerging technology to improve the way businesses manage regulatory compliance). They provided a range of viewpoints to make the disruptive potential of FinTech and its consequences for a more thorough financial ecosystem application in the banking and financial ecosystem easier to understand. Despite the widespread agreement that FinTech will have a big impact on the financial services industry, little academic literature has examined this topic, according to [ 30 ], citing [ 8 ]. Kindly assist with the changes.. Additionally, no accepted definition of FinTech has yet been established. On the other hand, according to Google, the query what is FinTech is presently ranked seventh among the most popular FinTech-related questions (Google, 2016b). He gave the most up-to-date definition of FinTech, which is a new financial business that uses technology to enhance financial activity. Contrarily, RegTech, or regulatory technology, uses cutting-edge tools and methods to assist financial institutions in enhancing their regulatory governance, reporting, compliance and risk management. According to [ 31 ] research, many desirable results might certainly be attained if regulators were willing to implement cultural change and integrate technical improvements with regulation. Such outcomes can include stabilizing the financial system, fostering systemic stability. The disruptive invention by [ 31 ] has the potential to improve consumer welfare, regulatory and supervisory outcomes, and the financial services industry's reputation. According to [ 10 ], the traditional business models of retail banks are seriously threatened by the emergence of digital innovators in the financial services industry. Lee and Shin [ 8 ] who contend that FinTech ushers in a new paradigm in which information technology drives innovation in the financial industry endorse this point of view. FinTech is hailed as a paradigm-shifting, disruptive innovation that has the power to upend established financial markets. The corporate world is quickly digitizing, shattering borders between industries, providing new opportunities and eliminating long-successful business models, according to [ 22 ], who added to the literature. They added that, on the plus side, growing digitalization presents opportunities, including the chance to take advantage of a solid customer connection and boost cross-selling. The dangers are typically precise and immediate, which is a drawback.

Cluster 3: The new digital business model of banks and other financial service providers

The papers in this cluster delved into the business model concept and, to a more significant extent, the new banking business model, which is technology-led. According to [ 32 ], business strategists and academics are paying more attention to business models as they try to understand how businesses create value and function well in order to gain a competitive advantage. Additionally, they argued that the digital economy had given businesses the chance to test out novel systems for networked value creation, where value is collaboratively produced by a firm and a big number of partners for a large number of users. The researchers came to the conclusion that four key themes are emerging, largely centered on the idea of the business model: as a new analytical unit, providing a systemic perspective on how to "do business," encompassing boundary-spanning activities (performed by a focal firm or others), and focusing on both value creation and value capture. These ideas are related and reinforce one another. Chesbrough [ 33 ] says that businesses must use their business models to commercialize novel concepts and technology. While businesses may make significant investments and have elaborate systems for investigating novel concepts and technologies, they frequently lack the ability to develop the business models that would be used to implement these inputs. He proposed that organizations should build the capacity to innovate their business models in order to make sound business decisions. Durkin et al. [ 34 ] did an excellent job investigating social media's role in a bank’s new digitally oriented business model. They suggested that social media had the power to profoundly alter customer-bank relationships and improve how the two sides communicate in the future. Their research shows that a wide range of clients regularly use transactional e-banking services. Loebbecke and Picot [ 35 ] presented a position paper that considers the factors driving how digitization and big data analytics drive the change of business and society. There is also discussion of the potential effects of digitalization and big data analytics on banking or employment, particularly in terms of cognitive work. Although several authors have recently proposed definitions of "business model," Shafer et al. [ 36 ] claim that none of them seem to be broadly recognized. This lack of agreement could be ascribed to the concept's interest from a variety of fields, all of which have connected it to something. To develop business models in the age of digital transformation, there must be an exponential shift in corporate culture and leadership concentration. The authors concur that banking is evolving as a result of a new wave of digital-only firms who are fragmenting the industry, componentizing products, and upending established business models. They claimed that switching from the previous business model to the new one is not the only way to succeed in this adaptable, fluid world. Instead, it will shift away from relying on a single, vertically integrated business model and toward a variety of non-linear models and value chain roles. In actuality, the Covid-19 epidemic has accelerated the development of business ecosystems for digital banking. Opportunities to develop, deliver and realize the value in new ways are made possible by digital technologies. The pipeline concept, the foundation of the classic universal bank, allows it to independently manufacture, sell and distribute products using its internal resources. This vertically integrated pipeline business model is disintegrating, making room for value chains that are becoming more fragmented and chances for new business models. A network of diverse business players from backgrounds including banking, insurance, pension, communications, real estate, education, healthcare service providers and IT are part of the new business model that the researchers have found. They work together to benefit each other through coexisting. The result of these developments and transformation is that financial services will continue to function in innovative and distinctive ways from those previously observed.

