literature review on online banking project

• Corpus ID: 220644814

E-BANKING: REVIEW OF LITERATURE

• Anukool Manish , Hyde
• Published 2017
• Business, Computer Science, Economics

4 Citations

Digital technology in banking post demonetization, effectiveness of e-banking to customer life service, digital payments: blockchain based security concerns and future, systemic acquired critique of credit card deception exposure through machine learning, 35 references, an empirical investigation of the turkish consumers’ acceptance of internet banking services, core capabilities for exploiting electronic banking, relationship quality, on‐line banking and the information technology gap, a survey of online e-banking retail initiatives, application of the latent class regression methodology to the analysis of internet use for banking transactions in the european union, e-banking and customer preferences in malaysia: an empirical investigation, adoption of internet banking by australian consumers: an empirical investigation, balances and accounts of online banking users: a study of two us financial institutions, the adoption of electronic banking technologies by us consumers, the bank of the future, related papers.

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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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Broby, D. Financial technology and the future of banking. Financ Innov 7 , 47 (2021). https://doi.org/10.1186/s40854-021-00264-y

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E-banking Overview: Concepts, Challenges and Solutions

• Published: 28 November 2020
• Volume 117 , pages 1059–1078, ( 2021 )

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The expansion of information technology has led to a new form of banking. Traditional banking, based on the physical presence of the customer, is only a part of banking activities. In the last few years, electronic banking has emerged, adopting a new distribution channels like Internet and mobile services. The main goal was to allow businesses to improve the quality of service delivery and reduce transaction cost, and anytime and anywhere service demand for customers. However, it increased the vulnerability to fraudulent activities like spamming, phishing and credit card frauds. Then, the main challenge that opposes electronic banking is ensuring banking security. In this context, this paper aims to provide an overview of the electronic banking service highlighting various aspects, investigating various challenges and risks, and discussing some proposed solutions.

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Kurnia, S., Peng, F., & Liu, Y. R. (2010). Understanding the adoption of electronic banking in China. In 43rd Hawaii International Conference on System Sciences , Honolulu, Hawaii, USA, pp. 1–10.

Vrîncianu, M., & Popa, L. A. (2010). Considerations regarding the security and protection of e-banking services consumers’ interests. The Amfiteatru Economic Journal , 12 (28), 388–403.

Google Scholar  

Peotta, L., Holtz, M. D., David, B. M., Deus, F. G., & Timoteo de Sousa, R. (2011). A formal classification of internet banking attacks and vulnerabilities. International Journal of Computer Science and Information Technology, 3 (1), 186–197.

Article   Google Scholar  

Drig, I., & Isac, C. (2014). E-banking services – Features, challenges and benefits. 10.

Chavan, J. (2013). Internet banking – Benefits and challenges in an emerging economy. International Journal of Research in Business Management, 1 (1), 19–26.

MathSciNet   Google Scholar  

Singhal, D., & Padhmanabhan, V. (2009). A study on customer perception towards internet banking: Identifying major contributing factors. Journal of Nepalese Business Studies, 5 (1), 101–111.

Liao, S., Shao, Y. P., Wang, H., & Chen, A. (1999). The adoption of virtual banking: An empirical study. International Journal of Information Management, 19 (1), 63–74.

Bahl, D. S. (2012). E-banking: Challenges and policy implications. International Journal of Computing & Business Research , 229–6166.

Zarei, S. (2011). Risk management of internet banking. In 10th WSEAS International conference on Artificial Intelligence, Knowledge Engineering and Data Bases , Cambridge, UK, pp. 134–139.

Hanaek, P., Malinka, K., & Schafer, J. (2008). E-banking security - comparative study. In 42nd Annual IEEE International Carnahan Conference on Security Technology , Prague, Czech Republic, pp. 326–330.

Omariba, Z. B., & Masese, N. B. (2012). Security and privacy of electronic banking. International Journal of Computer Science Issues (IJCSI), 9 (4), 432–446.

Park, K. C., Shin, J. W., & Lee, B. G. (2014). Analysis of authentication methods for smartphone banking service using ANP. KSII Transactions on Internet & Information Systems, 8 (6).

Brar, T. P. S., Sharma, D., & Khurmi, S. S. (2012). Vulnerabilities in e-banking: A study of various security aspects in e-banking. International Journal of Computing & Business Research .

Yang, Y. J. (1997). The security of electronic. In International Systems Security Conference , pp. 41–52.

Yang, J., Cheng, L., & Luo, X. (2009). A comparative study on e-banking services between China and USA. International Journal of Electronic Finance, 3 (3), 235–252.

Zahid, N., Mujtaba, A., & Riaz, A. (2010). Consumer acceptance of online banking. European Journal of Economics, Finance and Administrative Sciences, 27 (1).

Geetha, K. T., & Malarvizhi, V. (2011). Acceptance of E-banking among customers: An empirical investigation in India. The Journal of Internet Banking and Commerce, 15 (2), 1–17.

Deb, M., & Lomo-David, E. (2014). An empirical examination of customers’ adoption of m-banking in India. Marketing Intelligence & Planning, 32 (4), 475–494.

Lee, J. H., Lim, W. G., & Lim, J. I. (2013). A study of the security of Internet banking and financial private information in South Korea. Mathematical and Computer Modelling, 58 (1–2), 117–131.

Moga, L., Nor, K., Neculita, M., & Khani, N. (2012). Trust and security in e-banking adoption in Romania. Communications of the IBIMA , 1–10.

Komb, F., Korau, M., Belás, J., & Korauš, A. (2016). Electronic banking security and customer satisfaction in commercial banks. Journal of Security and Sustainability Issues, 5 (3), 411–422.

Ranaweera, H. (2019). Risk of electronic payments of the banking sector in Sri Lanka: Case of Colombo district. 4 (1).

Rajaratnam, A. (2019). The factors influencing on internet banking adoption in Trincomalee District, Sri Lanka, Sri Lanka. International Research Journal of Advanced Engineering and Science, 4 (1), 160–164.

Hasan, A. S., Baten, M. A., Kamil, A. A., & Parveen, S. (2010). Adoption of e-banking in Bangladesh: An exploratory study. African Journal of Business Management, 4 (13), 2718–2727.

Jalal, A., Marzooq, J., & Nabi, H. A. (2011). Evaluating the impacts of online banking factors on motivating the process of e-banking. Journal of Management and Sustainability, 1 (1).

Abukhzam, M., & Lee, A. (2010). Factors affecting bank staff attitude towards E-banking adoption in Libya. The Electronic Journal of Information Systems in Developing Countries, 42 (1), 1–15.

Abdellatif, T., Jinene, C., & Khazmi, N. (2014). Une cartographie de la résistance à l’adoption du M-Banking en Tunisie [Mapping of resistance to the adoption of M-Banking in Tunisia]. 8 (1).

Halime, Z. F., & Kirmi, B. Etude de la résistance à l’adoption et l’utilisation de la banque mobile. Management Research .

Floh, A., & Treiblmaier, H. (2006). What keeps the e-banking customer loyal? A multigroup analysis of the moderating role of consumer characteristics on e-loyalty in the financial service industry. SSRN Electronic Journal .

Gunson, N., Marshall, D., Morton, H., & Jack, M. (2011). User perceptions of security and usability of single-factor and two-factor authentication in automated telephone banking. Computers & Security, 30 (4), 208–220.

Weir, C. S., Douglas, G., Richardson, T., & Jack, M. (2010). Usable security: User preferences for authentication methods in eBanking and the effects of experience. Interacting with Computers, 22 (3), 153–164.

Ahmad, D. T., & Hariri, M. (2012). User acceptance of biometrics in e-banking to improve security.

Tassabehji, R., & Kamala, M. A. (2009). Improving e-banking security with biometrics: Modelling user attitudes and acceptance. In 3rd International Conference on New Technologies, Mobility and Security , Cairo, Egypt, pp. 1–6.

Moeckel, C. Human-computer interaction for security research: The case of EU e-banking systems.

Rifà-Pous, H. (2009). A secure mobile-based authentication system for e-banking. In On the Move to Meaningful Internet Systems: OTM, 5871 , 848–860.

Hamidi, N. A., Mahdi Rahimi, G. K., Nafarieh, A., Hamidi, A., & Robertson, B. (2013). Personalized security approaches in e-banking employing flask architecture over cloud environment. Procedia Computer Science, 21 , 18–24.

Alsaiari, H., Papadaki, M., Dowland, P. S., & Furnell, S. M. (2014). Alternative graphical authentication for online banking environments.

Elkhodr, M., Shahrestani, S., & Kourouche, K. (2012). A proposal to improve the security of mobile banking applications. 2012 Tenth International Conference on ICT and Knowledge Engineering (pp. 260–265). IEEE: Bangkok, Thailand.

Chapter   Google Scholar  

Islam Khan, B. U., Olanrewaju, R. F., Anwar, F., & Yaacob, M. (2018). Offline OTP based solution for secure internet banking access. In 2018 IEEE Conference on e-Learning, e-Management and e-Services (IC3e) , Langkawi Island, Malaysia, pp. 167–172.

Brodi, D., & Jankovi, R. (2016). Usability analysis of the specific captcha types. In International Scientific Conference , pp. 272–277.

Hoonakker, P., Bornoe, N., & Carayon, P. (2009). Password authentication from a human factors perspective: Results of a survey among end-users. Human Factors and Ergonomics Society Annual Meeting Proceedings, 53 (6), 459–463.

Mridha, F., Nur, K., Kumar, A., & Akhtaruzzaman, M. (2017). A new approach to enhance internet banking security. International Journal of Computer Applications, 160 (8), 35–39.

Chandanshive, A., Sureka, A., Gongiwala, V., & Nalawade, A. (2018). Access control using 3 level authentications for e-banking. International Journal on Recent and Innovation Trends in Computing and Communication, 6 (4).

Shen, L., Zheng, N., Zheng, S., & Li, W. (2010). Secure mobile services by face and speech based personal authentication. In 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems , Xiamen, China, pp. 97–100.

Onyesolu, M. O., Odoh, M., Akanwa, A. O., & Nwasor, V. C. (2010). Robust authentication model for ATM: A biometric strategy measure for enhancing e-banking security in Nigeria. International Journal of Advanced Research in Computer Science .

Bhosale, S. T. (2012). Security in e-banking via card less biometric. International Journal of Advanced Technology & Engineering Research, 2 (4), 457–462 2(2250).

Plateaux, A., Lacharme, P., Jøsang, A., & Rosenberger, C. (2014). One-time biometrics for online banking and electronic payment authentication. Availability, Reliability, and Security in Information Systems, 8708 , 179–193.

Darwish, S. M., & Hassan, A. M. (2012). A model to authenticate requests for online banking transactions. Alexandria Engineering Journal, 51 (3), 185–191.

Kumbhar, S., & Sahu, S. (2007). A new framework for online transaction using visual cryptography and steganography. International Journal of Innovative Research in Computer and Communication Engineering, 3 (11), 11418–11422.

Yaseen Khudhur, D., Saad Hameed, S., & Al-Barzinji, S. M. (2018). Enhancing e-banking security: Using whirlpool hash function for card number encryption. International Journal of Engineering & Technology, 7 (2.13).

Thompson, L. (2003). Smart card authentication: Added security for systems and network access.

Karia, A., Patankar, D. A. B., & Tawde, P. (2014). SMS-based one time password vulnerabilities and safeguarding OTP over network. International Journal of Engineering Research, 3 (5).

Al-Fairuz, M., & Renaud, K. (2010). Multi-channel, multi-level authentication for more secure eBanking.

Alarifi, A., Alsaleh, M., & Alomar, N. (2017). A model for evaluating the security and usability of e-banking platforms. Computing, 99 (5), 519–535.

Article   MathSciNet   Google Scholar  

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Chaimaa, B., Najib, E. & Rachid, H. E-banking Overview: Concepts, Challenges and Solutions. Wireless Pers Commun 117 , 1059–1078 (2021). https://doi.org/10.1007/s11277-020-07911-0

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Research Article

Open banking: A bibliometric analysis-driven definition

Contributed equally to this work with: Gorka Koldobika Briones de Araluze, Natalia Cassinello Plaza

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Universidad Pontificia Comillas, Madrid, Spain

Roles Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing

Affiliation Departament of Financial Management, Facultad de Ciencias Económicas y Empresariales, Universidad Pontificia Comillas, Madrid, Spain

• Gorka Koldobika Briones de Araluze, 
• Natalia Cassinello Plaza

• Published: October 3, 2022
• https://doi.org/10.1371/journal.pone.0275496
• Peer Review
• Reader Comments

“Open banking,” as a concept, was initially developed by a UK regulation to foster competition in banking through sharing client data (with their consent) amongst competitors. Today, it is regulated in several most relevant banking jurisdictions. Despite its growing relevance, consensus about the definition of open banking is lacking. This study examines 282 articles on open banking using bibliometric clustering techniques. Moreover, within the 282 articles and applying discourse analysis, we analyze 47 idiosyncratic definitions of open banking to test an integral framework that supports our proposed definition of the concept. Our study contributes to the literature by providing a generalized multidisciplinary definition of open banking. It identifies four main drivers behind the concept: business model change, client data sharing, incorporation of technological companies (fintechs and others), and regulation. These four elements, which should be considered in new regulations in the globalized banking sector, foresee open banking as a critical enabler of a new strategic dynamic in banking.

Citation: Briones de Araluze GK, Cassinello Plaza N (2022) Open banking: A bibliometric analysis-driven definition. PLoS ONE 17(10): e0275496. https://doi.org/10.1371/journal.pone.0275496

Editor: Tawei (David) Wang, DePaul University, UNITED STATES

Received: February 6, 2022; Accepted: September 19, 2022; Published: October 3, 2022

Copyright: © 2022 Briones de Araluze, Cassinello Plaza. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

What is open banking? Since the inception of the “Open Banking Working Group” in the United Kingdom in 2015, open banking has generally been considered as the platformization of the retail banking industry [ 1 , 2 ]. To date, it has spread worldwide from the UK to Continental Europe, America, and Asia, constituting one of the retail banking industry’s shaping forces of the future [ 3 , 4 ]. Thus, on top of the open banking initiative in the UK and PSD2 (Payment Services Directive 2) in the European Union, there are open banking regulations in Australia, India, México, and Brazil, and forthcoming regulations in Russia and Canada.

The essence of open banking regulations is to recognize the banking clients’ right to share their transactional data with authorized third parties and detailed provisions on how to materialize this right [ 5 ]. Despite its apparent simplicity, this data-sharing right constitutes the primary vector for fostering the transformation of the retail banking sector from a closed business model to an open platform, similar to what occurred in telecommunications, power, and gas industries [ 6 ].

Open banking originated from practitioners and was inspired by the open data, open-APIs (Application Programming Interfaces), and open innovation philosophies [ 7 ] applied to the retail banking business [ 8 , 9 ]. The business community is analyzing this phenomenon extensively, understanding it as a “ collaborative model in which banking data is shared through APIs between two or more unaffiliated parties to deliver enhanced capabilities to the marketplace ” [ 10 ].

Its first implementation worldwide materialized in the UK. It was requested by the Competition and Markets Authority as a foundational strategy to ascertain that personal current accounts, as well as small and medium-sized enterprises’ banking markets, serve customers better. This issue emanated from a retail banking market investigation concluded in 2016 [ 8 ]. It also inspired the European Commission to publish the PSD2 [ 7 , 11 , 12 ]. Although open banking is still in its initial stages of development, the concept has been embraced by practitioners and regulators, being regarded as one of the shaping forces of the financial industry worldwide [ 4 ].

Nevertheless, despite existing literature acknowledging the importance of open banking as a critical retail banking industry’s transformational lever [ 13 ], open banking as a research object still lacks conceptualization both theoretically and empirically [ 14 ]. Academic literature on the subject is still in its early stages of development. Out of 990 documents registered in the Google Scholar database (Aug 6, 2021) containing the term “open banking,” only 57 were published in Scopus-rated peer-reviewed academic journals.

Considering its international and multidisciplinary nature, open banking as a research object presents several challenges. To begin with, open banking is being studied in many academic fields, and researchers who represent different disciplines seem not to converge on a shared definition of open banking [ 14 ]. Additionally, most authors researching the topic leverage idiosyncratic definitions aligned with their respective research focus [ 15 ]. Moreover, subtle differences among open banking regulations worldwide create confusion when comparing publications from different geographies [ 3 ]. Hence, our study aims to establish a generalized definition of open banking and its varying interpretations in different disciplines and geographies. A generalized definition of open banking would add consistency and robustness to existing research, laying out a solid foundation to support high-quality research on the phenomenon.

