write an essay on innovative banking

• Innovative Banking

Innovation means something new or something which had not been done before. The same goes for banking section as well. There are many sections in banks which are going through or have gone through innovation in recent past. They are no longer restricted to age-old (traditional) methods. Thus, to increase the business avenues and capture the new market banks are resorting to innovation. This term innovative banking is being in use a lot nowadays.

There are many types of banking facilities that the banks have started in recent years. These are the following types of innovative banking used by the banks these days:

Mobile Banking

Mobile banking has been a revolution in the past few years. It has completely changed the way banking systems are working. Thus, it is a system that allows customers to perform many types of financial related services through a smartphone.

These include services like ATM locations, bill payment alert, inter or intrabank payments, bill payments, and many more. So, services are available at the fingertips of every person.

Internet Banking

Internet coverage in the last few years has increased drastically. This service is online banking, web banking, or virtual banking.

Thus, this banking service allows its users to execute and perform any financial transaction or service with the help of the Internet. The banking facilities are provided traditionally at a local bank outlet.

This includes bill payments, a deposit of money, borrowing of money, and other services are all available at one place. This service happens with the use of the Internet facility. In India, ICICI Bank was the first bank to avail it’s customers the facility of Internet banking.

 Learn more about History of Banking in India And World here

Retail and Wholesale Banking

Like other businesses, the banking sector to has evolved into retail and wholesale banking and it is also one of the parts of innovative banking.

Here, retail banking refers to the banking in which the transactions which are done daily by the banks are executed with consumers.

Thus, this is done instead of transactions with other banks or other corporates. The services under this are:

• Personal loans
• Savings accounts
• Checking accounts
• Credit card

Wholesale banking is completely the opposite of retail banking. It refers to the business being conducted with the business and industrial entities.

Thus, in wholesale banking, trading houses, domestic companies, and multinational companies are included. So, there are many services which are included in the wholesale banking and these services are:

• Value-added services
• Fund based services
• Non-fund related services
• Internet banking
• Multinational and offshore banking

Multinational banking is the banks that are present in more than one country. The main services are available in more than one country in these services. Thus, these banks are also called international banks.

The first bank to offer its services outside India was Indian bank in 1946. Currently, Bank of Baroda has the maximum number of the overseas franchise in India.

While under offshore banking, the banking activities are performed in the currencies that are different than the currency of the country in which the bank account is opened.   The banking services in these banks remain the same though. 

Narrow and Universal Banking

Narrow banking includes keeping together the higher part of deposits in risk-free assets like government securities. In India, this is basically in performance to reduce the size of the NPAs.

While commercial, investment, insurance, and many other financial activities combine to form universal banking. Thus, in this practice every product is available.

Practice Questions on Innovative Banking

Q. Out of the following, which was the first bank to start internet banking?

A. Axis bank                 B. Bank of Baroda               C. HDFC                  D. ICICI bank

Answer : D. ICICI bank

Customize your course in 30 seconds

Which class are you in.

Financial Reforms and Banking Innovation

• Major Effects of International Banking
• Introduction to Financial Reforms
• Services of Banks
• Trends in Banking
• Committees related to Banking Sector Reforms

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Download the App

• Open access
• 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

39k Accesses

52 Citations

4 Altmetric

Metrics details

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

Download references

Acknowledgements

There are no acknowldgements.

There was no funding associated with this paper.

Author information

Authors and affiliations.

Centre for Financial Regulation and Innovation, Strathclyde Business School, Glasgow, UK

Daniel Broby

You can also search for this author in PubMed   Google Scholar

Contributions

The author confirms the contribution is original and his own. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Daniel Broby .

Ethics declarations

Competing interests.

I declare I have no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

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

Download citation

Received : 21 January 2021

Accepted : 09 June 2021

Published : 18 June 2021

DOI : https://doi.org/10.1186/s40854-021-00264-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Cryptocurrencies
• P2P Lending
• Intermediation
• Digital Payments

JEL Classifications

Advertisement

FinTech’s rapid growth and its effect on the banking sector

• Original Article
• Open access
• Published: 28 November 2022
• Volume 6 , pages 159–176, ( 2022 )

Cite this article

You have full access to this open access article

• Charalampos Basdekis 1 , 2 , 3   na1 ,
• Apostolos Christopoulos 2 , 4   na1 ,
• Ioannis Katsampoxakis   ORCID: orcid.org/0000-0001-8019-6231 5 &
• Aikaterini Vlachou 2   na1  

11k Accesses

10 Citations

Explore all metrics

FinTech is a New Financial Technology, which provides financial services through innovative information and communication technologies. It is widely accepted that 4th industrial revolution, has affected tremendously the living and working conditions of the societies. The convergence between advanced technologies, entrepreneurship becomes more complex and remarkably computerized. Within such significant changes it is rather expected that banking, has been one of the most challenged sectors. New players like FinTech and Big Tech companies try to capitalize the circumstances, by promoting new consumer patterns to gain market shares. The purpose of this study is to investigate the rapid expansion of FinTech and to evaluate its impact on the Greek banking system. This topic becomes very important nowadays as the number of FinTech companies, which compete with traditional banks on financial products and services, are increasing constantly as digital technology develops. In our study we apply a questionnaire method mainly with closed questions to collect data from the main players. To do this, we use two questionnaires each one for a different sample. The first sample consists of the consumers for financial products and services in the Greek banking sector and the second sample consists of the employees in the Greek banking sector. According to the results, customers of all ages seem to trust the traditional banks more than FinTech companies whereas the level of mobile transactions separately for each consumer, depends on age and education. From the answers of the consumers, it is clear that security is on the top of their worries for using financial services by FinTech companies. On the other hand, the second questionnaire with bank employees shows clearly that educational level is a critical factor for their readiness and response to new technologies.

Similar content being viewed by others

Fintech Adoption in Palestine: Bank Customers’ Perspectives

An Empirical Study to Assess the Factors Influencing Banking Customers Toward FINTECH Adoption in Tamil Nadu

Traditional Banks and Fintech: Survival, Future and Threats

Avoid common mistakes on your manuscript.