Cluster 4: Role of IT in banking

The fourth cluster concentrated on the crucial part information technology (IT) plays in the supply of financial services. According to [ 37 ], several banks have used information technology (IT) to provide consumers with a variety of more effective services. They think that in order to gain clients and boost profits in a cutthroat business environment, bank management must simultaneously use a variety of service channels. The majority of earlier research on IT investment in the banking sector has been on implementing cutting-edge IT-based service channels, including Internet banking, from the perspectives of clients [ 37 ]. From the standpoint of the bank, Barkhordari et al. [ 37 ] demonstrate that IT has a beneficial effect on performance by taking into account both the conventional physical and alternative IT-based service channels at once. They came to the conclusion that the purpose of using IT-related tools in banking is to forward a strategic, transformative objective. Due to the advancement of modern IT, the relationship between banks and their customers has changed substantially over the past few decades. They claimed that some of the examples include well-known innovations such as automated teller machines (ATMs), online banking (e-banking), and straight-through processing (STP), as well as others that have not (yet) gained widespread adoption, such as electronic cash (e-cash), or electronic bill presentment and payment (EBPP). At least the first has changed how people and businesses manage their finances and had an impact on the entire sector. They outlined how the aforementioned advances needed structures that took trends into account and might broaden the scope of current bank architectures to include horizontal and vertical integration dimensions. According to [ 38 ], enterprise architecture is typically represented by the following layers and design objects:

Product/services, market segments, corporate strategy goals, strategic plans/projects and interactions with customers and suppliers are all included in the strategic layer.

Organizational layer: Information flows, organizational units, roles/responsibilities, sales channels and business processes.

Applications, application domains, business services, IS functionalities, information objects, and interfaces make up the integration layer.

Software layer: programs, data structures, etc.

Hardware components, network components, and software platforms make up the IT infrastructure layer.

When it comes to transformations, architectures are really useful, because they integrate many layers. Creating new businesses or reorganizing old ones is transformation.

According to [ 32 ], organizations that are successful over the long term have basic principles and purposes that never change while continuously adapting their business strategies and operations to the external environment. IT's penetration of the banking industry falls under this category of business change. Liu et al. [ 22 ] contributed to the conversation by asserting that technological advancements like high-frequency trading systems (HFT) and algorithmic trading systems had altered the financial markets. The point is that information technology (IT) makes it possible to design complex products, improve market infrastructure, apply adequate risk management strategies and aid financial intermediaries in reaching geographically remote and diverse markets. The Internet has considerably impacted the delivery methods used by banks. The Internet has become an essential medium for distributing banking services and goods.

Cluster 5: Response to DBT

This fifth and final cluster considered the attitude of staff and clients toward DBT. If computer systems are not utilized, they cannot increase organizational performance. Unfortunately, managers' and professionals' opposition to end-user technology is a common issue. We need to comprehend why people accept or reject computers in order to better forecast, explain and promote user acceptance. The findings point to the potential for straightforward yet effective models of user acceptance factors, with practical utility for assessing systems and directing managerial actions aimed at addressing the issue of underutilized computer technology. Agarwal and Prasad [ 39 ] assert that a recent lack of user adoption of information technology breakthroughs is to blame for the frequently paradoxical link between investments in information technology and increases in productivity. They continued by saying that the academic and professional sectors had grown concerned about this paradoxical connection between spending on information technology and increases in productivity. The axiom that systems that are not used generate little value is an often proposed explanation for this relationship. Therefore, in order to achieve the expected productivity advantage, it is not enough to simply have the technology available; it must also be accepted and used effectively by its target user group [ 39 ]. The work of DeLone and McLean threw more light on technology acceptance. When [ 32 ] created a thorough taxonomy, they provided a more comprehensive picture of the concept of information system success. Six main characteristics or categories of the success of information systems are proposed by this taxonomy: system quality, information quality, utilization, user satisfaction, individual impact and organizational impact. Meanwhile, further discussions in this cluster have given more insights into customer acceptance or otherwise of IT in banking. Perceived utility, perceived ease of use, trust and perceived enjoyment are discovered to be immediate direct drivers of customers' views toward utilizing Internet banking, according to [ 40 , 41 ] research. This finding is consistent with some of the findings of other studies. The clients' behavioral intentions to utilize Internet banking are determined by attitude, perceived risk, fun, and confidence. Although the perceived website design has a direct impact only on perceived usability, its indirect effects on perceived usefulness, attitude and behavioral intentions are considerable. Perceived enjoyment only has a short-term impact on perceived ease of use, but both a direct and indirect influence on perceived usefulness. Customer experience is at the heart of the digital banking transition. Therefore, banks must continuously innovate products, integrate cutting-edge technology and add value for their clients.