Apart from a generalized definition, understanding different contexts in which the term “open banking” is used is also essential. Open banking can be discussed from different perspectives (regulatory, technological, economic, and managerial) that imply different nuances, which should be identified. Additionally, it is also critical to validate a generalized definition under these different contexts to assure that it works properly in all of them.

This study aims to understand the contexts and meanings of the term “open banking” and proposes a generalized definition that can be used unambiguously in the academic literature. For this objective, two methodologies are used. First, through clustering-based bibliometric analysis, 282 academic articles are analyzed to identify the areas, contexts, or meanings of “open banking.” Second, applying a “discourse analysis” methodology, the 47 definitions of open banking found in the literature are examined, and a generalized definition of the term applicable to all open banking connotations is proposed.

Our study makes several contributions to the literature. First, it performs a review of the pre-existing literature on open banking applying bibliometric techniques. Second, a generalized definition of open banking and its four applications (business model, fintech, data-sharing, and regulation) are proposed. Third, the 47 existing open banking definitions are systematically analyzed, and a classification is proposed for them (institutional, ecosystem, and client). Likewise, generated inductively, an “open banking integrated definition framework” is formulated based on eight elements that can be applied to similar definitions. Finally, the Hirschman Herfindahl Index (HHI) is used innovatively within the discourse analysis to measure the degree of consensus regarding the definition.

2. Literature review and research question

Open banking is a new phenomenon in the banking industry and an even newer concept in academia. Before 2016, only four articles contained the term “open banking” in academic or grey journals. Hence, open banking can be considered a new study object.

Existing literature can be grouped into three blocks: regulatory, technical, and managerial. The regulatory literature analyzes the legislation that supports open banking (European Union’s Second Payment Services Directive [PSD2], UK’s Open Banking Standard, Australia’s Consumer Data Right, Singapore’s Personal Data Protection Act, India’s Aadhaar and Unified Payments Interface, and similar regulatory pieces being analyzed and approved in Hong Kong, Canada, Brazil, [BCB Circular No. 4,015/2020], and Mexico (Ley Fintech). Existing publications either focus on a single jurisdiction [ 16 – 19 ] or compare different legislations [ 20 , 21 ]. From a technology perspective, existing literature focuses on the underlying infrastructure [ 22 – 24 ] as well as on the acceptance of the open banking technology from the customer’s perspective [ 25 – 27 ]. Managerial literature analyzes structural changes in the demand and supply of financial services in the retail banking market due to open banking [ 7 , 10 , 12 , 28 – 30 ]. Finally, other fields such as microeconomics are also starting to analyze the phenomenon [ 31 ].

Nevertheless, despite a growing academic interest in open banking, foundational literature is still missing. There are no publications analyzing the origins of open banking (why open banking is needed), the nature of the phenomenon (how open banking has developed in different geographies) or, even more basic, what open banking is. As a matter of fact, there are only three publications devoted to establishing a definition of open banking. van Zeeland and Pierson (2021) follow a bibliometric and discourse analysis approach for open banking, but they fail to propose a definition, concluding that:

“Open Banking could be all kinds of things , from a remedy to an ecosystem , or most often : a (business) model of some sort . Its purposes are considered to be providing new (‘better’ , ‘customer-centric’) services to customers and improving competition in the banking market by letting ‘third parties’ in . ” [ 14 ]

O’Leary et al. (2021), building on an open data lenses approach, propose the following definition:

“An initiative which facilitates the secure sharing of account data with licensed third parties through Application Programming Interfaces (APIs) , empowering customers with ownership of their own data . The initiative aims to increase competition in retail banking by developing innovative products and services which will bring increased value to customers . ” [ 15 ]

Finally, Laplante and Kshetri (2021) approach the need for a definition of open banking, but do not provide a generalized definition other than describing the phenomenon as:

“Open banking describes a special kind of financial ecosystem . The ecosystem provides third-party financial service providers open access to consumer banking , transaction , and other financial data from banks and nonbank financial institutions through the use of application programming interfaces (APIs) . ” [ 32 ]

The existing definitions of open banking present three types of problems fundamentally: perspective bias, discipline bias, and purpose bias. Starting with the perspective bias problem, open banking is a tripartite scheme between the owner of the data, custodian, and third party who accesses it. Any general definition must consider the three agents to avoid partial or incomplete analysis of the phenomenon. Regarding the discipline bias problem, researchers tend to confuse the context in which open banking is used in their discipline with a generally applicable definition. Thus, technical literature focuses exclusively on the technological support of the phenomenon, the regulatory literature on its legal support, and the management literature on the possible implications for the business model. However, a generalized concept of open banking must be able to encompass all its contexts of use and not just one of the meanings. Finally, the purpose bias problem consists of giving open banking a specific purpose other than the one for which it was formulated: to increase competition in retail banking by facilitating the entry of new competitors. Considering the combined effect of the three biases, the definitions proposed so far of open banking do not allow the construction of solid and generalizable knowledge about the phenomenon, which is a significant caveat on its development.

One last question is why academic research on open banking is relevant. There are no global figures for the investment required to materialize open banking. According to Tink, one of the world’s leading open banking service providers [ 33 ], the average open banking expenditure for a retail bank in Europe in 2020 was €83.1 Mn. So, the aggregated figure for the system should be in the range of tenths of billions annually, just for Europe. Nevertheless, we have no evidence, based on scientific studies, of the intention of customers to use services based on open banking. There is no scientific evidence on how open banking can impact value creation and distribution in retail banking. No robust academic studies explain the conditions under which customers are willing to share data with third-party providers. In short, the academia has dealt with accessory elements of open banking but not with the central aspects of the phenomenon. The lack of a robust and generally shared definition of the phenomenon allowing collaboration among researchers and a holistic view of the phenomenon, is at the heart of this knowledge gap.

Thus, a generalized definition of open banking together with a detailed understanding of different contexts in which the “open banking” concept is used is a relevant gap in the academic literature that needs to be filled. A particular contribution of this study is that it tackles the research question through a multidisciplinary approach, integrating views from different knowledge domains and through mixed quantitative-qualitative techniques, specifically bibliometric research and discourse analysis.

3. Methodology

This study follows a three-tiered approach to present a potential generalized definition of open banking ( Fig 1 ). First, using bibliometric techniques, we map existing literature (282 documents) and, by applying co-word analysis, cluster co-occurring terms to identify conceptual domains related to open banking. The clustering analysis is executed using Visualization of Similarities (VoS), an evolution of Multidimensional Scaling (MDS) algorithms. From this analysis, we identify four clusters that inform the existing open banking literature and examine the interaction among them. Second, by applying a discourse analysis approach, we analyze existing definitions of open banking in the literature (47 definitions found in the 282 articles) to reveal critical attributes mentioned in these definitions considering their disciplinary and geographical variations. We, then, profile the descriptors used concerning each attribute and propose a framework to analyze existing open banking definitions. Third, based on the analysis, we outline an integrative definition of open banking, identify limitations of the investigation, and propose future research developments.

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https://doi.org/10.1371/journal.pone.0275496.g001

The analysis supporting this publication combines two methodological approaches: bibliometric and discourse analysis. First, we identify and analyze all relevant open banking literature and cluster the main perspectives on the topic by leveraging bibliometric techniques. Then, we extract 47 idiosyncratic, partial, or working definitions of open banking identified in the dataset. Applying critical discourse analysis, a method that has been accepted in the academic literature as a valid procedure for social sciences research [ 32 , 34 ], we systematically examine the 47 definitions to deduce a general definition for open banking and interpret the results.

3.1. Bibliometric analysis

3.1.1. analytical approach..

Bibliometrics refers to the field that investigates groups of publications applying quantitative analysis methods [ 35 ]. Although this technique was initiated during the 1950–1960 period, it gained traction in the last two decades with the emergence of large electronic databases of academic articles, such as Web of Science (WoS) and Scopus, and the generalization of bibliometric analytics software packages, such as Gephi, Leximancer, and VOSviewer [ 36 ].

Bibliometric analysis techniques can be divided into three prominent families according to their goal [ 37 ]: techniques for establishing a relationship between authors (co-author analysis), techniques that aim at establishing a relationship between publications (citation analysis, co-citation analysis, and bibliographic coupling), and techniques for defining relationships within the content of selected publications (co-word analysis). Considering the relative novelty of the topic under consideration and the lack of consolidation of the academic sources considered, this study focuses on co-word analysis to identify the underlying constructs of the open banking concept.

From an analytical point of view, core techniques of bibliometric analysis can be divided into performance analysis and science mapping [ 37 ]. As an evolution of science mapping core techniques, enrichment techniques allow outcome augmentation to produce more advanced insights. This study applies clustering and visualization, both enrichment techniques, to perform a co-word analysis on the dataset that comprises all relevant open banking academic literature. Co-word analysis clustering and visualization techniques’ output is a network of topics and their associations, which represent the conceptual domain of a research field. Although clustering and visualization techniques are conceptually different, they usually go hand in hand [ 37 ]. In this study, they are applied simultaneously to analyze the dataset.

3.1.2. Dataset building and process.

Although the first open banking regulation was approved in 2017 in the UK, the concept’s origins are uncertain. Simon Redfern founded the Open Bank Project in 2012 [ 38 ]. But even before that, academic articles have been containing references to “open finance” and “financial aggregation” since 2002 [ 39 ]. Consequently, our database includes articles about “open banking” since 2002.

The initial dataset consists of 990 documents identified through a search in the Google Scholar database for articles using “open banking” as a keyword, conducted on August 6, 2021. The search is carried out through the Publish or Perish software tool.

Since its launch in 2004, Google Scholar has positioned itself as the most comprehensive academic citations database compared with alternative options such as WoS or Scopus, especially for humanities and social sciences [ 40 ]. However, Google Scholar contains articles not published in peer-reviewed journals, which requires additional filtering to ensure the quality of the database. Thus, Publish or Perish is commonly used in bibliometric analysis to filter academic publications databases [ 40 ].

Only documents written in English are selected due to the clustering analysis’ language requirements (663 articles). Two filters are subsequently applied: documents containing “open banking” in the title (92 papers) and records that contained “open banking” in the abstract and that had at least one citation (264 documents), obtaining 356 articles. To include articles with at least one citation is a potential quality filter of literature referenced in Google Scholar and is consistent with academic procedures [ 41 , 42 ] and recent bibliometric publications on the topic [ 14 ]. An additional check is performed to ensure that all the articles referenced in Scopus and WoS related to the topic are contained in the filtered database. After that, the remaining papers are fully read with two objectives. First, on the bibliometric side, to reject false positives of the combination of the words “open” and “banking,” obtaining the final list of 282 documents from 2002 to 2021 ( Fig 2 ). The resulting dataset is uploaded to RefWorks, a commonly used reference manager software [ 26 ]. Second, on the content analysis approach, to extract all the definitions of “open banking” included in the dataset. Forty-eight definitions of “open banking,” transcribed in Tables 3–5 of S1 Annex , are identified and recorded in an excel database ( S1 Annex ) [ 42 ].

https://doi.org/10.1371/journal.pone.0275496.g002

Due to limitations in obtaining full-text searchable versions of all the articles in the dataset, co-wording analysis is performed only on the titles and abstracts. This approach is consistent with existing bibliometric techniques as described in the literature [ 36 ]. These 282 articles yield 5,000 terms; out of which only those with five or more occurrences are selected (377). Ten generic terms (article, case, case study, chapter, example, interview, number, paper, study, and year) are removed from the selection, finishing with 367 terms. These terms are clustered, defining a minimum size of 25 items per cluster to avoid micro fragmentation of clusters. This process results in four clusters discussed in the results section. The normalization method applied is Linear / Logarithmic, and the proposed visualization layer is built using an attraction parameter of 3 and a rejection parameter of 0. The minimum cluster size is set at 25 [ 43 ], and the iterations number is set at 50.

3.2. Discourse analysis

During the bibliometric analysis dataset-building process, 47 definitions of “open banking” are identified. Each one of them appears in just one article. Although only three articles [ 14 , 15 , 32 ] are devoted to defining open banking, most articles dealing with the topic leveraged idiosyncratic or working definitions. The definitions are extracted and systematically analyzed from two perspectives.

First, a semantic approach is used to understand the role of each definition component. Eight semantic/grammatical elements are identified by applying an inductive approach: Nature, Consent, Subject, Action, Object, Recipient, Process, and Purpose. These eight elements constitute our proposal of an “open banking integrated definition framework,” which is discussed in detail in the Results section.

Second, to test the framework’s robustness, a descriptive statistics approach is applied to understand (i) the degree of completion of the definitions identified according to the proposed framework and (ii) the level of convergence/dispersion in the definitions. HHI is applied to the definitions to assess the convergence/dispersion within each element.

In our case, we calculate HHI for each conceptual field identified in the definitions. For each of the eight elements, if the 47 definitions used the same concept, HHI would yield a 10,000 (maximum value). If different concepts were used by the 47 definitions, HHI would be 212.8 [47 x (100/47) 2 ].

4.1. Bibliometric analysis and main research trends

As previously mentioned, open banking is a relatively new term in academic literature. The first time it appeared in academic literature fully aligned with the current interpretation was in 2009, but it started to take-off after 2016. The data for 2020 and 2021 ( Fig 2 ) might be affected by the criteria of choosing auxiliary publications that were cited at least once.

Regarding the nature of the documents, the dataset is highly heterogeneous: 20.2% documents [ 57 ] are articles published in Scopus rated journals; 5.0% [ 14 ] are Scopus-listed conference proceedings, and the remaining 211 are primarily reports, books or book sections, and academic dissertations ( Fig 3 ).

https://doi.org/10.1371/journal.pone.0275496.g003

It is worth noting that despite the limited academic relevance of existing literature, it is evolving toward more journal publications and Scopus-listed conference proceedings, implying higher relevance within the academic community ( Fig 4 ).

https://doi.org/10.1371/journal.pone.0275496.g004

Although the main field of study for open banking, following Scopus classification, is Business , Management , and Accounting , interest in the phenomenon is growing in other disciplines, too. In fact, in 2020, Business , Management , and Accounting accounted for 30.2% of the documents published, Computer Sciences accounted for 27.1%, Social Science–Law accounted for 14.6%, Economics , Econometrics , and Finance accounted for 11.5%, and other fields ( Medicine , Engineering , Social Science–Other ) accounted for 16.7% ( Fig 5 ).

https://doi.org/10.1371/journal.pone.0275496.g005

Observation 1.1. While the interest of academia in the open banking phenomenon is still limited, it is growing significantly over the last few years.

Observation 1.2 The quality of academic literature analyzing open banking is increasing, with a higher number and proportion of publications in higher-rated magazines.

Observation 1.3 Open banking is a multidisciplinary phenomenon that is being studied by several disciplines.

4.2. Clustering analysis and main conceptual domains (drivers) of open banking

Through the application of the VoS algorithm, four clusters are identified ( Fig 6 ). These clusters are groups of keywords that appear in at least five documents. Table 1 summarizes the top 10 keywords for each cluster.

https://doi.org/10.1371/journal.pone.0275496.g006

https://doi.org/10.1371/journal.pone.0275496.t001

Before coding, both researchers agreed on the coding method: based on heuristics, assigning to the cluster a description that explained at least 50% terms included in each cluster. Both researchers performed independent coding, and the results were compared and discussed to obtain the proposed interpretation.

Cluster 1 ( Business model platformization ): the initial list included both “bank” and “banking,” and both terms were consolidated. Here, open banking could be interpreted as the transformation process of the retail banking business model toward a platform leveraging API technology and fostering innovation.

Cluster 2 ( Data sharing ): summarizes the main open banking features: a new framework involving data (information) sharing and opening the banking market to competition, which poses new challenges and risks for legacy players.

Cluster 3 ( Fintech ): summarizes the ecosystem impact of the fintech phenomenon as a new competitor for financial institutions. From the initial outcome of the analysis, several generic keywords were removed for interpretation purposes: “research,” “impact,” “use,” “level,” “role,” “factor,” and “effect.” Additionally, “service” was consolidated with “financial services” for clarity.

Cluster 4 ( Regulation ): reflects the regulatory side, focusing on the legal and jurisdictional implications.

Observation 2.1.

Open banking as a research field is built on four domains: business model platformization, data sharing, fintech, and regulation, all of which can be interpreted as different connotations of open banking.

Observation 2.2.

Each identified cluster has a strong relationship with different knowledge domains.

Observation 2.3.

Clustering analysis confirms the adequacy of a multidisciplinary approach, considering the heterogeneous nature of the phenomenon and the associated literature.