Research Problem : Advances in financial technology has brought a new era in the banking sector, introducing challenges, opportunities and risks. The integration of FinTech in the financial system has created global digital technology platforms through which new innovative financial products and services are provided to end customers.

At the same time, traditional banks seem unable to assimilate at the same level these new technologies to deliver products and services to their own customers. In the light of these developments, the question arises as to whether non-banking entities, such as FinTech companies, are capable to lead the competition in such a way and at such a level that banking products and services will no longer be a privilege of the traditional banking sector.

Objective: The evaluation of FinTech growth and the examination of the prospects for the Greek commercial banks, taking into consideration the presence of FinTech companies.

Research Questions :

What types of products and services are provided by FinTech companies and which of them are most attractive to users?

Which are the most important factors influencing the choice of FinTech services?

At what level traditional banks operating in Greece are interested to invest in FinTech?

How FinTech affects employment in the Greek banking sector?

1 Introduction

In recent years, technology has developed rapidly, affecting the way and means in which financial products and services are provided and the way in which consumers are served. Looking in the past, we find Bill Gates, the founder of Microsoft to declare in 1990 that "banking is necessary, banks are not." Thirty years later, this statement seems to be more suitable than ever, especially in Europe [ 19 ]. One can surely say that banks in the future will have many different forms. Brei et al. [ 13 ] point out that in order to maintain their profitability in such an environment, many banks have placed great emphasis on fee-generating services.

It is noteworthy that in the age of advanced technological developments, even the nature of deposits is changing. This prompts Braggion et al. [ 12 ] to investigate whether FinTech expansion could pose a threat for financial stability. Already today banks accept deposits and make transactions in a digital form. However, at the same time, this raises a number of issues, such as resilience, security and competition in payments, the way financial services are provided, the way and security of cross-border money transfers, but also raises the question of private and public money issuance.

According to Arner et al. [ 3 ], the global financial crisis in 2008 proved to be the most critical moment for the strengthening of FinTech financial technology and RegTech regulatory technology, as it stimulated all processes much faster. Indeed, as banks are unable to adopt right away new technologies due to regulatory restrictions [ 25 ] they have to rely at least for some time on obsolete infrastructure technologies. Therefore, advances in technologies are expected to benefit the FinTech companies more. However, according to Philippon [ 45 ], this advantage for FinTech companies does not show reduction in the intermediation costs of the banking sector. At a European level, during the crisis of 2008, the primary concern of ECB was to introduce effective measures, in order to achieve the key objective of financial stability in Eurozone [ 32 ] and thereafter to move towards the introduction and development of a strict and effective regulation framework for the operation of FinTech companies.

The growth of FinTech companies has strengthened more, after the global financial crisis of 2007. Estimates by Finances Online indicate that there are currently more than 12,000 FinTech companies operating worldwide [ 33 ]. The main target of FinTech companies is to offer in a friendly way financial products and services to their customers, in a more efficient, transparent and more automated way [ 21 ]. In another recent study, Broby [ 14 ] concluded that, in an increasingly digital world, trust will remain at the core of banking, which means that transformation of assets will continue to play an important role. However, the nature of banking and financial services is expected to change dramatically. The technological achievements and the importance on R&D expenditures is of paramount importance for every business in or out of the financial sector [ 10 , 30 , 31 ].

Mitra and Karathanasopoulos [ 41 ] examined the impact of financial technology on the relative value of the business in the banking sector. They found that financial technologies affect operational risk and thus companies must take into account the benefits but also the risks from implementing new technological innovations.

Before the introduction of FinTech, entrepreneurs and individuals had to visit a bank branch to apply for small business credit lines, finance leases, mortgages, business loans, credit cards and various other banking services. However, after the introduction of FinTech companies people no longer need to visit a bank to apply for a mortgage loan or a consumer loan. The applications for these products are now offered online through FinTech companies [ 29 ] which are incorporated in various business models.

There is a wide variety of business models that have been established under the banner of Fintech such as, crowdfunding, payments, wealth management, lending, capital markets and insurance services. Every business model is unique but depends on the digital platform in order to reduce operating costs [ 26 ].

The findings of Karsh and Abuhara [ 29 ] show that FinTech companies will grow faster in an environment, where digital technology is available and the penetration of smartphones is high. The empirical results of this study show that the profitability of traditional banks is higher when they collaborate with FinTech companies and when the banks adopt their own financial technology in their business model.

Internationally, the most influential banking system by FinTech is in China. Arner et al. [ 6 ], report that although the structure of the Chinese banking system is inefficient, the penetration of technology is high and thus why we see in China a rapid increase of technology companies like Alibaba, Baidu and Tencent which have a significant impact on financial services [ 36 ]. Although, for at least one decade, those involved with FinTech have attracted the worldwide attention, this issue has not studied widely by academics.

The existing literature shows that although FinTech companies perform like banks, till today they are not regulated like banks.

The main goal of our study is to enlighten aspects of the rapid growth of the financial industry in combination with high technology. At the same time, we aim to clarify the role of FinTech in the financial sector in general, emphasizing though in the banking sector. The results of our study show that generation Z will be the basis for new era emerging in the banking system and their needs and expectations will act a key role. At the same time another important output is the interrelation between FinTech and prudent investments decisions.

The present work is structured as follows: The second section presents the historical development of FinTech and TechFin, the third section deals with the regulation framework of RegTech in Europe and the fourth section refers to the technology used and efficiency of FinTech. In the fifth section, we analyze the technological trends in the banking sector, and in the sixth one the impact of Covid-19 pandemic on FinTech. The methodological framework, the results and the empirical analysis are presented form the seventh to ninth sections while in the last section there are analyzed the conclusions and the discussion regarding the existing literature and the empirical research, giving answers to the research questions that we have identified, suggesting future research perspectives.

2 The historical development of FinTech and TechFin

The term “FinTech” refers to companies that combine the provision of financial services with modern and innovative technologies, although the traditional banking sector has the potential for technological improvement and banks are working in this direction. However, in addition to the banking sector, there are FinTech companies that also offer insurance and financial instruments, either directly or as third parties. FinTech therefore includes companies that provide advance technology to financial service providers. However, it should be noted that there is a huge variation in the legislative and regulatory obligations that apply between banking institutions and FinTech companies [ 21 ].