Keywords analysis

The trends in the keywords displayed in multiple studies can be used to determine the main study direction for upcoming investigations [ 42 ]. The VOSviewer r software, which has previously been utilized by other writers, is employed in this study to extract the author's keywords [ 12 , 21 , 43 ]. A co-occurrences network is produced by the VOS viewer program as a dimensional map [ 12 ]. We used bibliographical author keyword analysis to examine our sample and determine whether there was any increasing or declining themes of interest per research question four. We discovered that writers of the 268 publications in our sample employed 829 keywords to indicate their scientific work, meeting the studies' threshold. Only 26 words, or around 3% of the total, were used at least four times. Our findings imply that the literature on DBT is incredibly heterogeneous. Indeed, according to the results of most recent articles, 80 percent of the authors' specified keywords were utilized precisely once. However, there are several keywords that authors frequently utilize to describe their works (Fig.  6 ). FinTech is the most often used keyword, with 25 occurrences and 29 links to other keywords, followed by digitalization, with 18 and 20 links. Reporting on Digital Transformation contains 13 instances and 18 links. The bibliometric map of author keywords is shown in Fig.  6 .

Bibliometric map of author keywords co-occurrence with five minimum occurrences and overlay visualization mode

The theme areas contemporary academics focus on can be seen by closely examining the map. The use of bibliographic coupling is based on the subject the authors are investigating. The digital transformation of financial service delivery was investigated by [ 43 ] from the perspective of Nigeria about chatbot adoption. A moderated mediated model was used by [ 44 ] to examine how blockchain technology was adopted in the financial sector during the fourth industrial revolution. Additionally, Karjaluoto et al. [ 19 ] looked at how users' perceptions of value influence their use of mobile financial services apps. Similarly, Podsakoff et al. [ 16 ] focused on enhancing the value co-creation process: artificial intelligence and mobile banking service platforms. Taking the discussion to a different dimension, Teng and Khong [ 45 ] worked on Examining actual consumer usage of E-wallets: A case study of big data analytics. David-West et al. [ 46 ] examined sustainable business models to create mobile financial services in Nigeria. Yip and Bocken [ 23 ] deepened the discussion and, in turn, looked at Sustainable business model archetypes for the banking industry. Finally, Niemand et al. [ 20 ] highlighted digitalization in the financial sector: a backup plan with a strategic focus on digitalization and an entrepreneurial attitude. Future research on financial services provided via e-wallets and mobile banking is the main emphasis of the second cluster. Authors are still studying entrepreneurship and digitalization in the supply of financial services. Future research is required in these areas of study because blockchain technology and digital currency are also gaining traction in the literature. The most popular search terms and the number of times they were used are displayed in Table 6 .

Discussions and future research agenda

The first paper on DBT was published by [ 3 ], and since then, both its audience and popularity have grown. Yet, the rapid rise in total publications across a wide range of specialist areas, notably during the last five years, has made it increasingly difficult for academics to ascertain the intellectual structure of the field. Existing qualitative assessments, which usually only address a small fraction of Digital Transformation in Banking while failing to accurately capture the entire body of work, have in some ways made the problem of theoretical specificity worse. It is rather tricky for a qualitative evaluation to describe more than 260 works over three decades. Thus, our research fills a critical vacuum in the literature by thoroughly (and quantitatively) mapping the digital banking domain, documenting its conceptual structure and suggesting its most likely future orientations. The theoretical underpinnings from which they have been developed, the subtopics and subthemes they have written about, and the notable historical contributors to DBT study (such as scholars, schools, and journals) are all identified in our work over time. Overall, our findings imply a considerable worldwide impact of digitization on banking, making it a truly global study paradigm. Additionally, the high number of citations for recent works shows that there is a great need for more research utilizing the DBT theoretical framework, suggesting that the field of study will continue to advance for a very long period. The study's structure is based on a wide range of goals and inquiries.

The initial research question aimed to characterize the increase in publication (document by year and county) and productivity of journals in terms of citations, top authors and institutions of studies on DBT. According to the data that are currently available, 174 papers, or 72% of all scientific publications, were published in the last six years, from 2016 to 2022. Also, prestigious journals carried out more than 40% of the publications. Therefore, our data imply that the quantity and quality of published research have typically stayed up. Our data also show that the research on the DBT is genuinely global in scope, as seen by the contributions of authors from 65 different countries. China and the UK are split equally, with India coming in second. It is essential to add that the BRIC (Brazil, Russia, India and China) countries perform well with publications. African countries like Ghana and Nigeria are equally showing promising signs of publications in this light. Regarding journal productivity, the study has revealed that articles on the banking industry's digital transformation are published in high-caliber journals in the A and A* classes. In our statistics, three top-five journals fall into the A category. These are the International Journal of Information Management (A*), Journal of Information Technology (A*), and Journal of Cleaner Production (A). We found 598 distinct writers from 224 organizations publishing on the subject of DBT inside our dataset. The descriptive statistics also reveal that Ranti et al. (2020) have the most citations, while the Financial University of the Government of the Russian Federation is the most productive institution in terms of the DBT, with seven publications.

The second research topic analyzes the co-authorship analysis and citation analysis by nation of authorship. Figure  3 shows that the UK has the maximum amount of collaboration, with 16 links and 18 co-authorships. China, Hong Kong and the Netherlands tie for second place with six linkages each. The increase in foreign students seeking second and third degrees in the UK and China may be one factor fostering closer ties between the two countries [ 21 ]. The UK and China are two other critical technological superpowers establishing the foundation for digitization. This might have attracted scholars and prompted them to conduct studies in the area. Future research might study the effects of digitization on banking on enforcing public and private sector regulations in emerging nations like Africa.