4.3. Analysis of open banking definitions

Next, the final 282-document dataset was manually read, searching for formal or idiosyncratic definitions of open banking, the result of which is 47 definitions ( S1 Annex ; Tables 3–5)

Existing literature does not provide a framework to analyze “open banking” or similar definitions. Following similar approaches in the academic literature [ 45 , 46 ], the authors proceed to build an ad-hoc framework: the “open banking integrated definition framework” based on induction from the 47 existing definitions. This process identifies eight elements in which all current definitions can be decomposed.

The definitions are then decomposed into eight elements categorized into the following three blocks and analyzed to deduce a general definition of open banking constituting the “open banking integrated definition framework”: (i) Conceptual elements: Nature ( How can the phenomenon be classified ?) and Consent ( What is the enforceability ?), (ii) Core attributes: Subject: ( Who is the actor ?); Action ( What is expected from the Subject ?); Object ( What is the target of the Action ); Recipient ( Who is affected by the Action ?) and Process ( How does the Subject interact with the Object and with the Recipient ?), (iii) Purpose ( What is the final goal ?).

After applying the proposed framework to the 47 definitions, we find that 79% contain five or more elements of the definitions ( Fig 7 ), which implies significant robustness of the proposed framework.

https://doi.org/10.1371/journal.pone.0275496.g007

Table 2 shows the three primary outcomes for each element and the percentage of definitions containing the term. Not surprisingly, the level of consensus calculated through the HHI varies significantly across concepts. Additionally, for each element, the table contains the percentage of definitions that contain the element.

https://doi.org/10.1371/journal.pone.0275496.t002

Starting with the conceptual elements, there are two different perspectives: the regulatory approach , where open banking is understood as a legal construct, and the framework approach , which focuses on the interactions between players, regardless of the regulation. This duality is compatible with the fact that there are specific open banking regulations in some geographical areas (UK, Europe, and Australia). In contrast, in other regions (US and Canada), open banking exists as a phenomenon but without a specific regulation in place yet. We find a tight relationship between Nature and Consent , considering that regulation implies requirement, obligation, or empowerment, while framework implies enablement.

Regarding core attributes, the main keywords are “sharing” for Action and “APIs” for Process . Nevertheless, the interpretation of both should be significantly different. Regarding Action , there is a high consensus among all definitions around “sharing,” which is consubstantial with the very notion of open banking as currently understood by practitioners [ 47 ]. However, talking about Process , although currently, APIs are the most common system interface technology, the open banking phenomenon could be perfectly conceived by leveraging different interface technologies such as screen scraping [ 48 ]. That is why API should be deemed a relevant yet not essential element in the definition of open banking.

As for Subject , there is a low degree of consensus: 30.6% definitions are built around “ customer ,” 25.0% around “ banks ” (including synonyms such as “ financial institutions ”), and 19.4% around “ third parties .” This lack of convergence emerges from the fact that open banking can be formulated under three perspectives: the client perspective: “ customers–share ,” institutional perspective: “ banks–make available ,” and ecosystem perspective: “ third parties–access .” However, it is still unclear which approach is better. Nevertheless, the fact is that comparing roles of the three main actors in the open banking process, banks are passive agents, and their only function is to facilitate access to data. Similarly, third parties such as fintechs, for that matter any third party, cannot force a customer to enter into an open banking relationship with a banking client. That is why the client perspective seems crucial to understanding the essence of open banking as a “right to share” rather than a “right to access.”

The Object of open banking is also unclear, ranging from “ data” to “ applications and services . ” Lastly, concerning the Recipient , there are different levels of concretion, from a general conception (“ third parties ”) to specific type players ( “fintechs” ). There is, however, one open matter, “payments initiation.” Apart from data sharing, some regulations also include payment initiation as an object of open banking (e.g., UK, EU, India, and Brazil). However, there are minimal academic literature references to this matter. Thus, we will attach to the mainstream definitions of open banking as data sharing.

Finally, the Purpose element is highly undefined. Although “transparency” and “ competition” appear in several cases, there is no convergence in the final goal of open banking in any of the analyzed definitions.

In sum, although consensus around different elements of open banking is limited, it could be defined as “a generally regulated framework that enables banking customers to share their data with third parties, commonly through standardized interfaces such as APIs, to increase competition in the financial sector.” The proposed definition covers the eight elements identified in the proposed open banking integrated framework and could be understood as a generalization of all the analyzed partial definitions.

Observation 3.1.

There is neither a single definition of open banking in the academic literature nor a specific definition by knowledge domain. Instead, there is a collection of idiosyncratic and paper-specific approaches toward its definition.

Observation 3.2.

Among existing definitions, there are strong commonalities in some elements, while others show a high degree of dispersion. These differences arise mainly from different knowledge domains through which open banking is analyzed and various jurisdictions where it occurs.

Observation 3.3.

Despite underlying divergences, a standard definition of open banking can be formulated and leveraged in all conceptual domains based on the proposed approach.

Observation 3.4.

Despite customers playing a central role in different definitions of open banking as the owner of data, decision-maker of data sharing, and target of the framework’s purpose, one key element where prior research lacks consensus and focus is the role of a banking customer within open banking. Only 30.6% definitions are built around the word “client” (compared with 25.0% definitions that are built around “banks” and 19.4% around “third parties”).

5. Discussion and conclusions

Our bibliometric analysis confirms the academic community’s limited but growing interest in open banking and the challenges of a multidisciplinary approach to the phenomenon. Together with the intrinsic fragmentation in the analysis of the phenomenon due to its regulatory facets, both elements result in a corpus of literature that is still getting consolidated but lacks some foundations for further development.

Based on the clustering analysis’ results of the nascent literature, four conceptual clusters have been identified. These are (i) the platformization of the retail banking industry business model; (ii) a manifestation of the overall data sharing trend applied to the banking data; (iii) the interaction between the emergent fintech ecosystem and incumbent financial institutions; and (iv) the regulatory framework that, in some jurisdictions, bolsters the open banking phenomenon. These four clusters can be interpreted as different connotations underpinning the concept of “open banking.” Hence, the complex nature of open banking is a considerable challenge for future literature development, as partial analysis of the phenomenon will yield limited conclusions. Thus, only multidisciplinary approaches will offer good insights.

A clustering analysis to identify the conceptual domains around the open banking definition is also a valuable contribution. As an unsupervised learning methodology, clustering analysis returns an objective output, eliminating pre-classification biases. Moreover, the clustering approach unveils all the critical factors behind the open banking concept, supporting our proposal of an integrative definition valid across all disciplines and realizations of open banking. Consequently, although there are strong linkages between Cluster 1 (Business model/Platform), Cluster 4 (Regulation), and the academic literature emanating from Business Management and Social Sciences-Law, respectively, Cluster 2 (Data sharing) and Cluster 3 (Fintech) unveil purely transversal conceptual domains, multidisciplinary in nature that do not match with a single academic field and that could not have been identified without the clustering approach.

The detailed analysis of the 47 identified idiosyncratic and working definitions of the phenomenon confirms the need for a generalized conceptualization that amalgamates all existing perspectives on the topic. The proposed framework arising from the definition analysis is by itself a valuable tool for understanding the depth of open banking and the importance of identifying all relevant components that intervene in its dynamics. It is also important to note that the different formulations for the Subject of open banking constitute three perspectives of the phenomenon. These include (i) the “institutional perspective,” which analyzes open banking based on the obligations to comply with banking regulation; (ii) the “ecosystem perspective,” which focuses on the potential mechanics and benefits for new entrants, especially fintechs, from accessing banking clients’ data; and (iii) the “client perspective,” which studies the fundamental data-sharing right that constitutes the basis of open banking. Although the literature has not been explicit on this matter, researchers need to understand the implications of each positioning.

This study contributes to filling the literature gap with a potential generalized multidisciplinary open banking definition. Our proposed definition encompasses the four conceptual domains identified through the cluster analysis of the existing literature. Further, our proposed definition contributes to synthesizing different approaches, serving as a catalyzer for further research on the topic and significantly enhancing multidisciplinary approaches to the question.

Our proposed generalized definition should help increase collaboration among researchers from different academic disciplines and cooperation among researchers in different geographies to analyze the open banking phenomenon. Additionally, the proposed definition is especially relevant for policymakers and private economic agents, considering current ongoing discussions around the evolution of open banking regulation. Finally, the generalization of the open banking concept is also relevant for end customers as data owners and primary beneficiaries of open banking regulations.

The main limitation of this analysis is the emergent nature of the existing literature. Although several quality filters have been applied to the inputs to ensure the quality of the outcomes, this approach could be replicated in the future on articles published in peer-reviewed journals once a sufficient corpus of high-quality literature has been developed.

Supporting information

S1 annex. open banking definitions [ 2 , 5 , 9 , 13 – 17 , 19 , 24 , 26 , 31 , 32 , 48 – 81 ]..

https://doi.org/10.1371/journal.pone.0275496.s001

S2 Annex. Analytical approach [ 82 – 84 ].

https://doi.org/10.1371/journal.pone.0275496.s002

S1 File. Cluster map.

https://doi.org/10.1371/journal.pone.0275496.s003

S2 File. Cluster network.

https://doi.org/10.1371/journal.pone.0275496.s004

S3 File. Terms thesaurus.

https://doi.org/10.1371/journal.pone.0275496.s005

https://doi.org/10.1371/journal.pone.0275496.s006

• View Article
• Google Scholar
• 3. Ziegler T. Implementation of open banking protocols around the world. In: Rau R, Wardrop R, Zingales L, editors. The Palgrave Handbook of Technological Finance. Cham: Springer International Publishing; 2021. p. 751–779.
• 8. Gozman D, Hedman J, Sylvest K. Open banking: emergent roles, risks & opportunities. 26th European Conference on Information Systems (ECIS 2018). 2018; Jun 23–28; Portsmouth, UK. Association for Information Systems; 2018. Available from: https://aisel.aisnet.org/ecis2018_rp/183
• 9. Brodsky L, Oakes L. Data sharing and open banking. McKinsey & Company, Inc; Sep 5 2017 [cited 2022 Sep 17]. Available from: https://www.mckinsey.com/industries/financial-services/our-insights/data-sharing-and-open-banking
• PubMed/NCBI
• 14. O’Leary K, O’Reilly P, Nagle T, Papadopoulos-Filelis C, Dehghani M. The sustainable value of open banking: insights from an open data lens. Proceedings of the 54th Hawaii International Conference on System Sciences. 2021; Jan 4–8. Honolulu: University of Hawai’i at Manoa; 2021. p. 5891–5901. https://doi.org/10.24251/HICSS.2021.713
• 23. Long G, Tan Y, Jiang J, Zhang C. Federated Learning for Open Banking. In: Yang Q, Fan L, Yu H, editors. Federated Learning. Lecture Notes in Computer Science, vol 12500. Germany: Springer, Cham; 2020. p. 240–254. https://doi.org/10.1007/978-3-030-63076-8_17
• 26. Chan RSO. Open Banking: does it open up a new way of banking? A case of financial technology adoption from a consumer’s perspective [dissertation]. Adelaide: University of Adelaide; 2020 [cited 2022 Sep 17]. Available from: https://trove.nla.gov.au/work/240894619
• 33. Wodak R, Meyer M. Methods for critical discourse analysis. London: SAGE Publications; 2009.
• 47. Brodsky L, Ip C, Lundberg T. Open banking’s next wave: Perspectives from three fintech CEOs. McKinsey & Company, Inc; 2018 Aug 20 [cited 2022 Sep 17]. Available from: https://www.mckinsey.com/industries/financial-services/our-insights/open-bankings-next-wave-perspectives-from-three-fintech-ceos
• 56. Plaitakis A, Staschen S. Open banking: How to design for financial inclusion. Washington, D.C.: Consultative Group to Assist the Poor; 2020 Oct [cited 2022 Sep 17]. Available from: https://www.cgap.org/sites/default/files/publications/2020_10_Working_Paper_Open_Banking.pdf
• 65. Arslanian H, Fischer F. Fintech and the future of the financial ecosystem. In: Anonymous The Future of Finance. Cham: Springer International Publishing; 2019. p. 201–216.
• 70. Fett D, Hosseyni P, Küsters R. An extensive formal security analysis of the OpenID financial-grade API. 019 IEEE Symposium on Security and Privacy (SP); May 19, 2019; San Francisco, United States. IEEE; May 2019. https://doi.org/10.1109/SP.2019.00067
• 76. Eccles P, Grout P, Siciliani P. Open banking and capital requirements. Frankfurt, Germany: European Central Bank; 2019 March 19 [cited 2022 Sep 17]. Available from: https://www.ecb.europa.eu/pub/conferences/shared/pdf/20190328_financial_intermediation/Session1_continued_open_banking_capital_requirements.pdf
• 78. Bascand GM. Banking the economy in post-COVID Aotearoa. Wellington, N.Z: Reserve Bank of New Zealand Te Pūtea Matua; 2020 Jul 31 [cited 2022 Sep 17]. Available from: https://www.rbnz.govt.nz/-/media/5180f4d05752415d8fa1c10b09bca1b7.ashx?sc_lang=en

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Digital Banking in India: A Review of Trends, Opportunities and Challenges

The banking sector has been the backbone of every economy whether developed or emerging. It plans and implements the economic reforms. Any change in this sector through the adoption of technology will have an extensive impact on an economy " s growth. Nowadays, banks are seeking unconventional ways to provide and differentiate amongst their diverse services. Both corporate as well as retail customers are no longer willing to queue in banks, or wait on the phone, for the basic banking services. They require and expect a facility to conduct their banking activities at any time and place. Plastic money (Credit Cards, Debit Cards and Smart Cards); internet banking including electronic payment services, online investments, online trading accounts, electronic fund transfer and clearing services, branch networking; telephone banking; mobile applications and wallet are some of the recent products and services acting as the drivers to the growth of banking sector. Towards this, the paper aims to examine the recent digital banking trends in India along with identifying the challenges faced by banks in incorporating these digital banking trends. The study is analytical and based on secondary data. The concept of digital banking is still evolving in the Indian banking sector and is likely to bring numerous opportunities as well as unprecedented risks to the fundamental nature of banking in India. Thus, this paper also aims to present the opportunities and challenges of going digital in the Indian banking sector alongwith some recommendations to overcome these challenges. The paper concludes that in future, digital banking will not only be acceptable but the most demanded mode of conducting transactions. It will be useful to the academicians, banking and insurance personnel, financial advisors, professionals, students and researchers.

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Digital transformation is changing every industry and unsurprisingly banking is at the forefront of this trend. Banks need to improve the customer experience, increase operational efficiency and respond faster to changing business environments. Digital technology is dramatically changing how banks interact with their customers. In just a few years, the financial services industry has evolved from traditional brick-and-mortar operations to online bill payment and deposits to the emerging world of mobile banking. Two trends enabled by digital technology are at the heart of this transformation. One is the growing incursion of new, non-bank players into the industry. The second trend is the emergence of customer experience as a central consideration for banks as they create and execute their competitive strategies. They want digital banking to be as easy and seamless as ordering an item online or booking a flight with a mobile app. There has already seen major disruptive trends in the banking sector and these trends are set to accelerate. Banking customers' preferences and expectations are fragile in nature. There is a great amount of interest from banks how they can use block chain technology. It is not only seem to present huge opportunities and provide potential to improve processes to enable customers to transact more efficiently but also to combat fraud and money laundering. In this context the researcher intended to study the pulse and prospectus of digital banking and also the suspecting factors in the minds of the customers.

A revolutionary change has taken place in our financial set up with the digitalisation of the payment system. With time, this has been moulded again and again in an unending process to come up with newer modes of electronic transactions and payments. However the result of the effort put into by the system for this purpose is far from satisfactory with the probable reason being widespread alienation from this entire modernised set up. This paper would dwell into the various modes of electronic transactions and payments. Further, the study would stress on the consumer attitude towards such electronic transactions and payments and would try to bring out any difficulties faced by a person with ordinary knowledge while performing electronic transactions in the North Eastern region of India. This initiative will only see success when such hindrances would be overcome with wider public participation in this digitalisation movement at every corner of the country.

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• Published: 03 September 2022

A literature review of risk, regulation, and profitability of banks using a scientometric study

• Shailesh Rastogi 1 ,
• Arpita Sharma 1 ,
• Geetanjali Pinto 2 &
• Venkata Mrudula Bhimavarapu   ORCID: orcid.org/0000-0002-9757-1904 1 , 3  

Future Business Journal volume  8 , Article number:  28 ( 2022 ) Cite this article

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This study presents a systematic literature review of regulation, profitability, and risk in the banking industry and explores the relationship between them. It proposes a policy initiative using a model that offers guidelines to establish the right mix among these variables. This is a systematic literature review study. Firstly, the necessary data are extracted using the relevant keywords from the Scopus database. The initial search results are then narrowed down, and the refined results are stored in a file. This file is finally used for data analysis. Data analysis is done using scientometrics tools, such as Table2net and Sciences cape software, and Gephi to conduct network, citation analysis, and page rank analysis. Additionally, content analysis of the relevant literature is done to construct a theoretical framework. The study identifies the prominent authors, keywords, and journals that researchers can use to understand the publication pattern in banking and the link between bank regulation, performance, and risk. It also finds that concentration banking, market power, large banks, and less competition significantly affect banks’ financial stability, profitability, and risk. Ownership structure and its impact on the performance of banks need to be investigated but have been inadequately explored in this study. This is an organized literature review exploring the relationship between regulation and bank performance. The limitations of the regulations and the importance of concentration banking are part of the findings.