According to the Financial Stability Board (FSB) [ 23 ], “FinTech is a new financial industry that applies new technology to improve financial activities, including processes, products or even business models”.

The development of FinTech can be divided into three main time periods [ 5 ]: The first is defined from 1866 to 1967 and focuses on the development of the infrastructure of economic globalization. The second refers to the period from 1967 to the outbreak of the international financial crisis and is characterized by the transition to digital technology. A hallmark of this period is the emergence of ATMs (Automated Teller Machine), the foundation of NASDAQ as the world's first digital stock exchange and the World Bank Interbank Financial Telecommunications Company (SWIFT), which is a network of encrypted messages that transmit secure information and instructions. [ 5 ].

FinTech’s most recent achievements during this period are the development of e-banking and e-commerce which resulted in a huge impact of the banking system on everyday human life. [ 5 ].

Currently we face the third era of FinTech, which corresponds to the response of distrust towards the performance of the traditional banking system. This period is characterized by the introduction of cryptocurrencies and the widespread use of smart phones, which allow the execution of several financial services. In fact, in the last decade, Google's digital wallet and Apple Pay have been introduced, which allow their holders to make electronic payments. Arner et al. [ 4 ], consider that in contrast with the more developed economies, in the emerging economies of Asia and Africa, FinTech has begun to develop in recent years. Dorfleitner et al. [ 21 ], point out that FinTech companies can be divided into four main categories, depending on the sector they operate: financing sector, asset management sector, payment transactions and other FinTech (see Fig.  1 ).

Source: Dorfleitner et al. [ 21 ]

Categorization of Fintech firms

In addition to FinTech which act as financial intermediaries there are also data intermediaries TechFin companies which aim to take advantage of their relationship with customers in non-financial services to collect big data in order to provide them with purely financial products and services. TechFin companies create large-scale databases which allows them to offer financial services and become major non-banking players in the sector [ 57 ]. At the same time, FinTech companies may fill the gap or malfunction of the traditional banking system due to regulatory changes and the lack of technological and digital focus on the customer, providing solutions either directly or through the provision of know-how to existing banking providers.

3 The regulatory regime of FinTech firms in Europe

The global financial crisis in 2007 significantly affected financial services and had a catalytic effect on FinTech growth. Although several years have passed it was only recently that legislation and the implementation of some international regulations became mandatory for these companies. Regulatory provisions primarily appeared with the introduction of Regulatory Technology (Reg Tech) which expanded rapidly as a result of the growth of FinTech companies. In turn, the growth of FinTech companies, has attracted the interest of the banking industry, regulators and consumers. The aim of RegTech companies is to provide secure, cost-effective and reliable regulatory solutions through the latest digital technology [ 20 ].

After the crisis, there was an economic gap, mainly due to the loss of confidence in traditional banking institutions. New Regulations through Basel III resulted in increased costs for these institutions due to the new regulatory obligations they had to comply with and their obligation to perform stress tests on a frequent basis.

All these developments have led in the growth of FinTech industry, which competes credit institutions by providing cheap and innovative services. In the field of payment services, the original PSD (Payments Services Directive—PSD) (Directive 2007/64/EU) was strengthened the competition in the European Market and the Simple European Payment Area (SEPA). The PSD2 Directive that followed not only helped to broaden the definition of payment services, but also extended the categories of providers [ 42 ]. Both directives define and extend the information, requirements, rights and obligations of users, as well as payment services that facilitate money transfers [ 56 ]. However, the year 2018 can be said with certainty to be the year that changed the game for traditional banks and this is mainly due to the revised payment directive PSD2.

The main objectives of the PSD2 Directive [ 19 ] are to:

Contribute to the completion of an efficient European payment market.

Contribute to improving fair competition between banking and non-banking providers regarding payment services.

Promote competition in the new economic environment, where new innovative products and services are available.

Offer secure payments.

Reduce customer costs.

According to Navaretti et al. [ 42 ], almost all central banks in the EU have created innovation hubs that provide regulatory sandbox. In Greece, the FinTech Hub, which first appeared in March 2019, aims to enhance the interaction between banks and to facilitate the interaction of FinTech companies with the supervisory mechanism, which aims to enter the industry. Through this hub, it becomes clear that economic innovation is encouraged and implemented and therefore, in some way, a balance between risks and opportunities is ensured. This security has provided some form of support to businesses and individuals who are developing or considering introducing innovative products and services.

Due to the trend of convergence between banks and FinTech, the regulations focus mainly on the services provided and not on the provider and the main goal is to ensure that services and products are offered in full transparency [ 42 ].

To date, it seems that the financial services sector is undergoing a period of radical transformation. As a result, market forces and regulations are leading to the rapid growth of Open Banking. The legal basis is provided by the implementation of the PSD2 Directive creating a single Pan-European payment market. Third party access to customer data held by banks is also regulated and consequently banks cease to have exclusivity in their customer data [ 17 ].

4 Technology and efficiency of FinTech

Numerous analysts argue that although FinTech’s original goal was to eradicate traditional banks from the market by acquiring a dominant position, there are several cases where we can see partnerships between these companies and established traditional banking institutions. In this way, the FinTech companies were able to cope with the difficulties they had in increasing the number of their customers by achieving larger economies of scale.

According to Vives [ 54 ], the use of new technologies has significant implications for the financial sector, such as reducing transaction costs and the availability of new and higher quality products.

One could briefly claim that:

Big Data and the appropriate statistical models can control prospective borrowers more effectively, which is very important for tackling the problem of asymmetric information.

Allows targeted pricing policies as sophisticated interest rate models are used.

Less developed countries have access to financial services but also companies that until now did not have easy access to the banking system.

Through new technologies, the business plan can be implemented and served more efficiently.