The third research question assesses the intellectual structure of the knowledge of DBT. This result was attained through citation analysis. Finding the most important publications in a specific field of study through citation analysis involves looking at the relationships between publications [ 5 ]. The primary point of contact for enabling retail banking and consumer transactions in the past has been actual bank branches. Customers are still transitioning from in-person to digital transactions as technology develops thanks to a complimentary effect brought on by increased access to digital banking services as well as an improved user experience of new digital access products, services and an improved user interface. Further research revealed that the banking sector's transition to digitization had increased competitiveness among service providers. The citation analysis highlighted the impact of FinTech on financial services innovations. According to [ 8 ], FinTech ushers in a new paradigm where information technology drives innovation in the financial sector. FinTech is hailed as a paradigm-shifting, disruptive innovation that has the power to upend established financial markets. We discovered that the corporate world is rapidly digitizing, removing industry barriers, opening up new opportunities, and dismantling long-established business structures. The concept of a business model and, to a greater extent, the new banking business model was also included in the analysis. The authors proposed that businesses build the capacity to innovate their business models since it makes good business sense. For instance, it has been seen that social media is significantly influencing the business models of some digitally focused banks. Social media, according to some, has the power to radically alter customer–bank interactions and improve how the two sides communicate in the future. If banks are to have an impact, they must transition from relying on a single, vertically integrated business model to multiple non-linear models and roles in the value chain. As a result of these developments and transformations, financial services will continue to operate in novel and unique ways from those previously observed. The study has proven beneficial for the use of IT in banking. IT-related tools are used in banking to advance a strategic transformational goal. The connection between banks and their customers has altered significantly over the past few decades with the development of contemporary IT. The most prevalent enterprise architecture layers and design items, according to [ 38 ], are the strategic, organizational, integration, software and IT infrastructure. It has been established that information technology (IT) enables the development of complicated products, enhances market infrastructure, implements efficient risk management techniques and enables financial intermediaries to access diverse and geographically dispersed markets. Despite the enormous advantages of digital banking, opinions on the systems are widely divided. Agarwal and Prasad [ 39 ] claim that a recent lack of user acceptance of information technology breakthroughs is to blame for the frequently paradoxical link between investments in information technology and productivity increases. They said that the counterintuitive connection between productivity increases and information technology investments had alarmed academic and professional groups. According to theories advanced by academics, digital technology, in general, and information systems, in particular, must fall under one of the following taxonomies to be accepted and used: system effectiveness, accuracy of the data, usability, user happiness, personal effect and organizational effect. The fourth research question looked at the future directions and emerging research themes and trends in studies of the digital banking transition. Future scholars are still interested in business models, FinTech, and DBT or banking. Additionally, the focus of the conversation is rapidly shifting to emerging and developing economies. Nevertheless, contemporary research areas include blockchain [ 44 ], mobile financial services apps [ 19 ], artificial intelligence and mobile banking service platforms [ 47 ], and sustainable business models [ 46 ]. The importance of highlighting the need for additional research in these fields of study cannot be overstated, given the growing popularity of blockchain technology and digital currency in literature.

Implications for theory

At least four substantial contributions to the body of DBT research, in our opinion, have been made by this study. We contribute primarily by expanding on current DBT reviews. While other reviewers have used qualitative methodologies, we may supplement and expand on such assessments by utilizing a thorough bibliometric study, allowing us to be more explicit about DBT's intellectual progress and structure. This is significant because it gives us a unique opportunity to highlight notable contributors and pinpoint the present and past origins of DBT research. Second, our quantitative analysis of bibliographic data demonstrates how DBT research has developed into its paradigm, which is supported by the original article by Bürk and Pfitzmann [ 3 ]. Third, we make a contribution by detecting rising and negative trends in subtopic areas, so identifying the subjects that are most likely to be studied in the future by academics. Fourth, by conducting a comprehensive assessment of DBT, we pinpoint areas where theory and practice diverge and evaluate the ways in which researchers have aided practitioners by modernizing DBT to comprehend and foresee the difficulties of "real-world" business.

Implications for practice

The banking sector, like other sectors, aspires to embrace contemporary practices and incorporate digital technologies into its operational procedures. This complicated collection of measures necessitates a methodical and considered approach, particularly in financial services where substantial sums of money and severe risks are at stake. DBT in this sense refers to several adjustments made to the banking sector to integrate different FinTech technologies to automate, optimize, and digitize procedures and improve data security. The processes and technologies employed in the financial industry will alter due to several small and significant changes implied by this process. The fundamental tendency of digital transformation, regardless of industry, is the integration of computer technologies, and Statista's analysis indicates that this trend will continue to expand. The challenges posed by introducing new digital innovations must be understood by stakeholders, who must also articulate solutions. Again, embracing digital technologies will involve taking on several tremendous risks; for this reason, bank executives must simultaneously establish and implement a strategy for managing those risks. If regulators utilizing technology to oversee and control the industry want to ensure solid financial stability in the economy, they must constantly be ahead of innovation risk with appropriate countermeasures. Digital banking involves the collection and processing of vast volumes of customer data. This raises the issue of data protection following regulations and international best practices. The DBT's third useful outcome is that it prompts organizational leaders to consider how their personal biases—which are the products of their histories, characteristics and experiences—might influence opinions and, ultimately, bank performance.