Introduction

Globally, banks are under extreme pressure to enhance their performance and risk management. The financial industry still recalls the ignoble 2008 World Financial Crisis (WFC) as the worst economic disaster after the Great Depression of 1929. The regulatory mechanism before 2008 (mainly Basel II) was strongly criticized for its failure to address banks’ risks [ 47 , 87 ]. Thus, it is essential to investigate the regulation of banks [ 75 ]. This study systematically reviews the relevant literature on banks’ performance and risk management and proposes a probable solution.

Issues of performance and risk management of banks

Banks have always been hailed as engines of economic growth and have been the axis of the development of financial systems [ 70 , 85 ]. A vital parameter of a bank’s financial health is the volume of its non-performing assets (NPAs) on its balance sheet. NPAs are advances that delay in payment of interest or principal beyond a few quarters [ 108 , 118 ]. According to Ghosh [ 51 ], NPAs negatively affect the liquidity and profitability of banks, thus affecting credit growth and leading to financial instability in the economy. Hence, healthy banks translate into a healthy economy.

Despite regulations, such as high capital buffers and liquidity ratio requirements, during the second decade of the twenty-first century, the Indian banking sector still witnessed a substantial increase in NPAs. A recent report by the Indian central bank indicates that the gross NPA ratio reached an all-time peak of 11% in March 2018 and 12.2% in March 2019 [ 49 ]. Basel II has been criticized for several reasons [ 98 ]. Schwerter [ 116 ] and Pakravan [ 98 ] highlighted the systemic risk and gaps in Basel II, which could not address the systemic risk of WFC 2008. Basel III was designed to close the gaps in Basel II. However, Schwerter [ 116 ] criticized Basel III and suggested that more focus should have been on active risk management practices to avoid any impending financial crisis. Basel III was proposed to solve these issues, but it could not [ 3 , 116 ]. Samitas and Polyzos [ 113 ] found that Basel III had made banking challenging since it had reduced liquidity and failed to shield the contagion effect. Therefore, exploring some solutions to establish the right balance between regulation, performance, and risk management of banks is vital.

Keeley [ 67 ] introduced the idea of a balance among banks’ profitability, regulation, and NPA (risk-taking). This study presents the balancing act of profitability, regulation, and NPA (risk-taking) of banks as a probable solution to the issues of bank performance and risk management and calls it a triad . Figure  1 illustrates the concept of a triad. Several authors have discussed the triad in parts [ 32 , 96 , 110 , 112 ]. Triad was empirically tested in different countries by Agoraki et al. [ 1 ]. Though the idea of a triad is quite old, it is relevant in the current scenario. The spirit of the triad strongly and collectively admonishes the Basel Accord and exhibits new and exhaustive measures to take up and solve the issue of performance and risk management in banks [ 16 , 98 ]. The 2008 WFC may have caused an imbalance among profitability, regulation, and risk-taking of banks [ 57 ]. Less regulation , more competition (less profitability ), and incentive to take the risk were the cornerstones of the 2008 WFC [ 56 ]. Achieving a balance among the three elements of a triad is a real challenge for banks’ performance and risk management, which this study addresses.

Triad of Profitability, regulation, and NPA (risk-taking). Note The triad [ 131 ] of profitability, regulation, and NPA (risk-taking) is shown in Fig.  1

Triki et al. [ 130 ] revealed that a bank’s performance is a trade-off between the elements of the triad. Reduction in competition increases the profitability of banks. However, in the long run, reduction in competition leads to either the success or failure of banks. Flexible but well-expressed regulation and less competition add value to a bank’s performance. The current review paper is an attempt to explore the literature on this triad of bank performance, regulation, and risk management. This paper has the following objectives:

To systematically explore the existing literature on the triad: performance, regulation, and risk management of banks; and

To propose a model for effective bank performance and risk management of banks.

Literature is replete with discussion across the world on the triad. However, there is a lack of acceptance of the triad as a solution to the woes of bank performance and risk management. Therefore, the findings of the current papers significantly contribute to this regard. This paper collates all the previous studies on the triad systematically and presents a curated view to facilitate the policy makers and stakeholders to make more informed decisions on the issue of bank performance and risk management. This paper also contributes significantly by proposing a DBS (differential banking system) model to solve the problem of banks (Fig.  7 ). This paper examines studies worldwide and therefore ensures the wider applicability of its findings. Applicability of the DBS model is not only limited to one nation but can also be implemented worldwide. To the best of the authors’ knowledge, this is the first study to systematically evaluate the publication pattern in banking using a blend of scientometrics analysis tools, network analysis tools, and content analysis to understand the link between bank regulation, performance, and risk.

This paper is divided into five sections. “ Data and research methods ” section discusses the research methodology used for the study. The data analysis for this study is presented in two parts. “ Bibliometric and network analysis ” section presents the results obtained using bibliometric and network analysis tools, followed by “ Content Analysis ” section, which presents the content analysis of the selected literature. “ Discussion of the findings ” section discusses the results and explains the study’s conclusion, followed by limitations and scope for further research.

Data and research methods

A literature review is a systematic, reproducible, and explicit way of identifying, evaluating, and synthesizing relevant research produced and published by researchers [ 50 , 100 ]. Analyzing existing literature helps researchers generate new themes and ideas to justify the contribution made to literature. The knowledge obtained through evidence-based research also improves decision-making leading to better practical implementation in the real corporate world [ 100 , 129 ].

As Kumar et al. [ 77 , 78 ] and Rowley and Slack [ 111 ] recommended conducting an SLR, this study also employs a three-step approach to understand the publication pattern in the banking area and establish a link between bank performance, regulation, and risk.

Determining the appropriate keywords for exploring the data

Many databases such as Google Scholar, Web of Science, and Scopus are available to extract the relevant data. The quality of a publication is associated with listing a journal in a database. Scopus is a quality database as it has a wider coverage of data [ 100 , 137 ]. Hence, this study uses the Scopus database to extract the relevant data.

For conducting an SLR, there is a need to determine the most appropriate keywords to be used in the database search engine [ 26 ]. Since this study seeks to explore a link between regulation, performance, and risk management of banks, the keywords used were “risk,” “regulation,” “profitability,” “bank,” and “banking.”

Initial search results and limiting criteria

Using the keywords identified in step 1, the search for relevant literature was conducted in December 2020 in the Scopus database. This resulted in the search of 4525 documents from inception till December 2020. Further, we limited our search to include “article” publications only and included subject areas: “Economics, Econometrics and Finance,” “Business, Management and Accounting,” and “Social sciences” only. This resulted in a final search result of 3457 articles. These results were stored in a.csv file which is then used as an input to conduct the SLR.

Data analysis tools and techniques

This study uses bibliometric and network analysis tools to understand the publication pattern in the area of research [ 13 , 48 , 100 , 122 , 129 , 134 ]. Some sub-analyses of network analysis are keyword word, author, citation, and page rank analysis. Author analysis explains the author’s contribution to literature or research collaboration, national and international [ 59 , 99 ]. Citation analysis focuses on many researchers’ most cited research articles [ 100 , 102 , 131 ].

The.csv file consists of all bibliometric data for 3457 articles. Gephi and other scientometrics tools, such as Table2net and ScienceScape software, were used for the network analysis. This.csv file is directly used as an input for this software to obtain network diagrams for better data visualization [ 77 ]. To ensure the study’s quality, the articles with 50 or more citations (216 in number) are selected for content analysis [ 53 , 102 ]. The contents of these 216 articles are analyzed to develop a conceptual model of banks’ triad of risk, regulation, and profitability. Figure  2 explains the data retrieval process for SLR.

Data retrieval process for SLR. Note Stepwise SLR process and corresponding results obtained

Bibliometric and network analysis

Figure  3 [ 58 ] depicts the total number of studies that have been published on “risk,” “regulation,” “profitability,” “bank,” and “banking.” Figure  3 also depicts the pattern of the quality of the publications from the beginning till 2020. It undoubtedly shows an increasing trend in the number of articles published in the area of the triad: “risk” regulation” and “profitability.” Moreover, out of the 3457 articles published in the said area, 2098 were published recently in the last five years and contribute to 61% of total publications in this area.

Articles published from 1976 till 2020 . Note The graph shows the number of documents published from 1976 till 2020 obtained from the Scopus database

Source of publications

A total of 160 journals have contributed to the publication of 3457 articles extracted from Scopus on the triad of risk, regulation, and profitability. Table 1 shows the top 10 sources of the publications based on the citation measure. Table 1 considers two sets of data. One data set is the universe of 3457 articles, and another is the set of 216 articles used for content analysis along with their corresponding citations. The global citations are considered for the study from the Scopus dataset, and the local citations are considered for the articles in the nodes [ 53 , 135 ]. The top 10 journals with 50 or more citations resulted in 96 articles. This is almost 45% of the literature used for content analysis ( n  = 216). Table 1 also shows that the Journal of Banking and Finance is the most prominent in terms of the number of publications and citations. It has 46 articles published, which is about 21% of the literature used for content analysis. Table 1 also shows these core journals’ SCImago Journal Rank indicator and H index. SCImago Journal Rank indicator reflects the impact and prestige of the Journal. This indicator is calculated as the previous three years’ weighted average of the number of citations in the Journal since the year that the article was published. The h index is the number of articles (h) published in a journal and received at least h. The number explains the scientific impact and the scientific productivity of the Journal. Table 1 also explains the time span of the journals covering articles in the area of the triad of risk, regulation, and profitability [ 7 ].

Figure  4 depicts the network analysis, where the connections between the authors and source title (journals) are made. The network has 674 nodes and 911 edges. The network between the author and Journal is classified into 36 modularities. Sections of the graph with dense connections indicate high modularity. A modularity algorithm is a design that measures how strong the divided networks are grouped into modules; this means how well the nodes are connected through a denser route relative to other networks.

Network analysis between authors and journals. Note A node size explains the more linked authors to a journal

The size of the nodes is based on the rank of the degree. The degree explains the number of connections or edges linked to a node. In the current graph, a node represents the name of the Journal and authors; they are connected through the edges. Therefore, the more the authors are associated with the Journal, the higher the degree. The algorithm used for the layout is Yifan Hu’s.

Many authors are associated with the Journal of Banking and Finance, Journal of Accounting and Economics, Journal of Financial Economics, Journal of Financial Services Research, and Journal of Business Ethics. Therefore, they are the most relevant journals on banks’ risk, regulation, and profitability.

Location and affiliation analysis

Affiliation analysis helps to identify the top contributing countries and universities. Figure  5 shows the countries across the globe where articles have been published in the triad. The size of the circle in the map indicates the number of articles published in that country. Table 2 provides the details of the top contributing organizations.

Location of articles published on Triad of profitability, regulation, and risk

Figure  5 shows that the most significant number of articles is published in the USA, followed by the UK. Malaysia and China have also contributed many articles in this area. Table 2 shows that the top contributing universities are also from Malaysia, the UK, and the USA.

Key author analysis

Table 3 shows the number of articles written by the authors out of the 3457 articles. The table also shows the top 10 authors of bank risk, regulation, and profitability.

Fadzlan Sufian, affiliated with the Universiti Islam Malaysia, has the maximum number, with 33 articles. Philip Molyneux and M. Kabir Hassan are from the University of Sharjah and the University of New Orleans, respectively; they contributed significantly, with 20 and 18 articles, respectively.

However, when the quality of the article is selected based on 50 or more citations, Fadzlan Sufian has only 3 articles with more than 50 citations. At the same time, Philip Molyneux and Allen Berger contributed more quality articles, with 8 and 11 articles, respectively.

Keyword analysis

Table 4 shows the keyword analysis (times they appeared in the articles). The top 10 keywords are listed in Table 4 . Banking and banks appeared 324 and 194 times, respectively, which forms the scope of this study, covering articles from the beginning till 2020. The keyword analysis helps to determine the factors affecting banks, such as profitability (244), efficiency (129), performance (107, corporate governance (153), risk (90), and regulation (89).

The keywords also show that efficiency through data envelopment analysis is a determinant of the performance of banks. The other significant determinants that appeared as keywords are credit risk (73), competition (70), financial stability (69), ownership structure (57), capital (56), corporate social responsibility (56), liquidity (46), diversification (45), sustainability (44), credit provision (41), economic growth (41), capital structure (39), microfinance (39), Basel III (37), non-performing assets (37), cost efficiency (30), lending behavior (30), interest rate (29), mergers and acquisition (28), capital adequacy (26), developing countries (23), net interest margin (23), board of directors (21), disclosure (21), leverage (21), productivity (20), innovation (18), firm size (16), and firm value (16).

Keyword analysis also shows the theories of banking and their determinants. Some of the theories are agency theory (23), information asymmetry (21), moral hazard (17), and market efficiency (16), which can be used by researchers when building a theory. The analysis also helps to determine the methodology that was used in the published articles; some of them are data envelopment analysis (89), which measures technical efficiency, panel data analysis (61), DEA (32), Z scores (27), regression analysis (23), stochastic frontier analysis (20), event study (15), and literature review (15). The count for literature review is only 15, which confirms that very few studies have conducted an SLR on bank risk, regulation, and profitability.

Citation analysis

One of the parameters used in judging the quality of the article is its “citation.” Table 5 shows the top 10 published articles with the highest number of citations. Ding and Cronin [ 44 ] indicated that the popularity of an article depends on the number of times it has been cited.

Tahamtan et al. [ 126 ] explained that the journal’s quality also affects its published articles’ citations. A quality journal will have a high impact factor and, therefore, more citations. The citation analysis helps researchers to identify seminal articles. The title of an article with 5900 citations is “A survey of corporate governance.”

Page Rank analysis

Goyal and Kumar [ 53 ] explain that the citation analysis indicates the ‘popularity’ and ‘prestige’ of the published research article. Apart from the citation analysis, one more analysis is essential: Page rank analysis. PageRank is given by Page et al. [ 97 ]. The impact of an article can be measured with one indicator called PageRank [ 135 ]. Page rank analysis indicates how many times an article is cited by other highly cited articles. The method helps analyze the web pages, which get the priority during any search done on google. The analysis helps in understanding the citation networks. Equation  1 explains the page rank (PR) of a published paper, N refers to the number of articles.

T 1,… T n indicates the paper, which refers paper P . C ( Ti ) indicates the number of citations. The damping factor is denoted by a “ d ” which varies in the range of 0 and 1. The page rank of all the papers is equal to 1. Table 6 shows the top papers based on page rank. Tables 5 and 6 together show a contrast in the top ranked articles based on citations and page rank, respectively. Only one article “A survey of corporate governance” falls under the prestigious articles based on the page rank.

Content analysis

Content Analysis is a research technique for conducting qualitative and quantitative analyses [ 124 ]. The content analysis is a helpful technique that provides the required information in classifying the articles depending on their nature (empirical or conceptual) [ 76 ]. By adopting the content analysis method [ 53 , 102 ], the selected articles are examined to determine their content. The classification of available content from the selected set of sample articles that are categorized under different subheads. The themes identified in the relationship between banking regulation, risk, and profitability are as follows.

Regulation and profitability of banks

The performance indicators of the banking industry have always been a topic of interest to researchers and practitioners. This area of research has assumed a special interest after the 2008 WFC [ 25 , 51 , 86 , 114 , 127 , 132 ]. According to research, the causes of poor performance and risk management are lousy banking practices, ineffective monitoring, inadequate supervision, and weak regulatory mechanisms [ 94 ]. Increased competition, deregulation, and complex financial instruments have made banks, including Indian banks, more vulnerable to risks [ 18 , 93 , 119 , 123 ]. Hence, it is essential to investigate the present regulatory machinery for the performance of banks.

There are two schools of thought on regulation and its possible impact on profitability. The first asserts that regulation does not affect profitability. The second asserts that regulation adds significant value to banks’ profitability and other performance indicators. This supports the concept that Delis et al. [ 41 ] advocated that the capital adequacy requirement and supervisory power do not affect productivity or profitability unless there is a financial crisis. Laeven and Majnoni [ 81 ] insisted that provision for loan loss should be part of capital requirements. This will significantly improve active risk management practices and ensure banks’ profitability.