5 Technological trends in banking sector

The growth of FinTech through newly established FinTech companies, contributed to the development of RegTech, due to the increased exposure to risk and the need for regulatory compliance. RegTech is considered as an evolving subcategory of FinTech. However, we could also see RegTech as a separate phenomenon, evolving through years (see Fig.  2 ).

Source: Arner et al. [ 2 ]

Stages of RegTech Development.

In general, the periods Reg1 (1967–2008) and Reg2 (2008–2018) are associated with the digitization of the regulatory authority, while the period Reg3 (2018-present) is related to the formation of an appropriate regulatory framework of the digital age.

More specifically, according to Arner et al. [ 2 ], Reg3 is the regulatory term directly linked to the future of RegTech. Concepts such as data dominance and algorithm monitoring now need to be modified as RegTech is used to control how regulations work and who should be subject to those regulations. It's the era marked by the transition from 'Know Your Customer' (KYC) to 'Know Your Data' (KYD). The main obstacle for RegTech is not the technological constraints, but probably the ability of regulators to process and analyze big data.

Therefore, regulators are required to develop systems that allow them to properly monitor and analyze all data. It is certain that the development of regulations has become necessary in order to meet the growing need for cybersecurity.

The technologies with the greatest impact on the FinTech growth are:

Blockchain technology Blockchain allows computer systems located in different places to propose, validate transactions and update the files of a common network at the same time and enhance efficiency [ 44 , 55 ]..

Blockchain information is not stored in a specific location, making malicious attacks more difficult, while the required time for transactions is limited. However, there are also new risks associated with money laundering, inadequate customer protection and tax evasion [ 20 ].

A main benefit of Blockchain technology is Smart Contacts which are based on a purely digital and complex computerized protocol and includes complex calculations, multi-party agreements, various forms of encryption and contributes to the make transactions safer. They also improve the ability of conducting contracts and offer easier confirmation that all obligations have been met, while at the same time, the monitoring time is being eliminated and therefore the contractual monitoring costs are reduced [ 24 ]. However, there is also a belief that Smart Contracts may create new legal requirements [ 9 ].

According to Saripalli [ 48 ], Blockchain can facilitate the decentralization of the last mile delivery channel, by enabling peer-to-peer and cashless transactions even among the unbanked population.

Application Programming Interface The Application Programming Interface (APIs), is the way of communication for two computer applications in a network, using the same communication code [ 56 ]. Through different channels offered by FinTech companies, banks can offer products and services of great flexibility and short time required, thus facilitating innovation [ 17 ].

According to Vishnu et al. [ 53 ], APIs have the same type of functionality in m-banking. They can be used to authorize the use of banking data by third parties. How banks are evolving over the years is important because, according to the OECD, the activities of the financial sector accounts for between 20 and 30% of the GDP of developed countries.

The open banking model is promoted by the Directive PSD2 and is based on APIs. It is an important data source, as it allows access to system’s data. This adds value to the bank, as through access to multiple data sources it receives valuable, difficult and complicated information. APIs are not a new reality in the banking system, as they are already used in the internal communication between the various infrastructure systems (or nodes). APIs are at the heart of the FinTech revolution, as they influence the way products and services are delivered and used. On the other hand, PSD2 allows access to customer information and communication from authorized third parties. According to Omarini [ 43 ], they have been created in order to ensure this compatibility.

Artificial Intelligence Artificial Intelligence (AI) is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior, whereas, machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly. Its popularity has increased, mainly due to the large volume of digital data, the growing need for data storage and the great progress that has been made in the algorithms that are applied [ 22 ].

According to Schlinder et al. [ 49 ], the applications of artificial intelligence are diverse and apply, inter alia, to regulatory reporting and data quality, monetary policy and risk analysis, as well as fraud monitoring and detection.

At the central bank level, AI has been integrated into functions that contribute to the identification of microeconomic and macroeconomic indicators [ 49 ], supervision, information management and forecasting and detection of malicious activities [ 22 ].

The benefits of AI application are manifold. In the financial sector, the use of AI and ML techniques increases efficiency, reduces transaction costs, improves service quality, provides smart investment solutions, increases and boosts customer satisfaction. In addition, AI and ML applications allow the institutions that use them to analyze all customer data to which they have access, learning about their preferences and thus developing specific products and services tailored to customer needs, while improving user experience [ 22 ].

Hsu [ 27 ] has developed a stock selection model in the S&P 500 and the FTSE 100, applying machine learning methods to enhance the performance of the benchmark for individual investors. The results of this study suggest that machine learning techniques are well applied in stock markets.

Villar and Khan [ 52 ], using artificial intelligence procedures, demonstrated how Deutsche Bank successfully automated Adverse Media Screening (AMS), speeding up compliance, increasing coverage for negative media, and drastically reducing false positives.

Virtual and Augmented Reality Augmented Reality (AR) and Virtual Reality (VR) are relatively new applications which are based on the principle of interaction. Their cost is still high, as they incorporate desktop, software, headphones, visual content and advertising costs [ 28 ]. According to Goldman Sachs, it is estimated that in 2025 the value of the VR market will amount to 25 billion dollars [ 34 ]. The technological revolution and the evolving customer base, led financial institutions to introduce AR and VR technology in financial services [ 28 ].

Robo Advisors Robo Advisors (RA) platforms provide automated portfolio management services that require minimal or even no human intervention, at a significantly lower cost than traditional consultants [ 47 ]. Automated service consultants or robotic consultants consist a new challenge in the financial services industry, providing investment, banking and insurance products. A well-known RA is the automated investment advisor in the financial sector [ 8 ]. A well-designed RA can be competent, honest and can recommend suitable products to their customers [ 7 ]. However, the motivation of those who plan or develop RA may not be objective as the applied algorithms may not be in favor of the customers’ benefit, but in favor of the providers [ 8 ]. According to Liu et al. [ 37 ], robotics is increasingly being used to automate customer interaction. In addition, robotics improve efficiency and the quality of execution Vishnu et al. [ 53 ].

Cloud Computing Cloud Computing (CC) is the on-demand availability of computer system resources, especially data storage, data sharing and remotely work through internet access. CC offers flexibility in the provision of services and the saving of resources. However, CC like APIs, if not segregated securely and not adequately monitored may cause serious problems [ 54 ].