Limitations

We know that no study is faultless, and ours has its setbacks. While we made every effort to minimize problems, we nevertheless expect to offer insightful suggestions for future bibliometric and DBT studies. First, we used the Scopus database, a popular database used in bibliometric research, to gather our bibliometric data [ 48 ]. Even though Scopus contains the most data sources, it does not include all research databases on the transformation of digital banking. Furthermore, because this database has so many uses, using Scopus for data collection could likely lead to mistakes that show up when performing bibliometric analysis. To put it another way, errors might have happened if articles were mislabeled, and it is possible that the database completely missed publications important to our study [ 49 ]. To address this potential issue, we followed the best bibliometric analysis methods. For instance, we thoroughly purged duplicates and other forms of incorrect items from our data. Additionally, this research is restricted to English-language publications, and the subject only includes business, management, finance, economics, FinTech and banking digitalization. The data search will be enhanced, and the search restriction will be reduced using several databases.

This article assesses the intellectual landscape and future potential of the field of DBT research, as well as the influence of that research. The approach for this study is based on descriptive analysis, performance analysis and science mapping analysis, and it employs bibliometric analysis. The set was created based on 268 documents from the Scopus database that span the years 1989 to 2022. We demonstrate that DBT has continued to be a hot topic for academic research approximately three decades after its conception. Our findings also indicate that the UK, USA, Germany and China are the countries that have conducted most of the studies on the DBT. Only China and India are considered emerging economies; everyone else is looking at it from a developed economy perspective. We further categorize the body of research on DBT into five main clusters, including (1) Digital Banking Innovation, (2) FinTech and RegTech in Banking, (3) The New Digital Business Model of Banks and Other Financial Service Providers, (4) The role of IT in banking, (5) Response to DBT. Due to a significant influx of international students, the UK, China and Hong Kong continue to be the most collaborative countries. Additional research reveals that papers rated with A* and A grades frequently publish studies on DBT. Once more, the analysis identifies key theoretical underpinnings, new trends and research directions. FinTech, block chain mobile financial services apps, artificial intelligence, mobile banking service platforms and sustainable business models are currently researched. Given the rising popularity of block chain technology and digital money in the literature, highlighting the need for more research in these areas of study cannot be overstated. This study builds on previous reviews by objectively charting the inception and intellectual growth of the digital banking area and evaluating its future possibilities. In essence, this bibliometric study offers a distinct and original viewpoint on the evolution of DBT by carefully and objectively assessing prior material and concurrently offering a clear road map for future work.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author upon request.

Abbreviations

Digital banking transformation

Financial technology

Regulatory technology

Internet of things

Automatic teller machine

Artificial intelligence

Information technology

Information communication technology

Straight through processing

Electronic banking

Electronic cash

Electronic bill presentment and payment

High-frequency trading system

Electronic wallets

Barrett M, Davidson E, Prabhu J, Vargo SL (2015) Service innovation in the digital age special issue: service innovation in the digital age service innovation in the digital age: key contributions and future directions Source: MIS Q 39:135–154. https://doi.org/10.2307/26628344

Berger AN (2003) The economic effects of technological progress: evidence from the banking industry. https://about.jstor.org/terms

Bürk H, Pfitzmann A (1989) Digital payment systems enabling security and unobservability. Comput Secur 8:399–416. https://doi.org/10.1016/0167-4048(89)90022-9

Article   Google Scholar  

Dharmani P, Das S, Prashar S (2021) A bibliometric analysis of creative industries: current trends and future directions. J Bus Res 135:252–267. https://doi.org/10.1016/J.JBUSRES.2021.06.037

Donthu N, Kumar S, Mukherjee D, Pandey N, Lim WM (2021) How to conduct a bibliometric analysis: an overview and guidelines. J Bus Res 133:285–296. https://doi.org/10.1016/J.JBUSRES.2021.04.070

White JV, Borgholthaus CJ (2022) Who’s in charge here? A bibliometric analysis of upper echelons research. J Bus Res 139:1012–1025. https://doi.org/10.1016/J.JBUSRES.2021.10.028

Omarini A (2017) Current Position: Tenured Researcher at the Department of Finance

Lee I, Shin YJ (2018) Fintech: ecosystem, business models, investment decisions, and challenges. Bus Horiz 61:35–46. https://doi.org/10.1016/J.BUSHOR.2017.09.003