Lee and Hsieh [ 83 ] proposed ambiguous findings that do not support either school of thought. According to Nguyen and Nghiem [ 95 ], while regulation is beneficial, it has a negative impact on bank profitability. As a result, when proposing regulations, it is critical to consider bank performance and risk management. According to Erfani and Vasigh [ 46 ], Islamic banks maintained their efficiency between 2006 and 2013, while most commercial banks lost, furthermore claimed that the financial crisis had no significant impact on Islamic bank profitability.

Regulation and NPA (risk-taking of banks)

The regulatory mechanism of banks in any country must address the following issues: capital adequacy ratio, prudent provisioning, concentration banking, the ownership structure of banks, market discipline, regulatory devices, presence of foreign capital, bank competition, official supervisory power, independence of supervisory bodies, private monitoring, and NPAs [ 25 ].

Kanoujiya et al. [ 64 ] revealed through empirical evidence that Indian bank regulations lack a proper understanding of what banks require and propose reforming and transforming regulation in Indian banks so that responsive governance and regulation can occur to make banks safer, supported by Rastogi et al. [ 105 ]. The positive impact of regulation on NPAs is widely discussed in the literature. [ 94 ] argue that regulation has multiple effects on banks, including reducing NPAs. The influence is more powerful if the country’s banking system is fragile. Regulation, particularly capital regulation, is extremely effective in reducing risk-taking in banks [ 103 ].

Rastogi and Kanoujiya [ 106 ] discovered evidence that disclosure regulations do not affect the profitability of Indian banks, supported by Karyani et al. [ 65 ] for the banks located in Asia. Furthermore, Rastogi and Kanoujiya [ 106 ] explain that disclosure is a difficult task as a regulatory requirement. It is less sustainable due to the nature of the imposed regulations in banks and may thus be perceived as a burden and may be overcome by realizing the benefits associated with disclosure regulation [ 31 , 54 , 101 ]. Zheng et al. [ 138 ] empirically discovered that regulation has no impact on the banks’ profitability in Bangladesh.

Governments enforce banking regulations to achieve a stable and efficient financial system [ 20 , 94 ]. The existing literature is inconclusive on the effects of regulatory compliance on banks’ risks or the reduction of NPAs [ 10 , 11 ]. Boudriga et al. [ 25 ] concluded that the regulatory mechanism plays an insignificant role in reducing NPAs. This is especially true in weak institutions, which are susceptible to corruption. Gonzalez [ 52 ] reported that firm regulations have a positive relationship with banks’ risk-taking, increasing the probability of NPAs. However, Boudriga et al. [ 25 ], Samitas and Polyzos [ 113 ], and Allen et al. [ 3 ] strongly oppose the use of regulation as a tool to reduce banks’ risk-taking.

Kwan and Laderman [ 79 ] proposed three levels in regulating banks, which are lax, liberal, and strict. The liberal regulatory framework leads to more diversification in banks. By contrast, the strict regulatory framework forces the banks to take inappropriate risks to compensate for the loss of business; this is a global problem [ 73 ].

Capital regulation reduces banks’ risk-taking [ 103 , 110 ]. Capital regulation leads to cost escalation, but the benefits outweigh the cost [ 103 ]. The trade-off is worth striking. Altman Z score is used to predict banks’ bankruptcy, and it found that the regulation increased the Altman’s Z-score [ 4 , 46 , 63 , 68 , 72 , 120 ]. Jin et al. [ 62 ] report a negative relationship between regulation and banks’ risk-taking. Capital requirements empowered regulators, and competition significantly reduced banks’ risk-taking [ 1 , 122 ]. Capital regulation has a limited impact on banks’ risk-taking [ 90 , 103 ].

Maji and De [ 90 ] suggested that human capital is more effective in managing banks’ credit risks. Besanko and Kanatas [ 21 ] highlighted that regulation on capital requirements might not mitigate risks in all scenarios, especially when recapitalization has been enforced. Klomp and De Haan [ 72 ] proposed that capital requirements and supervision substantially reduce banks’ risks.

A third-party audit may impart more legitimacy to the banking system [ 23 ]. The absence of third-party intervention is conspicuous, and this may raise a doubt about the reliability and effectiveness of the impact of regulation on bank’s risk-taking.

NPA (risk-taking) in banks and profitability

Profitability affects NPAs, and NPAs, in turn, affect profitability. According to the bad management hypothesis [ 17 ], higher profits would negatively affect NPAs. By contrast, higher profits may lead management to resort to a liberal credit policy (high earnings), which may eventually lead to higher NPAs [ 104 ].

Balasubramaniam [ 8 ] demonstrated that NPA has double negative effects on banks. NPAs increase stressed assets, reducing banks’ productive assets [ 92 , 117 , 136 ]. This phenomenon is relatively underexplored and therefore renders itself for future research.

Triad and the performance of banks

Regulation and triad.

Regulations and their impact on banks have been a matter of debate for a long time. Barth et al. [ 12 ] demonstrated that countries with a central bank as the sole regulatory body are prone to high NPAs. Although countries with multiple regulatory bodies have high liquidity risks, they have low capital requirements [ 40 ]. Barth et al. [ 12 ] supported the following steps to rationalize the existing regulatory mechanism on banks: (1) mandatory information [ 22 ], (2) empowered management of banks, and (3) increased incentive for private agents to exert corporate control. They show that profitability has an inverse relationship with banks’ risk-taking [ 114 ]. Therefore, standard regulatory practices, such as capital requirements, are not beneficial. However, small domestic banks benefit from capital restrictions.

DeYoung and Jang [ 43 ] showed that Basel III-based policies of liquidity convergence ratio (LCR) and net stable funding ratio (NSFR) are not fully executed across the globe, including the US. Dahir et al. [ 39 ] found that a decrease in liquidity and funding increases banks’ risk-taking, making banks vulnerable and reducing stability. Therefore, any regulation on liquidity risk is more likely to create problems for banks.

Concentration banking and triad

Kiran and Jones [ 71 ] asserted that large banks are marginally affected by NPAs, whereas small banks are significantly affected by high NPAs. They added a new dimension to NPAs and their impact on profitability: concentration banking or banks’ market power. Market power leads to less cost and more profitability, which can easily counter the adverse impact of NPAs on profitability [ 6 , 15 ].

The connection between the huge volume of research on the performance of banks and competition is the underlying concept of market power. Competition reduces market power, whereas concentration banking increases market power [ 25 ]. Concentration banking reduces competition, increases market power, rationalizes the banks’ risk-taking, and ensures profitability.

Tabak et al. [ 125 ] advocated that market power incentivizes banks to become risk-averse, leading to lower costs and high profits. They explained that an increase in market power reduces the risk-taking requirement of banks. Reducing banks’ risks due to market power significantly increases when capital regulation is executed objectively. Ariss [ 6 ] suggested that increased market power decreases competition, and thus, NPAs reduce, leading to increased banks’ stability.

Competition, the performance of banks, and triad

Boyd and De Nicolo [ 27 ] supported that competition and concentration banking are inversely related, whereas competition increases risk, and concentration banking decreases risk. A mere shift toward concentration banking can lead to risk rationalization. This finding has significant policy implications. Risk reduction can also be achieved through stringent regulations. Bolt and Tieman [ 24 ] explained that stringent regulation coupled with intense competition does more harm than good, especially concerning banks’ risk-taking.

Market deregulation, as well as intensifying competition, would reduce the market power of large banks. Thus, the entire banking system might take inappropriate and irrational risks [ 112 ]. Maji and Hazarika [ 91 ] added more confusion to the existing policy by proposing that, often, there is no relationship between capital regulation and banks’ risk-taking. However, some cases have reported a positive relationship. This implies that banks’ risk-taking is neutral to regulation or leads to increased risk. Furthermore, Maji and Hazarika [ 91 ] revealed that competition reduces banks’ risk-taking, contrary to popular belief.

Claessens and Laeven [ 36 ] posited that concentration banking influences competition. However, this competition exists only within the restricted circle of banks, which are part of concentration banking. Kasman and Kasman [ 66 ] found that low concentration banking increases banks’ stability. However, they were silent on the impact of low concentration banking on banks’ risk-taking. Baselga-Pascual et al. [ 14 ] endorsed the earlier findings that concentration banking reduces banks’ risk-taking.

Concentration banking and competition are inversely related because of the inherent design of concentration banking. Market power increases when only a few large banks are operating; thus, reduced competition is an obvious outcome. Barra and Zotti [ 9 ] supported the idea that market power, coupled with competition between the given players, injects financial stability into banks. Market power and concentration banking affect each other. Therefore, concentration banking with a moderate level of regulation, instead of indiscriminate regulation, would serve the purpose better. Baselga-Pascual et al. [ 14 ] also showed that concentration banking addresses banks’ risk-taking.

Schaeck et al. [ 115 ], in a landmark study, presented that concentration banking and competition reduce banks’ risk-taking. However, they did not address the relationship between concentration banking and competition, which are usually inversely related. This could be a subject for future research. Research on the relationship between concentration banking and competition is scant, identified as a research gap (“ Research Implications of the study ” section).

Transparency, corporate governance, and triad

One of the big problems with NPAs is the lack of transparency in both the regulatory bodies and banks [ 25 ]. Boudriga et al. [ 25 ] preferred to view NPAs as a governance issue and thus, recommended viewing it from a governance perspective. Ahmad and Ariff [ 2 ] concluded that regulatory capital and top-management quality determine banks’ credit risk. Furthermore, they asserted that credit risk in emerging economies is higher than that of developed economies.

Bad management practices and moral vulnerabilities are the key determinants of insolvency risks of Indian banks [ 95 ]. Banks are an integral part of the economy and engines of social growth. Therefore, banks enjoy liberal insolvency protection in India, especially public sector banks, which is a critical issue. Such a benevolent insolvency cover encourages a bank to be indifferent to its capital requirements. This indifference takes its toll on insolvency risk and profit efficiency. Insolvency protection makes the bank operationally inefficient and complacent.

Foreign equity and corporate governance practices help manage the adverse impact of banks’ risk-taking to ensure the profitability and stability of banks [ 33 , 34 ]. Eastburn and Sharland [ 45 ] advocated that sound management and a risk management system that can anticipate any impending risk are essential. A pragmatic risk mechanism should replace the existing conceptual risk management system.

Lo [ 87 ] found and advocated that the existing legislation and regulations are outdated. He insisted on a new perspective and asserted that giving equal importance to behavioral aspects and the rational expectations of customers of banks is vital. Buston [ 29 ] critiqued the balance sheet risk management practices prevailing globally. He proposed active risk management practices that provided risk protection measures to contain banks’ liquidity and solvency risks.

Klomp and De Haan [ 72 ] championed the cause of giving more autonomy to central banks of countries to provide stability in the banking system. Louzis et al. [ 88 ] showed that macroeconomic variables and the quality of bank management determine banks’ level of NPAs. Regulatory authorities are striving hard to make regulatory frameworks more structured and stringent. However, the recent increase in loan defaults (NPAs), scams, frauds, and cyber-attacks raise concerns about the effectiveness [ 19 ] of the existing banking regulations in India as well as globally.

Discussion of the findings

The findings of this study are based on the bibliometric and content analysis of the sample published articles.

The bibliometric study concludes that there is a growing demand for researchers and good quality research

The keyword analysis suggests that risk regulation, competition, profitability, and performance are key elements in understanding the banking system. The main authors, keywords, and journals are grouped in a Sankey diagram in Fig.  6 . Researchers can use the following information to understand the publication pattern on banking and its determinants.

Sankey Diagram of main authors, keywords, and journals. Note Authors contribution using scientometrics tools

Research Implications of the study

The study also concludes that a balance among the three components of triad is the solution to the challenges of banks worldwide, including India. We propose the following recommendations and implications for banks:

This study found that “the lesser the better,” that is, less regulation enhances the performance and risk management of banks. However, less regulation does not imply the absence of regulation. Less regulation means the following:

Flexible but full enforcement of the regulations

Customization, instead of a one-size-fits-all regulatory system rooted in a nation’s indigenous requirements, is needed. Basel or generic regulation can never achieve what a customized compliance system can.

A third-party audit, which is above the country's central bank, should be mandatory, and this would ensure that all three aspects of audit (policy formulation, execution, and audit) are handled by different entities.

Competition

This study asserts that the existing literature is replete with poor performance and risk management due to excessive competition. Banking is an industry of a different genre, and it would be unfair to compare it with the fast-moving consumer goods (FMCG) or telecommunication industry, where competition injects efficiency into the system, leading to customer empowerment and satisfaction. By contrast, competition is a deterrent to the basic tenets of safe banking. Concentration banking is more effective in handling the multi-pronged balance between the elements of the triad. Concentration banking reduces competition to lower and manageable levels, reduces banks’ risk-taking, and enhances profitability.

No incentive to take risks

It is found that unless banks’ risk-taking is discouraged, the problem of high NPA (risk-taking) cannot be addressed. Concentration banking is a disincentive to risk-taking and can be a game-changer in handling banks’ performance and risk management.

Research on the risk and performance of banks reveals that the existing regulatory and policy arrangement is not a sustainable proposition, especially for a country where half of the people are unbanked [ 37 ]. Further, the triad presented by Keeley [ 67 ] is a formidable real challenge to bankers. The balance among profitability, risk-taking, and regulation is very subtle and becomes harder to strike, just as the banks globally have tried hard to achieve it. A pragmatic intervention is needed; hence, this study proposes a change in the banking structure by having two types of banks functioning simultaneously to solve the problems of risk and performance of banks. The proposed two-tier banking system explained in Fig.  7 can be a great solution. This arrangement will help achieve the much-needed balance among the elements of triad as presented by Keeley [ 67 ].

Conceptual Framework. Note Fig.  7 describes the conceptual framework of the study

The first set of banks could be conventional in terms of their structure and should primarily be large-sized. The number of such banks should be moderate. There is a logic in having only a few such banks to restrict competition; thus, reasonable market power could be assigned to them [ 55 ]. However, a reduction in competition cannot be over-assumed, and banks cannot become complacent. As customary, lending would be the main source of revenue and income for these banks (fund based activities) [ 82 ]. The proposed two-tier system can be successful only when regulation especially for risk is objectively executed [ 29 ]. The second set of banks could be smaller in size and more in number. Since they are more in number, they would encounter intense competition for survival and for generating more business. Small is beautiful, and thus, this set of banks would be more agile and adaptable and consequently more efficient and profitable. The main source of revenue for this set of banks would not be loans and advances. However, non-funding and non-interest-bearing activities would be the major revenue source. Unlike their traditional and large-sized counterparts, since these banks are smaller in size, they are less likely to face risk-taking and NPAs [ 74 ].

Sarmiento and Galán [ 114 ] presented the concerns of large and small banks and their relative ability and appetite for risk-taking. High risk could threaten the existence of small-sized banks; thus, they need robust risk shielding. Small size makes them prone to failure, and they cannot convert their risk into profitability. However, large banks benefit from their size and are thus less vulnerable and can convert risk into profitable opportunities.

India has experimented with this Differential Banking System (DBS) (two-tier system) only at the policy planning level. The execution is impending, and it highly depends on the political will, which does not appear to be strong now. The current agenda behind the DBS model is not to ensure the long-term sustainability of banks. However, it is currently being directed to support the agenda of financial inclusion by extending the formal credit system to the unbanked masses [ 107 ]. A shift in goal is needed to employ the DBS as a strategic decision, but not merely a tool for financial inclusion. Thus, the proposed two-tier banking system (DBS) can solve the issue of profitability through proper regulation and less risk-taking.

The findings of Triki et al. [ 130 ] support the proposed DBS model, in this study. Triki et al. [ 130 ] advocated that different component of regulations affect banks based on their size, risk-taking, and concentration banking (or market power). Large size, more concentration banking with high market power, and high risk-taking coupled with stringent regulation make the most efficient banks in African countries. Sharifi et al. [ 119 ] confirmed that size advantage offers better risk management to large banks than small banks. The banks should modify and work according to the economic environment in the country [ 69 ], and therefore, the proposed model could help in solving the current economic problems.

This is a fact that DBS is running across the world, including in India [ 60 ] and other countries [ 133 ]. India experimented with DBS in the form of not only regional rural banks (RRBs) but payments banks [ 109 ] and small finance banks as well [ 61 ]. However, the purpose of all the existing DBS models, whether RRBs [ 60 ], payment banks, or small finance banks, is financial inclusion, not bank performance and risk management. Hence, they are unable to sustain and are failing because their model is only social instead of a much-needed dual business-cum-social model. The two-tier model of DBS proposed in the current paper can help serve the dual purpose. It may not only be able to ensure bank performance and risk management but also serve the purpose of inclusive growth of the economy.