6 Covid-19 pandemic and banking sector challenges

The Covid-19 pandemic has forced countries around the world to accept a new reality as almost everything in people's daily lives has changed dramatically. This new reality has forced financial institutions to move fast to protect both their employees and their customers, changing their operations and serving customers in new ways.

The coronavirus footprint was visible to both consumers and banks with small businesses in their clientele. The steps taken during the pandemic period will shape many banking activities in the future. What is certain, however, is that the need to "Stay Home" is rapidly accelerating the adoption of digital technologies. This increasing use of digital technology means at the same time reduced dependence on traditional banking branches, thus accelerating the transformation of the banking landscape. It is estimated that in China and Italy, just four weeks after the onset of the coronavirus, the increase in consumer digital choices increased by between 10 and 20%. This gained experience by consumers may change their trading behavior in the long run [ 1 ].

Currently, the implementation of a dynamic and flexible banking model seems inevitable. During the pandemic, the operation of bank branches was temporarily differentiated by incorporating remote work. If this continues on a more permanent basis, it will obviously affect the number of branches currently in operation as well as the number of bank employees. Such a scenario is expected to accelerate the conversion process of traditional banks to virtual banking, where the customer communicates with a specialized consultant via video call in order to conduct banking transactions, thus developing a model that relies heavily on remote consultants [ 1 ]. In the near future, it is very likely that customers will visit the bank branches relatively infrequently, as almost all of the services will be offered through e-banking, mobile banking or virtual banking. Therefore, the challenges are expected to be intense with long-term effects worldwide.

Especially in the case of Greece, the imposition of capital controls in 2015 contributed to the first rapid transformation of banking transactions where the paper currency was replaced by plastic money. The Covid-19 pandemic has pushed this transformation further. As the crisis progresses, we have more and clearer evidence of the impact on the behavior and expectations of customers and businesses but what is certain is that there can be no return to the methods applied before 2019 [ 1 ]. Banks need to develop new strategies taking into account certain internal and external factors. The new trends will definitely include great receptivity to digital channels. After the crisis, employees may be more willing to embrace new working models remotely. On the other hand, banks will have to face a prolonged period of low interest rates and reduced profits with tighter balance sheets and higher operating costs due to the new security measures and for their survival they must move immediately with the right decisions.

Thus, we see that although the global financial crisis of 2008 highlighted the seriousness of systemic risks to banks, in the case of the Covid-19 pandemic the risk was entirely due to factors unrelated to the banking system offering banks the opportunity to highlight their role as a systemic stabilizer. Banks need to learn from the two crises that emerged in 2008 and 2019 respectively and proceed directly to their own digital transformation, while at the same time creating a much higher degree of operational and financial resilience [ 16 ]. During the recent global crisis, banks were considered to be the biggest problem. Today, however, they are considered to be at the heart of problem solving [ 11 ].

7 Sample and hypotheses

Sample In the context of this study, we conducted questionnaires to collect information from the participants selected in our samples and the hypotheses were tested by non-parametric tests. For the purposes of our study, we use two separate groups and samples, constructing two independent questionnaires, oriented to the needs of our study.

The first sample includes consumers/users of banking products and services, regardless of the banking institution that are customers, who answered a questionnaire structured and tailored to their personal transactional needs, habits and desires. The survey was conducted in Greece during the period 28/12/2019–19/02/2020 where 300 questionnaires were distributed to users of which 241 questionnaires received feedback. 10 questionnaires were removed due to omissions in the answers and we finally obtained 231 valid questionnaires, with an effective rate of 77%. The sample consists of 117 women (50.65%) and 114 men (49.35%). The respondents are mainly under the age of 50 (n = 206, 89.15%) and only 42 (18.18%) of the respondents have not graduated from a higher education institution.

The second pool of our study includes the employees of Greek banks. This survey took place in Greece during the period 10/01/2020 to 12/02/2020. In order to investigate the banks employees’ convictions and opinions related to FinTech, we distributed 148 questionnaires to employees from which we received feedback on 120 questionnaires of which 16 questionnaires were deleted due to omissions. Thus, our final sample consists of 104 valid questionnaires, with an effective rate of 70.3%. The second sample of bank employees consists of 64 women (61.54%) and 40 men (38.46%). Participants under the age of 40 constitute the largest percentage (n = 97, 93.20%) while the 87 employees (83.65%) hold at least an undergraduate university degree.

The sampling for distribution and completion of both users’ and bank employees’ questionnaires followed the rules of sampling. In the case of bank employees, the questionnaires were distributed to employees of both bank branches and headquarters services during the time period mentioned above. Regarding the users, the questionnaires were distributed to citizens outside specified metro central stations during the period 28/12/2019 to 19/02/2020. Both questionnaires are listed in the appendix section at the end of the paper, while the empirical results with the corresponding tables are analyzed at the empirical part of the paper.

A common feature of both our questionnaires is that they include three critical questions to test our hypotheses, regarding the demographic characteristics, gender, age and educational level of the respondents.

Hypotheses The users’ questionnaire was constructed by categorizing the questions into four subgroups, which emerged from the research questions and led to the hypotheses testing of the study. A total of twenty questions are included:

The intention to use FinTech services

The perception of the usefulness offered by FinTech services

The trust and the perception of the risk that is integrated in the FinTech services

The preference between FinTech services and services provided by traditional banking branches

On the other hand, bank employees were asked to answer a questionnaire consisting of thirteen questions structured in four subgroups, according to the research needs and the hypotheses testing:

The knowledge they have in new technologies

The degree of adoption of new technologies

The perceived usefulness of new technologies

The perception they have regarding the digital transformation and employment

More specifically, the following hypotheses are considered:

Do users take advantage of the opportunities provided by FinTech companies?

Do they receive sufficient satisfaction from the use of FinTech services?

Do they trust FinTech companies and/or banks for securely making transactions?

Do bank employees have thorough knowledge on new technologies and to what extent they adopt them in their professional environment?