Lee J, Wewege L, Thomsett MC (2020) Disruptions and Digital Banking Trends, (online) Scientific Press International Limited. https://www.researchgate.net/publication/343050625

Dietz M, Härle P, Khanna S (n.d) A digital crack in banking’s business model

Rauch A (2020) Opportunities and threats in reviewing entrepreneurship theory and practice. Entrepreneurship: Theory Pract 44:847–860. https://doi.org/10.1177/1042258719879635

Anand A, Brøns Kringelum L, Øland Madsen C, Selivanovskikh L (2020) Interorganizational learning: a bibliometric review and research agenda. Learn Organ 28:111–136. https://doi.org/10.1108/TLO-02-2020-0023

Kumar S, Pandey N, Kaur J (2023) Fifteen years of the : a retrospective using bibliometric analysis. Soc Respons J 19:377–397. https://doi.org/10.1108/SRJ-02-2020-0047

Short J (2009) The art of writing a review article. J Manage 35:1312–1317. https://doi.org/10.1177/0149206309337489

Block J, Fisch C, Rehan F (2020) Religion and entrepreneurship: a map of the field and a bibliometric analysis. Manag Rev Q 70:591–627. https://doi.org/10.1007/s11301-019-00177-2

Podsakoff PM, MacKenzie SB, Podsakoff NP, Bachrach DG (2008) Scholarly influence in the field of management: a bibliometric analysis of the determinants of University and author impact in the management literature in the past quarter century. J Manage 34:641–720. https://doi.org/10.1177/0149206308319533

Widharto P, Pandesenda AI, Yahya AN, Sukma EA, Shihab MR, Ranti B (2020) Digital Transformation of Indonesia Banking Institution: case study of PT. BRI Syariah. In: 2020 International conference on information technology systems and innovation (ICITSI), 2020, pp 44–50. https://doi.org/10.1109/ICITSI50517.2020.9264935

Harjanti I, Nasution F, Gusmawati N, Jihad M, Shihab MR, Ranti B, Budi I (2019) IT impact on business model changes in banking Era 4.0: case study Jenius. In: 2019 2nd International conference of computer and informatics engineering (IC2IE), pp 53–57. https://doi.org/10.1109/IC2IE47452.2019.8940837

Karjaluoto H, Shaikh AA, Saarijärvi H, Saraniemi S (2019) How perceived value drives the use of mobile financial services apps. Int J Inf Manage 47:252–261. https://doi.org/10.1016/J.IJINFOMGT.2018.08.014

Niemand T, Rigtering JPC, Kallmünzer A, Kraus S, Maalaoui A (2021) Digitalization in the financial industry: a contingency approach of entrepreneurial orientation and strategic vision on digitalization. Eur Manag J 39:317–326. https://doi.org/10.1016/J.EMJ.2020.04.008

Khatib SFA, Abdullah DF, Elamer A, Yahaya IS, Owusu A (2023) Global trends in board diversity research: a bibliometric view. Meditar Account Res 31:441–469. https://doi.org/10.1108/MEDAR-02-2021-1194

Liu Y, Luan L, Wu W, Zhang Z, Hsu Y (2021) Can digital financial inclusion promote China’s economic growth?. Int Rev Financ Anal 78: 101889. https://doi.org/10.1016/J.IRFA.2021.101889

Yip AWH, Bocken NMP (2018) Sustainable business model archetypes for the banking industry. J Clean Prod 174:150–169. https://doi.org/10.1016/j.jclepro.2017.10.190

Kent Baker H, Pandey N, Kumar S, Haldar A (2020) A bibliometric analysis of board diversity: current status, development, and future research directions. J Bus Res 108:232–246. https://doi.org/10.1016/J.JBUSRES.2019.11.025

Gomber P, Kauffman RJ, Parker C, Weber BW (2018) On the Fintech Revolution: interpreting the forces of innovation, disruption, and transformation in financial services. J Manag Inf Syst 35:220–265. https://doi.org/10.1080/07421222.2018.1440766

Fain D, Lou Roberts M (1997) Technology vs. consumer behavior: the battle for the financial services customer. J Direct Market 11:44–54. https://doi.org/10.1002/(sici)1522-7138(199724)11:1<44::aid-dir5>3.0.co;2-z

Henseler J, Ringle CM, Sarstedt M (2015) A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci 43:115–135. https://doi.org/10.1007/s11747-014-0403-8

Laukkanen T (2016) Consumer adoption versus rejection decisions in seemingly similar service innovations: the case of the Internet and mobile banking. J Bus Res 69:2432–2439. https://doi.org/10.1016/J.JBUSRES.2016.01.013

Chaouali W, Souiden N (2019) The role of cognitive age in explaining mobile banking resistance among elderly people. J Retail Consum Serv 50:342–350. https://doi.org/10.1016/J.JRETCONSER.2018.07.009

Schueffel P (2016) Taming the beast: a scientific definition of Fintech. J Innov Manag Schueffel JIM 4:32–54