Conclusion of the study

The study’s conclusions have some significant ramifications. This study can assist researchers in determining their study plan on the current topic by using a scientific approach. Citation analysis has aided in the objective identification of essential papers and scholars. More collaboration between authors from various countries/universities may help countries/universities better understand risk regulation, competition, profitability, and performance, which are critical elements in understanding the banking system. The regulatory mechanism in place prior to 2008 failed to address the risk associated with banks [ 47 , 87 ]. There arises a necessity and motivates authors to investigate the current topic. The present study systematically explores the existing literature on banks’ triad: performance, regulation, and risk management and proposes a probable solution.

To conclude the bibliometric results obtained from the current study, from the number of articles published from 1976 to 2020, it is evident that most of the articles were published from the year 2010, and the highest number of articles were published in the last five years, i.e., is from 2015. The authors discovered that researchers evaluate articles based on the scope of critical journals within the subject area based on the detailed review. Most risk, regulation, and profitability articles are published in peer-reviewed journals like; “Journal of Banking and Finance,” “Journal of Accounting and Economics,” and “Journal of Financial Economics.” The rest of the journals are presented in Table 1 . From the affiliation statistics, it is clear that most of the research conducted was affiliated with developed countries such as Malaysia, the USA, and the UK. The researchers perform content analysis and Citation analysis to access the type of content where the research on the current field of knowledge is focused, and citation analysis helps the academicians understand the highest cited articles that have more impact in the current research area.

Practical implications of the study

The current study is unique in that it is the first to systematically evaluate the publication pattern in banking using a combination of scientometrics analysis tools, network analysis tools, and content analysis to understand the relationship between bank regulation, performance, and risk. The study’s practical implications are that analyzing existing literature helps researchers generate new themes and ideas to justify their contribution to literature. Evidence-based research knowledge also improves decision-making, resulting in better practical implementation in the real corporate world [ 100 , 129 ].

Limitations and scope for future research

The current study only considers a single database Scopus to conduct the study, and this is one of the limitations of the study spanning around the multiple databases can provide diverse results. The proposed DBS model is a conceptual framework that requires empirical testing, which is a limitation of this study. As a result, empirical testing of the proposed DBS model could be a future research topic.

Availability of data and materials

SCOPUS database.

Abbreviations

Systematic literature review

World Financial Crisis

Non-performing assets

Differential banking system

SCImago Journal Rank Indicator

Liquidity convergence ratio

Net stable funding ratio

Fast moving consumer goods

Regional rural banks

Agoraki M-EK, Delis MD, Pasiouras F (2011) Regulations, competition and bank risk-taking in transition countries. J Financ Stab 7(1):38–48

Google Scholar  

Ahmad NH, Ariff M (2007) Multi-country study of bank credit risk determinants. Int J Bank Financ 5(1):35–62

Allen B, Chan KK, Milne A, Thomas S (2012) Basel III: Is the cure worse than the disease? Int Rev Financ Anal 25:159–166

Altman EI (2018) A fifty-year retrospective on credit risk models, the Altman Z-score family of models, and their applications to financial markets and managerial strategies. J Credit Risk 14(4):1–34

Alvarez F, Jermann UJ (2000) Efficiency, equilibrium, and asset pricing with risk of default. Econometrica 68(4):775–797

Ariss RT (2010) On the implications of market power in banking: evidence from developing countries. J Bank Financ 34(4):765–775

Aznar-Sánchez JA, Piquer-Rodríguez M, Velasco-Muñoz JF, Manzano-Agugliaro F (2019) Worldwide research trends on sustainable land use in agriculture. Land Use Policy 87:104069

Balasubramaniam C (2012) Non-performing assets and profitability of commercial banks in India: assessment and emerging issues. Nat Mon Refereed J Res Commer Manag 1(1):41–52

Barra C, Zotti R (2017) On the relationship between bank market concentration and stability of financial institutions: evidence from the Italian banking sector, MPRA working Paper No 79900. Last Accessed on Jan 2021 https://mpra.ub.uni-muenchen.de/79900/1/MPRA_paper_79900.pdf

Barth JR, Caprio G, Levine R (2004) Bank regulation and supervision: what works best? J Financ Intermed 2(13):205–248

Barth JR, Caprio G, Levine R (2008) Bank regulations are changing: For better or worse? Comp Econ Stud 50(4):537–563

Barth JR, Dopico LG, Nolle DE, Wilcox JA (2002) Bank safety and soundness and the structure of bank supervision: a cross-country analysis. Int Rev Financ 3(3–4):163–188

Bartolini M, Bottani E, Grosse EH (2019) Green warehousing: systematic literature review and bibliometric analysis. J Clean Prod 226:242–258

Baselga-Pascual L, Trujillo-Ponce A, Cardone-Riportella C (2015) Factors influencing bank risk in Europe: evidence from the financial crisis. N Am J Econ Financ 34(1):138–166

Beck T, Demirgüç-Kunt A, Levine R (2006) Bank concentration, competition, and crises: first results. J Bank Financ 30(5):1581–1603

Berger AN, Demsetz RS, Strahan PE (1999) The consolidation of the financial services industry: causes, consequences, and implications for the future. J Bank Financ 23(2–4):135–194

Berger AN, Deyoung R (1997) Problem loans and cost efficiency in commercial banks. J Bank Financ 21(6):849–870

Berger AN, Udell GF (1998) The economics of small business finance: the roles of private equity and debt markets in the financial growth cycle. J Bank Financ 22(6–8):613–673

Berger AN, Udell GF (2002) Small business credit availability and relationship lending: the importance of bank organisational structure. Econ J 112(477):F32–F53

Berger AN, Udell GF (2006) A more complete conceptual framework for SME finance. J Bank Financ 30(11):2945–2966

Besanko D, Kanatas G (1996) The regulation of bank capital: Do capital standards promote bank safety? J Financ Intermed 5(2):160–183

Beyer A, Cohen DA, Lys TZ, Walther BR (2010) The financial reporting environment: review of the recent literature. J Acc Econ 50(2–3):296–343

Bikker JA (2010) Measuring performance of banks: an assessment. J Appl Bus Econ 11(4):141–159

Bolt W, Tieman AF (2004) Banking competition, risk and regulation. Scand J Econ 106(4):783–804

Boudriga A, BoulilaTaktak N, Jellouli S (2009) Banking supervision and non-performing loans: a cross-country analysis. J Financ Econ Policy 1(4):286–318

Bouzon M, Miguel PAC, Rodriguez CMT (2014) Managing end of life products: a review of the literature on reverse logistics in Brazil. Manag Environ Qual Int J 25(5):564–584. https://doi.org/10.1108/MEQ-04-2013-0027

Article   Google Scholar  

Boyd JH, De Nicolo G (2005) The theory of bank risk taking and competition revisited. J Financ 60(3):1329–1343

Brealey RA, Myers SC, Allen F, Mohanty P (2012) Principles of corporate finance. Tata McGraw-Hill Education

Buston CS (2016) Active risk management and banking stability. J Bank Financ 72:S203–S215

Casu B, Girardone C (2006) Bank competition, concentration and efficiency in the single European market. Manch Sch 74(4):441–468

Charumathi B, Ramesh L (2020) Impact of voluntary disclosure on valuation of firms: evidence from Indian companies. Vision 24(2):194–203

Chen X (2007) Banking deregulation and credit risk: evidence from the EU. J Financ Stab 2(4):356–390

Chen H-J, Lin K-T (2016) How do banks make the trade-offs among risks? The role of corporate governance. J Bank Financ 72(1):S39–S69

Chen M, Wu J, Jeon BN, Wang R (2017) Do foreign banks take more risk? Evidence from emerging economies. J Bank Financ 82(1):20–39

Claessens S, Laeven L (2003) Financial development, property rights, and growth. J Financ 58(6):2401–2436. https://doi.org/10.1046/j.1540-6261.2003.00610.x

Claessens S, Laeven L (2004) What drives bank competition? Some international evidence. J Money Credit Bank 36(3):563–583

Cnaan RA, Moodithaya M, Handy F (2012) Financial inclusion: lessons from rural South India. J Soc Policy 41(1):183–205

Core JE, Holthausen RW, Larcker DF (1999) Corporate governance, chief executive officer compensation, and firm performance. J Financ Econ 51(3):371–406

Dahir AM, Mahat FB, Ali NAB (2018) Funding liquidity risk and bank risk-taking in BRICS countries: an application of system GMM approach. Int J Emerg Mark 13(1):231–248

Dechow P, Ge W, Schrand C (2010) Understanding earnings quality: a review of the proxies, their determinants, and their consequences. J Acc Econ 50(2–3):344–401

Delis MD, Molyneux P, Pasiouras F (2011) Regulations and productivity growth in banking: evidence from transition economies. J Money Credit Bank 43(4):735–764

Demirguc-Kunt A, Laeven L, Levine R (2003) Regulations, market structure, institutions, and the cost of financial intermediation (No. w9890). National Bureau of Economic Research.

Deyoung R, Jang KY (2016) Do banks actively manage their liquidity? J Bank Financ 66:143–161

Ding Y, Cronin B (2011) Popularand/orprestigious? Measures of scholarly esteem. Inf Process Manag 47(1):80–96

Eastburn RW, Sharland A (2017) Risk management and managerial mindset. J Risk Financ 18(1):21–47

Erfani GR, Vasigh B (2018) The impact of the global financial crisis on profitability of the banking industry: a comparative analysis. Economies 6(4):66

Erkens DH, Hung M, Matos P (2012) Corporate governance in the 2007–2008 financial crisis: evidence from financial institutions worldwide. J Corp Finan 18(2):389–411

Fahimnia B, Sarkis J, Davarzani H (2015) Green supply chain management: a review and bibliometric analysis. Int J Prod Econ 162:101–114

Financial Stability Report (2019) Financial stability report (20), December 2019. https://www.rbi.org.in/Scripts/PublicationReportDetails.aspx?UrlPage=&ID=946 Accesses on March 2020

Fink A (2005) Conducting Research Literature Reviews:From the Internet to Paper, 2nd edn. SAGE Publications

Ghosh A (2015) Banking-industry specific and regional economic determinants of non-performing loans: evidence from US states. J Financ Stab 20:93–104. https://doi.org/10.1016/j.jfs.2015.08.004

Gonzalez F (2005) Bank regulation and risk-taking incentives: an international comparison of bank risk. J Bank Financ 29(5):1153–1184

Goyal K, Kumar S (2021) Financial literacy: a systematic review and bibliometric analysis. Int J Consum Stud 45(1):80–105

Grassa R, Moumen N, Hussainey K (2020) Do ownership structures affect risk disclosure in Islamic banks? International evidence. J Financ Rep Acc 19(3):369–391

Haque F, Shahid R (2016) Ownership, risk-taking and performance of banks in emerging economies: evidence from India. J Financ Econ Policy 8(3):282–297

Hellmann TF, Murdock KC, Stiglitz JE (2000) Liberalization, moral hazard in banking, and prudential regulation: Are capital requirements enough? Am Econ Rev 90(1):147–165

Hirshleifer D (2001) Investor psychology and asset pricing. J Financ 56(4):1533–1597

Huang J, You JX, Liu HC, Song MS (2020) Failure mode and effect analysis improvement: a systematic literature review and future research agenda. Reliab Eng Syst Saf 199:106885

Ibáñez Zapata A (2017) Bibliometric analysis of the regulatory compliance function within the banking sector (Doctoral dissertation). Last Accessed on Jan 2021 https://riunet.upv.es/bitstream/handle/10251/85952/Bibliometric%20analysis_AIZ_v4.pdf?sequence=1

Ibrahim MS (2010) Performance evaluation of regional rural banks in India. Int Bus Res 3(4):203–211

Jayadev M, Singh H, Kumar P (2017) Small finance banks: challenges. IIMB Manag Rev 29(4):311–325

Jin JY, Kanagaretnam K, Lobo GJ, Mathieu R (2013) Impact of FDICIA internal controls on bank risk taking. J Bank Financ 37(2):614–624

Joshi MK (2020) Financial performance analysis of select Indian Public Sector Banks using Altman’s Z-Score model. SMART J Bus Manag Stud 16(2):74–87

Kanoujiya J, Bhimavarapu VM, Rastogi S (2021) Banks in India: a balancing act between profitability, regulation and NPA. Vision, 09722629211034417

Karyani E, Dewo SA, Santoso W, Frensidy B (2020) Risk governance and bank profitability in ASEAN-5: a comparative and empirical study. Int J Emerg Mark 15(5):949–969

Kasman S, Kasman A (2015) Bank competition, concentration and financial stability in the Turkish banking industry. Econ Syst 39(3):502–517

Keeley MC (1990) Deposit insurance, risk, and market power in banking. Am Econ Rev 1:1183–1200

Khaddafi M, Heikal M, Nandari A (2017) Analysis Z-score to predict bankruptcy in banks listed in indonesia stock exchange. Int J Econ Financ Issues 7(3):326–330

Khanna T, Yafeh Y (2007) Business groups in emerging markets: Paragons or parasites? J Econ Lit 45(2):331–372

King RG, Levine R (1993) Finance and growth: schumpeter might be right. Q J Econ 108(3):717–737

Kiran KP, Jones TM (2016) Effect of non performing assets on the profitability of banks–a selective study. Int J Bus Gen Manag 5(2):53–60

Klomp J, De Haan J (2015) Banking risk and regulation: Does one size fit all? J Bank Financ 36(12):3197–3212

Koehn M, Santomero AM (1980) Regulation of bank capital and portfolio risk. J Financ 35(5):1235–1244

Köhler M (2015) Which banks are more risky? The impact of business models on bank stability. J Financ Stab 16(1):195–212

Kothari SP (2001) Capital markets research in accounting. J Account Econ 31(1–3):105–231

Kumar S, Goyal N (2015) Behavioural biases in investment decision making – a systematic literature review. Qual Res Financ Mark 7(1):88–108

Kumar S, Kamble S, Roy MH (2020) Twenty-five years of Benchmarking: an International Journal (BIJ): a bibliometric overview. Benchmarking Int J 27(2):760–780. https://doi.org/10.1108/BIJ-07-2019-0314

Kumar S, Sureka R, Colombage S (2020) Capital structure of SMEs: a systematic literature review and bibliometric analysis. Manag Rev Q 70(4):535–565. https://doi.org/10.1007/s11301-019-00175-4

Kwan SH, Laderman ES (1999) On the portfolio effects of financial convergence-a review of the literature. Econ Rev 2:18–31

Lado AA, Boyd NG, Hanlon SC (1997) Competition, cooperation, and the search for economic rents: a syncretic model. Acad Manag Rev 22(1):110–141

Laeven L, Majnoni G (2003) Loan loss provisioning and economic slowdowns: Too much, too late? J Financ Intermed 12(2):178–197

Laeven L, Ratnovski L, Tong H (2016) Bank size, capital, and systemic risk: Some international evidence. J Bank Finance 69(1):S25–S34

Lee C-C, Hsieh M-F (2013) The impact of bank capital on profitability and risk in Asian banking. J Int Money Financ 32(1):251–281

Leech D, Leahy J (1991) Ownership structure, control type classifications and the performance of large British companies. Econ J 101(409):1418–1437

Levine R (1997) Financial development and economic growth: views and agenda. J Econ Lit 35(2):688–726

Lim CY, Woods M, Humphrey C, Seow JL (2017) The paradoxes of risk management in the banking sector. Br Acc Rev 49(1):75–90

Lo AW (2009) Regulatory reform in the wake of the financial crisis of 2007–2008. J Financ Econ Policy 1(1):4–43

Louzis DP, Vouldis AT, Metaxas VL (2012) Macroeconomic and bank-specific determinants of non-performing loans in Greece: a comparative study of mortgage, business and consumer loan portfolios. J Bank Financ 36(4):1012–1027

Maddaloni A, Peydró J-L (2011) Bank risk-taking, securitization, supervision, and low interest rates: evidence from the Euro-area and the U.S. lending standards. Rev Financ Stud 24(6):2121–2165. https://doi.org/10.1093/rfs/hhr015

Maji SG, De UK (2015) Regulatory capital and risk of Indian banks: a simultaneous equation approach. J Financ Econ Policy 7(2):140–156

Maji SG, Hazarika P (2018) Capital regulation, competition and risk-taking behavior of Indian banks in a simultaneous approach. Manag Financ 44(4):459–477

Messai AS, Jouini F (2013) Micro and macro determinants of non-performing loans. Int J Econ Financ Issues 3(4):852–860