According to bank employees how useful new technologies are for their work and for customers’ satisfaction and whether there may be a negative impact on future employment?

8 Empirical approach

For each variable we examine descriptive statistics average, median, standard deviation and variance and then Kolmogorov Smirnov and Shapiro Wilk tests for normality is applied.

However, as the samples do not follow normal distribution, we apply the non-parametric tests:

Kruskal–Wallis test.

Chi-squared (X^2) test for independence.

rs rank-order Correlation Coefficient (Spearman test).

In our research we are interested to examine which variables from both questionnaires are affected and differentiated by demographic factors, i.e. gender, age and educational level. As the data from both samples do not follow the normal distribution, non-parametric tests at 5% significance level will be tested. When P-value is less than 5%, the examined variable is not independent by each tested demographic factor. Thus, in the next step non -parametric tests follow a single factor (non-parametric dispersion analysis), using Kruskal–Wallis non parametric tests.

We apply the non-parametric Kruskal–Wallis test by ranks, or one-way ANOVA on ranks for testing whether samples originate from the same distribution [ 18 , 35 , 50 ]. This is a way for comparing two or more independent samples of equal or different sizes and tests whether the difference is statistically significant related to their median. It extends the Mann–Whitney U test, which is used for comparing only two groups. The parametric equivalent of the Kruskal–Wallis test is the one-way analysis of variance (ANOVA).

A significant Kruskal–Wallis test indicates that at least one sample stochastically dominates over the other sample. Since it is a non-parametric method, the Kruskal–Wallis test does not assume a normal distribution of the residuals, unlike the analogous one-way analysis of variance. Kruskal–Wallis test is widely used to test small-sized non-parametric models, as it provides exact probabilities for sample sizes even less than about 30 participants. It is indicative that the mechanism behind Kruskal–Wallis test has the possibility to adequately estimate smaller samples, relying on asymptotic approximation for larger sample sizes. Spurrier [ 51 ] published exact probability tables for samples as large as 45 participants, while Meyer and Seaman [ 39 , 40 ] produced exact probability distributions for samples as large as 105 participants. In order to use the Kruskal—Wallis criterion (K-Intependent Samples), we test for the following hypotheses:

The null hypothesis is accepted when P (value) is greater than 0.05, while when P (value) receives price less than 0.05 the null hypothesis is rejected in comparison to the alternative one (H1).

Validity and Reliability Tests Before we applied the proposed conceptual model, we have tested the internal reliability and validity of the scales by calculating the Cronbach alpha coefficient. Cronbach's alpha tests the internal consistency among a set of items. It is a scale reliability measure and its value ranges from 0 to 1. When Cronbach alpha value equals to 0 it implies that scale is perfectly unreliable whereas a value 1 suggests that it is perfectly reliable. When Cronbach alpha value is greater than 0.5 the scale is considered reliable and therefore it is acceptable, whereas if it is over 0.7 the scale is considered very reliable. The Cronbach alpha value depends on the number of the items, the inter-item covariance and the average variance.

The reliability of the Cronbach alpha value for the first questionnaire addressed to users is 0.708 whereas, the reliability of the Cronbach alpha value for the second questionnaire addressed to the employees is 0.796.

9 Empirical results

The following tables (1 and 2) summarize the cases where we compare the variables and we find different medians (p < 0.05) which implies differences in statistical significance.

For the first, users’ questionnaire, we found the following results, in Table 1 :

On the other hand, from the answers of employees in the second questionnaire we find the results presented in Table 2 :

Chi-square Χ 2 testing At this stage the Chi-square (Χ^2) test for independence was performed in order to determine whether the questionnaire’s variables are independent, not correlated to the demographic data of the sample. According to the null hypothesis (H0), the variables are independent between each other (p > 0.05) and the alternative hypothesis (H1), the variables are not independent between each other (p < 0.05) but at least some dependence is present. In the following tables (3–7) we present the cases where null hypothesis is rejected (p < 0.05) implying statistical significance for these relationships, meaning that cases on the other hand with evidence of statistical significance imply that variables are not independent.

Empirical analysis of users’ questionnaire

For the users’ questionnaire we can see the following results in Table 3 :

Chi-square Χ 2 test for independence according to gender

Based on Table 3 which shows some kind of dependency on gender, we observe that the highest value (v = 25.218) is given to the knowledge of digital currencies, such as Bitcoin or Litecoin. The lowest value (v = 9.988) corresponds to the possibility of recommending FinTech services to friends and the users’ families. Therefore, we can suggest that data with dependency on both genders are mainly evident, indicating the intention for using FinTech services. In addition, there is a statistical significant dependence relationship between trust and gender, as well as a comparison between FinTech companies and traditional banking branches, regardless gender.

Chi-square Χ 2 test for independence according to age

In the above Table 4 , we can observe some kind of dependency on the users’ age in relation to their view whether FinTech services provide better services relatively to traditional banks as it receives the highest value (v = 26.402). On the contrary, the lowest price (v = 8.896) corresponds to the question that according to users, funding can be consider as an interesting FinTech area of action. Therefore, the questions which show the highest dependence between age and users’ responses include all the variables which examine the trust and the implied risk for FinTech services as well as the questions that compare FinTech with the traditional banks branches. Another dependence emerging relationship is that between users’ age and their intention for using FinTech services.

Chi-square Χ 2 test for independence according to educational level

Based on the above Table 5 regarding the questions that have some kind of dependence on users’ education level, the highest value (v = 61.441) corresponds to the importance of interaction between the banks and the use of mobile phones. On the other hand, the question related to the availability of services as a selection factor for non-banking providers corresponds to the lowest value (v = 12.939). So far, the main questions with the highest dependence with the users’ educational level are those which examine the intention to use Fintech services.

Empirical analysis of employees’ questionnaire

At this section the analysis focus on the main results derived from the elaboration and test of employees’ questionnaire.

In the above Table 6 , we present only the questions that have some dependence on the gender. The most important results are linked with the existence of dependence between the employees’ gender and the assessment of innovation (ν = 8.821) and the facilitation of daily work with the use of new technologies, such as digitization (ν = 8.894).