Google Scholar  

Anagnostopoulos I (2018) Fintech and regtech: impact on regulators and banks. J Econ Bus 100:7–25. https://doi.org/10.1016/J.JECONBUS.2018.07.003

Porter ME (1980) Industry structure and competitive strategy: keys to profitability. Financ Anal J 36:30–41. https://doi.org/10.2469/faj.v36.n4.30

Chesbrough H (2010) Business model innovation: opportunities and barriers. Long Range Plann 43:354–363. https://doi.org/10.1016/J.LRP.2009.07.010

Durkin M, Mulholland G, McCartan A (2015) A socio-technical perspective on social media adoption: a case from retail banking. Int J Bank Market 33:944–962. https://doi.org/10.1108/IJBM-01-2015-0014

Loebbecke C, Picot A (2015) Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda. J Strateg Inf Syst 24:149–157. https://doi.org/10.1016/J.JSIS.2015.08.002

Shafer SM, Smith HJ, Linder JC (2005) The power of business models. Bus Horiz 48:199–207. https://doi.org/10.1016/J.BUSHOR.2004.10.014

Barkhordari M, Nourollah Z, Mashayekhi H, Mashayekhi Y, Ahangar MS (2017) Factors influencing adoption of e-payment systems: an empirical study on Iranian customers. Inf Syst E-Business Manag 15:89–116. https://doi.org/10.1007/s10257-016-0311-1

Winter R, Fischer R (2006) Essential layers, artifacts, and dependencies of enterprise architecture. In: 2006 10th IEEE international enterprise distributed object computing conference workshops (EDOCW’06), p 30. https://doi.org/10.1109/EDOCW.2006.33

Agarwal R, Prasad J (1997) The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decis Sci 28:557–582. https://doi.org/10.1111/j.1540-5915.1997.tb01322.x

Panetta IC, Leo S, Delle Foglie A (2023) The development of digital payments: past, present, and future—from the literature. Res Int Bus Finance 64: 101855. https://doi.org/10.1016/J.RIBAF.2022.101855

Bashir I, Madhavaiah C (2015) Consumer attitude and behavioural intention towards Internet banking adoption in India. Journal of Indian Business Research 7:67–102. https://doi.org/10.1108/JIBR-02-2014-0013

Pesta B, Fuerst J, Kirkegaard EOW (2018) Bibliometric keyword analysis across seventeen years (2000–2016) of intelligence articles. J Intell 6:1–12. https://doi.org/10.3390/jintelligence6040046

Abdulquadri A, Mogaji E, Kieu TA, Nguyen NP (2021) Digital transformation in financial services provision: a Nigerian perspective to the adoption of chatbot. J Enterp Commun 15:258–281. https://doi.org/10.1108/JEC-06-2020-0126

Khalil M, Khawaja KF, Sarfraz M (2022) The adoption of blockchain technology in the financial sector during the era of fourth industrial revolution: a moderated mediated model. Qual Quant 56:2435–2452. https://doi.org/10.1007/s11135-021-01229-0

Teng S, Khong KW (2021) Examining actual consumer usage of E-wallet: a case study of big data analytics, Comput Human Behav 121:106778. https://doi.org/10.1016/J.CHB.2021.106778

David-West O, Iheanachor N, Umukoro I (2020) Sustainable business models for the creation of mobile financial services in Nigeria. J Innov Knowl 5:105–116. https://doi.org/10.1016/J.JIK.2019.03.001

Dimitrova I, Öhman P, Yazdanfar D (2022) Barriers to bank customers’ intention to fully adopt digital payment methods. Int J Qual Serv Sci 14:16–36. https://doi.org/10.1108/IJQSS-03-2021-0045

Bhatt Y, Ghuman K, Dhir A (2020) Sustainable manufacturing. Bibliometrics and content analysis, J Clean Prod 260:120988. https://doi.org/10.1016/J.JCLEPRO.2020.120988

Di Vaio A, Palladino R, Hassan R, Escobar O (2020) Artificial intelligence and business models in the sustainable development goals perspective: a systematic literature review. J Bus Res 121:283–314. https://doi.org/10.1016/J.JBUSRES.2020.08.019

Amit R, Zott C (2012) Creating value through business model innovation, MIT Sloan Manag Rev. 48.

Fornell C, Larcker DF (1981) Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J Market Res. 18:39–50. https://doi.org/10.1177/002224378101800104 .

Porter ME (1996) What Is Strategy?.

Möwes T, Puschmann T, Alt R (2011) Service-based Integration of IT-Innovations in Customer-Bank-Interaction. https://aisel.aisnet.org/wi2011/102 .

DeLone WH, McLean ER (1992) Information Systems Success: The Quest for the Dependent Variable, Info Syst Res. 3:60–95. https://doi.org/10.1287/isre.3.1.60 .

Weill P, Woerner SL (2015) Thriving in an increasing digital ecosystem, MIT Sloan Manag Rev. 15.