Mitra S, Karathanasopoulos A, Sermpinis G, Dunis C, Hood J (2015) Operational risk: emerging markets, sectors and measurement. Eur J Oper Res 241(1):122–132

Mohsni S, Otchere I (2018) Does regulatory regime matter for bank risk-taking? A comparative analysis of US and Canada, d/Seas Working Papers-ISSN 2611-0172 1(1):28–28

Nguyen TPT, Nghiem SH (2015) The interrelationships among default risk, capital ratio and efficiency: evidence from Indian banks. Manag Financ 41(5):507–525

Niinimäki J-P (2004) The effects of competition on banks’ risk taking. J Econ 81(3):199–222

Page L, Brin S, Motwani R, Winograd T (1999) The PageRank citation ranking: bringing order to the web. Stanford InfoLab

Pakravan K (2014) Bank capital: the case against Basel. J Financ Regul Compl 22(3):208–218

Palacios-Callender M, Roberts SA, Roth-Berghofer T (2016) Evaluating patterns of national and international collaboration in Cuban science using bibliometric tools. J Doc 72(2):362–390. https://doi.org/10.1108/JD-11-2014-0164

Pinto G, Rastogi S, Kadam S, Sharma A (2019) Bibliometric study on dividend policy. Qual Res Financ Mark 12(1):72–95

Polizzi S, Scannella E (2020) An empirical investigation into market risk disclosure: Is there room to improve for Italian banks? J Financ Regul Compl 28(3):465–483

Prasad P, Narayanasamy S, Paul S, Chattopadhyay S, Saravanan P (2019) Review of literature on working capital management and future research agenda. J Econ Surv 33(3):827–861

Rahman MM, Zheng C, Ashraf BN, Rahman MM (2018) Capital requirements, the cost of financial intermediation and bank risk-taking: empirical evidence from Bangladesh. Res Int Bus Financ 44(1):488–503

Rajan RG (1994) Why bank credit policies fluctuate: a theory and some evidence. Q J Econ 109(2):399–441

Rastogi S, Gupte R, Meenakshi R (2021) A holistic perspective on bank performance using regulation, profitability, and risk-taking with a view on ownership concentration. J Risk Financ Manag 14(3):111

Rastogi S, Kanoujiya J (2022) Does transparency and disclosure (T&D) improve the performance of banks in India? Int J Product Perform Manag. https://doi.org/10.1108/IJPPM-10-2021-0613

Rastogi S, Ragabiruntha E (2018) Financial inclusion and socioeconomic development: gaps and solution. Int J Soc Econ 45(7):1122–1140

RBI (2001) Prudential Norms on income recognition, asset classification, and provisioning -pertaining to advances. Accessed on Apr 2020. https://rbidocs.rbi.org.in/rdocs/notification/PDFs/23068.pdf

Reddy S (2018) Announcement of payment banks and stock performance of commercial banks in India. J Internet Bank Commer 23(1):1–12

Repullo R (2004) Capital requirements, market power, and risk-taking in banking. J Financ Intermed 13(2):156–182

Rowley J, Slack F (2004) Conducting a literature review. Manag Res News 27(6):31–39. https://doi.org/10.1108/01409170410784185

Salas V, Saurina J (2003) Deregulation, market power and risk behaviour in Spanish banks. Eur Econ Rev 47(6):1061–1075

Samitas A, Polyzos S (2015) To Basel or not to Basel? Banking crises and contagion. Journal of Financial Regulation and Compliance 23(3):298–318

Sarmiento M, Galán JE (2017) The influence of risk-taking on bank efficiency: evidence from Colombia. Emerg Mark Rev 32:52–73. https://doi.org/10.1016/j.ememar.2017.05.007

Schaeck K, Cihak M, Wolfe S (2009) Are competitive banking systems more stable? J Money Credit Bank 41(4):711–734

Schwerter S (2011) Basel III’s ability to mitigate systemic risk. J Financ Regul Compl 19(4):337–354

Sen S, Sen RL (2014) Impact of NPAs on bank profitability: an empirical study. In: Ray N, Chakraborty K (eds) Handbook of research on strategic business infrastructure development and contemporary issues in finance. IGI Global, pp 124–134. https://doi.org/10.4018/978-1-4666-5154-8.ch010

Chapter   Google Scholar  

Shajahan K (1998) Non-performing assets of banks: Have they really declined? And on whose account? Econ Pol Wkly 33(12):671–674

Sharifi S, Haldar A, Rao SN (2016) Relationship between operational risk management, size, and ownership of Indian banks. Manag Financ 42(10):930–942

Sharma A, Theresa L, Mhatre J, Sajid M (2019) Application of altman Z-Score to RBI defaulters: Indian case. Asian J Res Bus Econ Manag 9(4):1–11

Shehzad CT, De Haan J (2015) Supervisory powers and bank risk taking. J Int Finan Markets Inst Money 39(1):15–24

Shen L, Xiong B, Hu J (2017) Research status, hotspotsandtrends forinformation behavior in China using bibliometric and co-word analysis. J Doc 73(4):618–633

Shleifer A, Vishny RW (1997) A survey of corporate governance. J Financ 52(2):737–783

Singh HP, Kumar S (2014) Working capital management: a literature review and research agenda. Qual Res Financ Mark 6(2):173–197

Tabak BM, Fazio DM, Cajueiro DO (2013) Systemically important banks and financial stability: the case of Latin America. J Bank Financ 37(10):3855–3866

Tahamtan I, SafipourAfshar A, Ahamdzadeh K (2016) Factors affecting number of citations: a comprehensive review of the literature. Scientometrics 107(3):1195–1225

Thakor AV (2018) Post-crisis regulatory reform in banking: Address insolvency risk, not illiquidity! J Financ Stab 37(1):107–111

Thomsen S, Pedersen T (2000) Ownership structure and economic performance in the largest European companies. Strategic Manag J 21(6):689–705

Tranfield D, Denyer D, Smart P (2003) Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br J Manag 14(3):207–222

Triki T, Kouki I, Dhaou MB, Calice P (2017) Bank regulation and efficiency: What works for Africa? Res Int Bus Financ 39(1):183–205

Tsay M, Shu Z (2011) Journal bibliometric analysis: a case study on the journal of documentation. J Doc 67(5):806–822

Vento GA, La Ganga P (2009) Bank liquidity risk management and supervision: which lessons from recent market turmoil. J Money Invest Bank 10(10):78–125

Wahid ANM (1994) The grameen bank and poverty alleviation in Bangladesh: theory, evidence and limitations. Am J Econ Sociol 53(1):1–15

Xiao Y, Watson M (2019) Guidance on conducting a systematic literature review. J Plan Educ Res 39(1):93–112

Xu X, Chen X, Jia F, Brown S, Gong Y, Xu Y (2018) Supply chain finance: a systematic literature review and bibliometric analysis. Int J Prod Econ 204:160–173

Yadav M (2011) Impact of non performing assets on profitability and productivity of public sector banks in India. AFBE J 4(1):232–239

Yong-Hak J (2013), Web of Science, Thomson Reuters

Zheng C, Rahman MM, Begum M, Ashraf BN (2017) Capital regulation, the cost of financial intermediation and bank profitability: evidence from Bangladesh. J Risk Financ Manag 10(2):9

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Rastogi, S., Sharma, A., Pinto, G. et al. A literature review of risk, regulation, and profitability of banks using a scientometric study. Futur Bus J 8 , 28 (2022). https://doi.org/10.1186/s43093-022-00146-4

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Neuromarketing and big data analysis of banking firms’ website interfaces and performance.

1. Introduction

2. literature background, 2.1. banking firms, digital marketing, and user engagement, 2.2. metrics and kpis of friendly website user interface (ui), 2.3. neuromarketing and big data analysis implications on website interface and performance, 2.4. hypotheses development, 3. materials and methods, 3.1. methodological concept.

• The research started with the collection of data on website customers and digital marketing activities from banking firm websites. A website’s user behavioral data (pages per visit, bounce rate, time on site, etc.) were sourced from the website platform Semrush [ 61 ], which enables the extraction of big data from corporate webpages.
• The next step involved statistical analysis using methods such as descriptive statistics, correlation, and linear regression. By analyzing the coefficients obtained, researchers can determine the impact of banking firms’ website customer data on their digital marketing and interface performance metrics, including purchase conversion, display ads, organic traffic, and bounce rate.
• After statistical analysis, a hybrid model (HM) incorporating agent-based models (ABMs) and System Dynamics (SD) was used for the simulation. The software AnyLogic (version 8.9.1) [ 62 ] was employed to create a hybrid model that simulates the relationships between the study’s dependent and independent variables over 360 days. This model aims to represent the dynamic interaction between banking firms’ website interface metrics and key metrics of their digital marketing strategies.
• The final stage included a neuromarketing approach to gain deeper insights from 26 participants who viewed the websites of the selected banking firms. They were instructed to search and observe, in 20 s, the selected banking firm websites and their provided financial products and services. Eye-tracking and heatmap analysis were conducted using the SeeSo Web Analysis platform (Eyedid SDK) [ 63 ]. This method seeks to extract additional information about the onsite activity and engagement of the participants from the qualitative methodological concept.

3.2. Fuzzy Cognitive Mapping (FCM) Framework

3.3. research sample, 4.1. statistical analysis, 4.2. simulation model, 4.3. neuromarketing applications, 5. discussion, 6. conclusions, 6.1. theoretical, practical, and managerial implications, 6.2. future work and limitations, author contributions, data availability statement, conflicts of interest.