Table 7 shows the employees’ responses being affected by their educational level. These responses are related to the degree of effective customer service through the use of technological innovation (ν = 25.301), the readiness to meet the requirements of new technology (ν = 19.548) and the automation of work as a threat to their employment conditions.

In addition, the Chi-square Χ 2 test for independence according to the age of the employees does not show any kind of dependence between the respondents’ answers and their age.

Summing up the above analysis, we find that in the first questionnaire addressed to the users, the demographics related to the age and education level are somewhat dependent with several questions from almost every subgroups of the questionnaire, whereas, compared to the gender it seems to be dependent on specific responses related mainly to the knowledge of FinTech services and trust on FinTech services. Concerning the employees, we can come to the conclusion that demographic characteristics of the sample in relation to the gender and education are dependent on specific responses such as the services innovation, work facility, readiness for using FinTech, effectiveness in serving customers and the impact of new technologies for their employment future. On the contrary, dependence is not present in the relationship between the age of the employees and the responses in the questionnaire.

rs rank-order Spearman Correlation Coefficient

Spearman's correlation coefficient or Spearman's r{s}, is a nonparametric measure of ranking correlation as it tests for the existence of statistical dependence between the rankings of two variables. Alternatively, it can assess how well the relationship between two variables is described using a monotonic function. When there are no repeated data values means that a perfect Spearman correlation of + 1 or − 1 occurs as each of the variables is a perfect monotone function of the other. Intuitively, the Spearman correlation between two variables will be high when observations have a similar (or identical for a correlation of 1) ranking between the two variables, and low when observations have a dissimilar (or fully opposed for a correlation of − 1) ranking between the two variables.

According to the null hypothesis (H0) tests show that variables are not related between each other, meaning that it does not seem to have any kind of dependence (p > 0.05). On the other hand, the alternative hypothesis (H1) tests whether variables are correlated to each other, meaning there is a dependence relationship (p < 0.05) between the examined variables. The following Tables 8 , 9 show that questionnaire responses reject the null hypothesis (H0) accepting the alternative hypothesis (H1) so there is a dependence relationship.

The above Table 8 illustrates the dependence relationship that exists between the demographic data of the sample and the responses from the users’ questionnaire. Thus, the knowledge of adding digital banks/FinTech companies to the financial sector, the knowledge of digital currencies and the question that examines the equivalence of trust between traditional banks and FinTech companies being under the supervision of the European Supervisory Authorities are positively related to users’ gender. Regarding the respondents’ educational level, the questions related to the degree of price, quality and availability of services importance are positively dependent with users’ educational level. On the other hand, we observe a negative correlation between educational level and the questions related with the knowledge of digital currencies, the choice for specific services such as TransferWise, Currency, Peer Transfer, Currencies Direct, the quality and availability of services as non-selecting a non-banking provider.

In terms of age, there is a positive correlation between the responses the users’ age with and the existence of greater trust of users in traditional banks in terms of transactions and personal data management, increased risk undertaken through the use of FinTech services, the speed as a very important factor of selecting a non-banking provider and the increased transactions insurance as an interesting FinTech area of operating. Last but not least, there is a negative dependence relationship between users’ age and the cooperation with a bank through smart phones.

Table 9 shows the dependence between the demographic characteristics of the employees and the corresponding questionnaire.

Regarding the respondents’ gender, there is a positive dependence between the assessment of innovation of traditional banks and the facilitation of the daily work through the use of new technologies and employees’ gender.

As far as the respondents’ age is concerned, there is a negative dependence between their age and the choice of specific services such as Zopa, Lending Club, Funding Circle and Rate Setter.

In terms of employees’ education, the readiness to meet the requirements of new technology is positively dependent to educational level. Finally, the subgroup which is related to digital transformation and employment is not dependent with any of the sample demographics.

Main Implications of Empirical Results Taking into account the empirical surveys conducted at the level of users and bank employees, the main findings that emerged are the following:

The vast majority of users seem to prefer only financial institutions to conduct their banking transactions. According to the literature, FinTech has great potential and is active in various fields. However, the present study shows that users only know payment services as FinTech's area of activity as almost no other activity was reported in the questionnaire responses. Payment services are the activity of most interest to FinTech companies, while the second most important activity is the trading of shares and investments. It is worth noting that most customers who have used payment services have opted for PayPal. This conclusion is also in line with the answers of the bank employees. This is a clear sign that FinTech services in Greece are still at an early stage of development.

Although there are several factors that affect the decision to use FinTech services, the security factor seems to be of paramount importance for the users. In the case of trust, the majority of the respondents indicate that they trust traditional banks more than other non-financial institutions. According to the literature, the main advantages of banks are the regulatory compliance and the confidence between the bank and its customers, which is built over the years.

Regarding the adoption of new technologies by banks, it seems that, admittedly, Greek banks have given the necessary weight to the digital transformation and have made significant investments. The increased pressure on traditional banking institutions to modernize their core business activities is mainly due to the parallel penetration of new technology-oriented companies. From the results of the present study, the digital transformation seems to be a one-way street and will continue to light the way for the technological revolution. Also, the findings of the study show that banks have invested significantly in education, offering employees the opportunity to acquire the necessary skills to meet modern needs and be able to further develop their skills. It seems that Greek banks have largely focused their investment strategy on staff training. Another conclusion is that only a small percentage of bank employees feel fully prepared to face the new technological reality, although based on their educational level, this percentage is expected to be higher soon.

Regarding their future employment, employees seem to be worried and their prevailing position is that for a job that needs mainly automated movements, there is high risk of dismissal. The majority of respondents believe that artificial intelligence and robotics are likely to replace a wide range of professional skills and pose a risk to their personal work and further professional development. The literature shows that artificial intelligence has a very important role as it intervenes and disrupts the activities in tasks traditionally performed by humans. However, its impact on the work is not clear and opinions vary substantially. Professions that require a high degree of creative intelligence, are less likely to be replaced by smart machines in the next decade.