Zhao JL, Fan S, Yan J (2016) Overview of business innovations and research opportunities in blockchain and introduction to the special issue, Financial Innovation. 2:28. https://doi.org/10.1186/s40854-016-0049-2

Gassmann O, Enkel E, Chesbrough H (2010) The future of open innovation. R and D Manage 40:213–221. https://doi.org/10.1111/j.1467-9310.2010.00605.x

Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology

Zhang S, Riordan R (2011) Association for information systems AIS electronic library (AISeL) technology and market quality: the case of high frequency trading recommended citation. http://aisel.aisnet.org/ecis2011/95

Banker R, Chen P.-Y, Liu F.-C, Ou C.-S (2009) Business value of IT in commercial banks. http://aisel.aisnet.org/icis2009/76

Ende B (2010) Association for information systems IT-driven execution opportunities in securities trading: insights into the innovation adoption of institutional investors recommended citation Ende, Bartholomäus, “it-driven execution opportunities in securities trading: insights into the innovation adoption of institutional investors,”. http://aisel.aisnet.org/ecis2010 ; http://aisel.aisnet.org/ecis2010/118

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Acknowledgements

The authors would like to graciously thank the Editor-in-Chief and the editorial team, and the two anonymous reviewers for their feedback in developing this paper. The writers also acknowledge Prof. Alfred Owusu, Dean of KsTU's Business School, for his guidance, inspiration and support. We appreciate his inventiveness and how it enabled us to clearly define the goal and possibilities of this effort. The authors also appreciate the helpful advice provided by Dr. Thomas Adomah Worae and Prof. Abdul-Aziz Iddrisu as we worked on the first versions of the manuscript. Finally, we would like to thank Riya Sureka, a research scholar at the Malaviya National Institute of Technology in Jaipur, India, for his advice on how to analyze bibliometric data using the ‘R’ and VOS viewer software.

This research received no external funding.

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Lambert Kofi Osei &  Kofi Mintah Oware

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All authors contributed significantly to the development of this article; LK generated the title, wrote the introduction, collection and analysis of the data, interpreted the co-citation analysis and put the manuscript together. YC reviewed the existing to conceptualize the study, reviewed the study and expanded the analysis. KM involved data generation from Scopus data base, software running, data analysis and review of the work. All authors read and approved the final manuscript.

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Lambert Kofi Osei holds a masters of business administration (finance option) degree from the Kwame Nkrumah University of Science and Technology. He is currently a PhD finance and banking student of Siberia Federal University, Russia. He is currently a lecturer at the Department of Banking Technology and Finance—Kumasi Technical University—in Ghana. He also holds an associated charted membership with the Chartered Institute of Securities and Investment—UK. Osei is certified expert in microfinance (CEMF) from the Frankfurt School of Finance—Germany. Osei has had considerable level of industry experience, with over 12 years managerial experience in the banking industry in Ghana including been the chief executive officer of Eman Capital. Prior to joining Kumasi Technical University, he was the National Chairman of Ghana Association of Microfinance Companies (GAMC)—an umbrella body of all microfinance companies in Ghana. Despite joining academia recently, Osei has made two publications of his work and a lot more articles are under completion stage to be sent for review. It is the goal of him to be an authority in the field of digital banking to impact businesses and societies.

Yuliya Cherkasova holds Ph.D. in economics and is a associate professor, School of Economics, Finance and Public Administration, Siberian Federal University. She is the chair of Digital Financial Technologies of Sberbank of Russia. Her research interests include banking prudential regulation of banks, digital economy and public finance. As a researcher, she has published more than 70 articles, 10 textbooks on topics, related finance and banking aria.

Kofi Mintah Oware has a Ph.D. in business administration (sustainability finance and management) from Mangalore University, India, and an MBA degree from Aberdeen Business School (Robert Gordon University—UK). He is currently a senior lecturer in the department of banking technology and finance. He is also a chartered accountant with membership from the Institute of Chartered Accountants (ICA), Ghana, and Institute of Cost Executive & Accountants (ICEA)—UK. Before joining academia, he worked in blue-chip companies for 12 years in various capacities, including chief accountant, head of finance and general manager for finance & administration in Ghana and research consultant to Aberdeen Businesswomen network in the UK. Among his key roles during industry experience include representing management in union negotiations and presenting the firm's financial reports in the corporate board meeting. In academia, he has 34 publications in various journal, including two "A" s under ABDC (Meditari Accountancy Research), three "B" s under ABDC (Social Responsibility Journal & Society and Business Review) and one C (South Asian Journal of Business Studies) all with Emerald publications. Also, he has 10 academic papers in various journals under review.

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A table of short literature of articles on DBT.

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Osei, L.K., Cherkasova, Y. & Oware, K.M. Unlocking the full potential of digital transformation in banking: a bibliometric review and emerging trend. Futur Bus J 9 , 30 (2023). https://doi.org/10.1186/s43093-023-00207-2

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Received : 08 November 2022

Accepted : 06 April 2023

Published : 07 July 2023

DOI : https://doi.org/10.1186/s43093-023-00207-2

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• Bibliometric literature review
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