• Hennig-Thurau, T.; Malthouse, E.C.; Friege, C.; Gensler, S.; Lobschat, L.; Rangaswamy, A.; Skiera, B. The impact of new media on customer relationships. J. Serv. Res. 2010 , 13 , 311–330. [ Google Scholar ] [ CrossRef ]
• Broby, D. Financial technology and the future of banking. Financ. Innov. 2021 , 7 , 1–19. [ Google Scholar ] [ CrossRef ]
• Ding, Q.; He, W. Digital transformation, monetary policy and risk-taking of banks. Financ. Res. Lett. 2023 , 55 , 103986. [ Google Scholar ] [ CrossRef ]
• Shukla, S. Analyzing customer engagement through e-CRM: The role of relationship marketing in the era of digital banking in Varanasi banks. J. Commer. Econ. Comput. Sci. 2021 , 7 , 57–65. [ Google Scholar ]
• Hendriyani, C.; Raharja, S.J. Analysis building customer engagement through eCRM in the era of digital banking in Indonesia. Int. J. Econ. Policy Emerg. Econ. 2018 , 11 , 479–486. [ Google Scholar ]
• Vivek, S.D.; Beatty, S.E.; Morgan, R.M. Customer engagement: Exploring customer relationships beyond purchase. J. Mark. Theory Pract. 2012 , 20 , 122–146. [ Google Scholar ] [ CrossRef ]
• Lee, D.; Hosanagar, K.; Nair, H.S. Advertising content and consumer engagement on social media: Evidence from Facebook. Manag. Sci. 2018 , 64 , 5105–5131. [ Google Scholar ] [ CrossRef ]
• Lin, K.-Y.; Lu, H.-P. Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Comput. Hum. Behav. 2011 , 27 , 1152–1161. [ Google Scholar ] [ CrossRef ]
• Lee, M.; Wang, Y.R.; Huang, C.F. Design and development of a friendly user interface for building construction traceability system. Microsyst. Technol. 2021 , 27 , 1773–1785. [ Google Scholar ] [ CrossRef ]
• Faghih, B.; Azadehfar, M.; Katebi, S. User interface design for E-learning software. Int. J. Soft Comput. Softw. Eng. 2014 , 3 , 786–794. [ Google Scholar ] [ CrossRef ]
• Cheng, S.; Yang, Y.; Xiu, L.; Yu, G. Effects of prior experience on the user experience of news aggregation app’s features—Evidence from a behavioral experiment. Int. J. Hum.-Comput. Interact. 2022 , 39 , 1271–1279. [ Google Scholar ] [ CrossRef ]
• Nielsen, J.; Norman, D. The Definition of User Experience (UX) ; Nielsen Norman Group N N/g.: Fremont, CA, USA, 2018; Available online: https://www.nngroup.com/articles/definition-user-experience/ (accessed on 20 June 2024).
• He, W.; Hung, J.-L.; Liu, L. Impact of big data analytics on banking: A case study. J. Enterp. Inf. Manag. 2023 , 36 , 459–479. [ Google Scholar ] [ CrossRef ]
• Kalaganis, F.P.; Georgiadis, K.; Oikonomou, V.P.; Laskaris, N.A.; Nikolopoulos, S.; Kompatsiaris, I. Unlocking the Subconscious Consumer Bias: A Survey on the Past, Present, and Future of Hybrid EEG Schemes in Neuromarketing. Front. Neuroergonomics 2021 , 2 , 672982. [ Google Scholar ] [ CrossRef ]
• Walker, P.R. How Does Website Design in the e-Banking Sector Affect Customer Attitudes and Behaviour? Ph.D. Thesis, University of Northumbria, Newcastle upon Tyne, UK, 2021. Available online: https://nrl.northumbria.ac.uk/id/eprint/5849/7/walker.philip_phd_(VOLUME_1of2).pdf (accessed on 12 June 2024).
• Manser Payne, E.H.; Peltier, J.; Barger, V.A. Enhancing the value co-creation process: Artificial intelligence and mobile banking service platforms. J. Res. Interact. Mark. 2021 , 15 , 68–85. [ Google Scholar ] [ CrossRef ]
• Diener, F.; Špacek, M. Digital transformation in banking: A managerial perspective on barriers to change. Sustainability 2021 , 13 , 2032. [ Google Scholar ] [ CrossRef ]
• Khattak, M.A.; Ali, M.; Azmi, W.; Rizvi, S.A.R. Digital transformation, diversification and stability: What do we know about banks? Econ. Anal. Policy 2023 , 78 , 122–132. [ Google Scholar ] [ CrossRef ]
• Giannakis-Bompolis, C.; Boutsouki, C. Customer Relationship Management in the Era of Social Web and Social Customer: An Investigation of Customer Engagement in the Greek Retail Banking Sector. Procedia Soc. Behav. Sci. 2014 , 148 , 67–78. [ Google Scholar ] [ CrossRef ]
• Mogaji, E. Redefining banks in the digital era: A typology of banks and their research, managerial and policy implications. Int. J. Bank Mark. 2023 , 41 , 1899–1918. [ Google Scholar ] [ CrossRef ]
• Salvi, A.; Petruzzella, F.; Raimo, N.; Vitolla, F. Transparency in the digitalization choices and the cost of equity capital. Qual. Res. Financ. Mark. 2023 , 15 , 630–646. [ Google Scholar ] [ CrossRef ]
• Carmona, J.; Cruz, C. Banks’ social media goals and strategies. J. Bus. Res. 2018 , 91 , 31–41. [ Google Scholar ] [ CrossRef ]
• Kosiba, J.P.; Boateng, H.; Okoe, A.F.; Hinson, R. Trust and customer engagement in the banking sector in Ghana. Serv. Ind. J. 2018 , 40 , 960–973. [ Google Scholar ] [ CrossRef ]
• Del Sarto, N.; Bocchialini, E.; Gai, L.; Ielasi, F. Digital banking: How social media is shaping the game. Qual. Res. Financ. Mark. 2024 . ahead of print . [ Google Scholar ] [ CrossRef ]
• Sakas, D.P.; Giannakopoulos, N.T.; Trivellas, P. Exploring affiliate marketing’s impact on customers’ brand engagement and vulnerability in the online banking service sector. Int. J. Bank Mark. 2023 , 42 , 1282–1312. [ Google Scholar ] [ CrossRef ]
• Sakas, D.P.; Giannakopoulos, N.T.; Terzi, M.C.; Kamperos, I.D.G.; Kanellos, N. What is the connection between Fintechs’ video marketing and their vulnerable customers’ brand engagement during crises? Int. J. Bank Mark. 2023 , 42 , 1313–1347. [ Google Scholar ] [ CrossRef ]
• Mbama, C.I.; Ezepue, P.O. Digital banking, customer experience and bank financial performance: UK customers’ perceptions. Int. J. Bank Mark. 2018 , 36 , 230–255. [ Google Scholar ] [ CrossRef ]
• Khandelwal, R.; Kapoor, D. The Use of Digital Tools for Customer Engagement in the Financial Services Sector. In Revolutionizing Customer-Centric Banking through ICT ; IGI Global: Hershey, PA, USA, 2024; pp. 29–55. [ Google Scholar ]
• Islam, J.U.; Shahid, S.; Rasool, A.; Rahman, Z.; Khan, I.; Rather, R.A. Impact of website attributes on customer engagement in banking: A solicitation of stimulus-organism-response theory. Int. J. Bank Mark. 2020 , 38 , 1279–1303. [ Google Scholar ] [ CrossRef ]
• Lestari, D.M.; Hardianto, D.; Hidayanto, A.N. Analysis of user experience quality on responsive web design from its informative perspective. Int. J. Softw. Eng. Appl. 2014 , 8 , 53–62. [ Google Scholar ] [ CrossRef ]
• Almeida, F.; Monteiro, J. Approaches and principles for UX web experiences: A case study approach. Int. J. Inf. Technol. Web Eng. 2017 , 12 , 49–65. [ Google Scholar ] [ CrossRef ]
• Walsh, T.A.; Kapfhammer, G.M.; McMinn, P. Automated layout failure detection for responsive web pages without an explicit oracle. In Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis, Santa Barbara, CA, USA, 10–14 July 2017. [ Google Scholar ] [ CrossRef ]
• Rogers, Y.; Sharp, H.; Preece, J. Interaction Design: Beyond Human-Computer Interaction , 6th ed.; John Wiley & Sons Ltd.: New York, NY, USA, 2023. [ Google Scholar ]
• ISO9241-11 ; Ergonomics of Human-System Interaction–Part 11: Usability for Definition and Concept. ISO: Geneva, Switzerland, 2018.
• Hussain, I.; Khan, I.A.; Jadoon, W.; Jadoon, R.N.; Khan, A.N.; Shafi, M. Touch or click friendly: Towards adaptive user interfaces for complex applications. PLoS ONE 2024 , 19 , e0297056. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kim, S.; Cho, D. Technology Trends for UX/UI of Smart Contents. Korea Contents Assoc. Rev. 2016 , 14 , 29–33. [ Google Scholar ] [ CrossRef ]
• Joo, H.S. A Study on UI/UX and Understanding of Computer Major Students. Int. J. Adv. Smart Converg. 2017 , 6 , 26–32. [ Google Scholar ]
• Von Saucken, C.; Michailidou, I.; Lindemann, U. How to Design Experiences: Macro UX versus Micro UX Approach. Lect. Notes Comuter Sci. 2013 , 8015 , 130–139. [ Google Scholar ]
• Instatus. Our Comprehensive List of Website Performance Metrics to Monitor. 2024. Available online: https://instatus.com/blog/website-performance-metrics (accessed on 20 June 2024).
• Levrini, G.R.; Jeffman dos Santos, M. The influence of Price on purchase intentions: Comparative study between cognitive, sensory, and neurophysiological experiments. Behav. Sci. 2021 , 11 , 16. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Gabriel, D.; Merat, E.; Jeudy, A.; Cambos, S.; Chabin, T.; Giustiniani, J.; Haffen, E. Emotional effects induced by the application of a cosmetic product: A real-time electrophysiological evaluation. Appl. Sci. 2021 , 11 , 4766. [ Google Scholar ] [ CrossRef ]
• Filipović, F.; Baljak, L.; Naumović, T.; Labus, A.; Bogdanović, Z. Developing a web application for recognizing emotions in neuromarketing. In Marketing and Smart Technologies ; Springer: Berlin/Heidelberg, Germany, 2020; pp. 297–308. [ Google Scholar ]
• Lee, Ν.; Broderick, A.J.; Chamberlain, L. What is ‘neuromarketing’? A discussion and agenda for future research. Int. J. Psychophysiol. 2007 , 63 , 199–204. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Rawnaque, F.; Rahman, K.; Anwar, S.; Vaidyanathan, R.; Chau, T.; Sarker, F.; Mamun, K. Technological advancements and opportunities in Neuromarketing: A systematic review. Brain Inform. 2020 , 7 , 10. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ariely, D.; Berns, G. Neuromarketing: The hope and hype of neuroimaging in business. Nat. Rev. Neurosci. 2010 , 11 , 284–292. [ Google Scholar ] [ CrossRef ]
• Sousa, J. Neuromarketing and Big Data Analytics for Strategic Consumer Engagement: Emerging Research and Opportunities ; IGI Global: Hershey, PA, USA, 2017. [ Google Scholar ] [ CrossRef ]
• Šola, H.M.; Qureshi, F.H.; Khawaja, S. Exploring the Untapped Potential of Neuromarketing in Online Learning: Implications and Challenges for the Higher Education Sector in Europe. Behav. Sci. 2024 , 14 , 80. [ Google Scholar ] [ CrossRef ]
• Berčík, J.; Neomániová, K.; Gálová, J. Using neuromarketing to understand user experience with the website (UX) and interface (UI) of a selected company. In The Poprad Economic and Management Forum 2021, Conference Proceedings from International Scientific Conference, Poprad, Slovak Republic, 14 October 2021 ; Madzík, P., Janošková, M., Eds.; VERBUM: Ružomberok, Slovakia, 2021; pp. 246–254. [ Google Scholar ]
• Golnar-Nik, P.; Farashi, S.; Safari, M. The application of EEG power for the prediction and interpretation of consumer decision-making: A neuromarketing study. Physiol. Behav. 2019 , 207 , 90–98. [ Google Scholar ] [ CrossRef ]
• Uygun, Y.; Oguz, R.F.; Olmezogullari, E.; Aktas, M.S. On the Large-scale Graph Data Processing for User Interface Testing in Big Data Science Projects. In Proceedings of the 2020 IEEE International Conference on Big Data (Big Data), Atlanta, GA, USA, 10–13 December 2020; pp. 2049–2056. [ Google Scholar ] [ CrossRef ]
• Li, L.; Zhang, J. Research and Analysis of an Enterprise E-Commerce Marketing System under the Big Data Environment. J. Organ. End User Comput. 2021 , 33 , 1–19. [ Google Scholar ] [ CrossRef ]
• Sakas, D.P.; Giannakopoulos, N.T.; Terzi, M.C.; Kanellos, N.; Liontakis, A. Digital Transformation Management of Supply Chain Firms Based on Big Data from DeFi Social Media Profiles. Electronics 2023 , 12 , 4219. [ Google Scholar ] [ CrossRef ]
• Bala, M.; Verma, D. A Critical Review of Digital Marketing. Int. J. Manag. IT Eng. 2018 , 8 , 321–339. Available online: https://ssrn.com/abstract=3545505 (accessed on 20 July 2024).
• Pongpaew, W.; Speece, M.; Tiangsoongnern, L. Social presence and customer brand engagement on Facebook brand pages. J. Prod. Brand Manag. 2017 , 26 , 262–281. [ Google Scholar ] [ CrossRef ]
• Chaffey, D.; Ellis-Chadwick, F. Digital Marketing ; Pearson: London, UK, 2019. [ Google Scholar ]
• Dodson, I. The Art of Digital Marketing: The Definitive Guide to Creating Strategic, Targeted, and Measurable Online Campaigns ; John Wiley & Sons: New York, NY, USA, 2016. [ Google Scholar ]
• Chawla, Y.; Chodak, G. Social media marketing for businesses: Organic promotions of web-links on Facebook. J. Bus. Res. 2021 , 135 , 49–65. [ Google Scholar ] [ CrossRef ]
• McIlwain, C.D. Algorithmic Discrimination: A Framework and Approach to Auditing & Measuring the Impact of Race-Targeted Digital Advertising. PolicyLink Rep. 2023 , 1–50. [ Google Scholar ] [ CrossRef ]
• Mladenović, D.; Rajapakse, A.; Kožuljević, N.; Shukla, Y. Search engine optimization (SEO) for digital marketers: Exploring determinants of online search visibility for blood bank service. Online Inf. Rev. 2023 , 47 , 661–679. [ Google Scholar ] [ CrossRef ]
• Wedel, M.; Kannan, P.K. Marketing analytics for data-rich environments. J. Mark. 2016 , 80 , 97–121. [ Google Scholar ] [ CrossRef ]
• Semrush. 2024. Available online: https://www.semrush.com/ (accessed on 12 April 2024).
• Anylogic. 2024. Available online: https://www.anylogic.com/ (accessed on 12 April 2024).
• SeeSo Web Analysis (Eyedid SDK). 2024. Available online: https://sdk.eyedid.ai/ (accessed on 20 April 2024).
• MentalModeler. 2024. Available online: https://dev.mentalmodeler.com/ (accessed on 10 April 2024).
• Migkos, S.P.; Sakas, D.P.; Giannakopoulos, N.T.; Konteos, G.; Metsiou, A. Analyzing Greece 2010 Memorandum’s Impact on Macroeconomic and Financial Figures through FCM. Economies 2022 , 10 , 178. [ Google Scholar ] [ CrossRef ]
• Mpelogianni, V.; Groumpos, P.P. Re-approaching fuzzy cognitive maps to increase the knowledge of a system. AI Soc. 2018 , 33 , 175–188. [ Google Scholar ] [ CrossRef ]
• Forbes India. The 10 Largest Banks in the World in 2024. 2024. Available online: https://www.forbesindia.com/article/explainers/the-10-largest-banks-in-the-world/86967/1 (accessed on 6 January 2024).
• Nugroho, S.; Uehara, T. Systematic Review of Agent-Based and System Dynamics Models for Social-Ecological System Case Studies. Systems 2023 , 11 , 530. [ Google Scholar ] [ CrossRef ]
• McGarraghy, S.; Olafsdottir, G.; Kazakov, R.; Huber, É.; Loveluck, W.; Gudbrandsdottir, I.Y.; Čechura, L.; Esposito, G.; Samoggia, A.; Aubert, P.-M.; et al. Conceptual System Dynamics and Agent-Based Modelling Simulation of Interorganisational Fairness in Food Value Chains: Research Agenda and Case Studies. Agriculture 2022 , 12 , 280. [ Google Scholar ] [ CrossRef ]
• Wang, H.; Shi, W.; He, W.; Xue, H.; Zeng, W. Simulation of urban transport carbon dioxide emission reduction environment economic policy in China: An integrated approach using agent-based modelling and system dynamics. J. Clean. Prod. 2023 , 392 , 136221. [ Google Scholar ] [ CrossRef ]
• Nguyen, L.K.N.; Howick, S.; Megiddo, I. A framework for conceptualising hybrid system dynamics and agent-based simulation model. Eur. J. Oper. Res. 2024 , 315 , 1153–1166. [ Google Scholar ] [ CrossRef ]
• Ezquerra, A.; Agen, F.; Bogdan Toma, R.; Ezquerra-Romano, I. Using facial emotion recognition to research emotional phases in an inquiry-based science activity. Res. Sci. Technol. Educ. 2023 , 1–24. [ Google Scholar ] [ CrossRef ]
• Chen, Y.; Qin, X.; Xu, X. Visual Analysis and Recognition of Virtual Reality Resolution Based on Pupil Response and Galvanic Skin Response. In Proceedings of the 4th International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI) 2023, Guangzhou, China, 4–6 August 2023; pp. 74–83. [ Google Scholar ] [ CrossRef ]
• Muke, P.Z.; Kozierkiewicz, A.; Pietranik, M. Investigation and Prediction of Cognitive Load During Memory and Arithmetic Tasks. In Computational Collective Intelligence. ICCCI 2023. Lecture Notes in Computer Science ; Nguyen, N.T., Botzheim, J., Gulyás, L., Núñez, M., Treur, J., Vossen, G., Kozierkiewicz, A., Eds.; Springer: Cham, Switzerland, 2023; Volume 14162. [ Google Scholar ] [ CrossRef ]
• Amiri, S.S.; Masoudi, M.; Asadi, S.; Karan, E.P. A Quantitative Way for Measuring the Building User Design Feedback and Evaluation. In Proceedings of the 16th International Conference on Computing in Civil and Building Engineering (ICCCBE2016), Osaka, Japan, 6–8 July 2016; pp. 1–7. [ Google Scholar ]
• Wilson, L. 30-Minute Conversion Rate Optimisation Actions. In 30-Minute Website Marketing ; Emerald Publishing Limited: Leeds, UK, 2019; pp. 131–141. [ Google Scholar ] [ CrossRef ]
• Sood, S. Leveraging Web Analytics for Optimizing Digital Marketing Strategies. In Big Data Analytics ; Chaudhary, K., Alam, M., Eds.; CRC Press (Auerbach Publications): Boca Raton, FL, USA, 2022; pp. 173–188. [ Google Scholar ]
• Drivas, I.C.; Sakas, D.P.; Giannakopoulos, G.A. Display Advertising and Brand Awareness in Search Engines: Predicting the Engagement of Branded Search Traffic Visitors. In Business Intelligence and Modelling. IC-BIM 2019. Springer Proceedings in Business and Economics ; Sakas, D.P., Nasiopoulos, D.K., Taratuhina, Y., Eds.; Springer: Cham, Switzerland, 2021. [ Google Scholar ] [ CrossRef ]
• Hari, H.; Iyer, R.; Sampat, B. Customer Brand Engagement through Chatbots on Bank Websites–Examining the Antecedents and Consequences. Int. J. Hum. Comput. Interact. 2023 , 38 , 1212–1227. [ Google Scholar ] [ CrossRef ]
• Makrydakis, N. SEO mix 6 O’s model and categorization of search engine marketing factors for websites ranking on search engine result pages. Int. J. Res. Mark. Manag. Sales 2024 , 6 , 18–32. [ Google Scholar ] [ CrossRef ]
• Shankar, B. Strategies for Deep Customer Engagement. In Nuanced Account Management ; Palgrave Macmillan: Singapore, 2018; pp. 53–99. [ Google Scholar ] [ CrossRef ]
• Chakrabortty, K.; Jose, E. Relationship Analysis between Website Traffic, Domain Age and Google Indexed Pages of E-commerce Websites. IIM Kozhikode Soc. Manag. Rev. 2018 , 7 , 171–177. [ Google Scholar ] [ CrossRef ]
• Müller, O.; Fay, M.; vom Brocke, J. The Effect of Big Data and Analytics on Firm Performance: An Econometric Analysis Considering Industry Characteristics. J. Manag. Inf. Syst. 2018 , 35 , 488–509. [ Google Scholar ] [ CrossRef ]
• Pejić Bach, M.; Krstić, Ž.; Seljan, S.; Turulja, L. Text Mining for Big Data Analysis in Financial Sector: A Literature Review. Sustainability 2019 , 11 , 1277. [ Google Scholar ] [ CrossRef ]
• Gupta, S.; Justy, T.; Kamboj, S.; Kumar, A.; Kristoffersen, E. Big data and firm marketing performance: Findings from knowledge-based view. Technol. Forecast. Soc. Change 2021 , 171 , 120986. [ Google Scholar ] [ CrossRef ]
• Ravi, V.; Kamaruddin, S. Big Data Analytics Enabled Smart Financial Services: Opportunities and Challenges. In Big Data Analytics. BDA 2017. Lecture Notes in Computer Science ; Reddy, P., Sureka, A., Chakravarthy, S., Bhalla, S., Eds.; Springer: Cham, Switzerland, 2017; Volume 10721, pp. 15–39. [ Google Scholar ] [ CrossRef ]
• Tichindelean, M.T.; Cetină, I.; Orzan, G. A Comparative Eye Tracking Study of Usability—Towards Sustainable Web Design. Sustainability 2021 , 13 , 10415. [ Google Scholar ] [ CrossRef ]
• Bajaj, R.; Syed, A.A.; Singh, S. Analysing applications of neuromarketing in efficacy of programmatic advertising. J. Consum. Behav. 2023 , 23 , 939–958. [ Google Scholar ] [ CrossRef ]
• Tirandazi, P.; Bamakan, S.M.H.; Toghroljerdi, A. A review of studies on internet of everything as an enabler of neuromarketing methods and techniques. J. Supercomput. 2022 , 79 , 7835–7876. [ Google Scholar ] [ CrossRef ]
• Slijepčević, M.; Popović Šević, N.; Radojević, I.; Šević, A. Relative Importance of Neuromarketing in Support of Banking Service Users. Marketing 2022 , 53 , 131–142. [ Google Scholar ] [ CrossRef ]

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Share and Cite

Giannakopoulos, N.T.; Sakas, D.P.; Migkos, S.P. Neuromarketing and Big Data Analysis of Banking Firms’ Website Interfaces and Performance. Electronics 2024 , 13 , 3256. https://doi.org/10.3390/electronics13163256

Giannakopoulos NT, Sakas DP, Migkos SP. Neuromarketing and Big Data Analysis of Banking Firms’ Website Interfaces and Performance. Electronics . 2024; 13(16):3256. https://doi.org/10.3390/electronics13163256

Giannakopoulos, Nikolaos T., Damianos P. Sakas, and Stavros P. Migkos. 2024. "Neuromarketing and Big Data Analysis of Banking Firms’ Website Interfaces and Performance" Electronics 13, no. 16: 3256. https://doi.org/10.3390/electronics13163256

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