Non-parametric tests show that in matters of trust, security and protection of personal data, the majority of the sample shows a preference for traditional banking institutions and seems to be age-dependence. The importance of interaction with the use of smartphones seems to depend on users’ age and educational level. On the other hand, for bank employees it holds that their educational level clearly plays an important role in the degree of readiness and response to new technologies.

10 Conclusions

FinTech has come to stay is sure to force reform in many areas, mainly intervening technologically and creating competition. In this way there is a view that argues that business activities that have traditionally been vital to the banking sector are threatened. What is certain is that companies that have decoded developments in time and invested significant capital in technology and human resources will be ready for the digital transformation, which will give them a comparative advantage over other companies.

The best way for banks to stay competitive in the new era, is to implement Open Banking, which is both an opportunity and a threat to banking institutions. The threat comes mainly from the limited ability to control the interaction between banks and their customers. However, the most important element that should not be lost in the new economic landscape is the trust of all stakeholders (banks, FinTech, TechFin, regulators and users). A new open platform between banks and FinTech is sure to be an advanced environment for increasing bank innovation. For example, through the Open Banking environment, customers will be able to view all their accounts and transactions independently of the bank provider on a 24-h basis.

It is obvious that in the coming years we will be able to know who the real winner will be, between the FinTech companies and the banking institutions. According to the existing literature, the one that will prevail will be any more investments to succeed in turning it into a customer-centric organization, even if it is a new coalition or collaboration that will consist of both players [ 43 ].

It is accepted that the 4th Industrial Revolution has transformed modern enterprises by causing radical changes in the banking sector. Global banking giants have begun to be challenged by new players, while at the same time FinTech and BigTech are claiming market share, creating major changes in consumer patterns and habits.

The main results of the current study imply that users only know payment services as FinTech's area of activity and prefer to use for their transactions PayPal. It is worth noting that payment services consist the most invested activity for FinTech firms.

Security, trust and protection of privatization seems to be by far the most significant factors affecting users in conducting transactions, using new financial technologies and that is mostly argued by trusting traditional banks more than other non-financial institutions. For their transactions, most of customers use smart phones, whose use depends on users’ age and educational level.

Moreover, banks have invested significantly in education, offering employees the opportunity to acquire the necessary skills to meet modern needs and be able to further develop their skills. However, only a small percentage of bank employees feel fully prepared to face the new technological reality. One equally important conclusion for employees’ part is that they consider themselves in risk of being dismissed due to the automation of many jobs. In addition to the above, for bank employees it holds that their educational level clearly plays an important role in the degree of readiness and response to new technologies.

In conclusion, the present study shows that we must be focused on the new generation that will be the basis for the banking system in the future and those in charge to target the needs and expectations of the "Millennials" while at the same time appropriate investments in technology and knowledge must be planned. Recent literature shows that FinTech companies may look and act like banks, but they are not yet set up as banks. It is also worth mentioning that in cases of pandemics, such as Covid-19, the importance of FinTech is highlighted while financial technology in all areas of activity becomes more important than ever. The coronavirus crisis has helped the banking sector take steps of digital transformation in the short term, something that would otherwise take longer to take place. What is certain is that these new developments will "force" customers to adapt to these unprecedented conditions, while creating new business habits, regardless of age and educational level. Questions such as what is the real relationship between banks and FinTech companies, who is most affected and by whom, are interesting topics for future investigation as well as to repeat the current study after the end of the Covid-19 crisis to compare the results, even expanding the study to incorporate the financial systems of more Member States in the E.U.

The above conclusions must be taken into account by the competent regulatory authorities in order to shield the economy with the necessary institutional framework for the operation of the FinTech companies, as well as the Basel Committee for the reconsideration of Basel regulations.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Adarkar A, Hyde P, Maxwell M, Sridharan A (2020) Leading a consumer bank through the coronavirus pandemic. Retrieved from https://www.mckinsey.com/~/media/McKinsey/Industries/Financial%20Services/Our%20Insights/Leading%20a%20consumer%20bank%20through%20the%20coronavirus%20pandemic/Leadinga-consumer-bank-through-the-coronavirus-pandemic-final.ashx . Accessed 18 May 2020

Arner DW, Barberis JN, Buckley RP (2018) FinTech and RegTech in a Nutshell, and the Future in a Sandbox. SSRN Electron J. https://doi.org/10.2139/ssrn.3088303

Article   Google Scholar  

Arner DW, Barberis JN, Buckley RP (2017) The emergence of Regtech 2.0: from know your customer to know your data. SSRN Electron J. https://doi.org/10.2139/ssrn.3044280

Arner D, Barberis J, Buckley R (2016) 150 years of Fintech: an evolutionary analysis. Jassa (3):22. Retrieved from https://www.researchgate.net/publication/313364787_150_Years_of_FinTech_An_Evolutionary_Analysis . Accessed 17 Jan 2020

Arner DW, Barberis JN, Buckley RP (2015) The evolution of fintech: a new post-crisis paradigm? SSRN Electron J. https://doi.org/10.2139/ssrn.2676553

Arner D, Barberis J, Buckley R (2017) FinTech, RegTech, and the Reconceptualization of Financial Regulation. Northwestern. J Int Law Bus 37(3):371–413

Google Scholar  

Baker T (2018) Regulating Robo advice across the financial services industry. Regulating Robo Advice Across the Penn Law: Legal Scholarship Repository. Faculty Scholarship at Penn Law, 1740. https://scholarship.law.upenn.edu/faculty_scholarship/1740

Baker T, Dellaert B (2018) Regulating robo advice across the financial services industry. Iowa Law Rev 103(2):713–750. https://doi.org/10.2139/ssrn.2932189

Bakos Y, Halaburda H (2019) When do smart contracts and IoT improve efficiency? Automated execution vs increased information. SSRN Electron J. https://doi.org/10.2139/ssrn.3394546

Basdekis H, Christopoulos A, Katsampoxakis I, Lyras A (2020) Profitability & optimal debt ratio of the automobiles & parts sector in the Euro αrea. J Cap Mark Stud 4(2):113–127. https://doi.org/10.1108/JCMS-08-2020-0031

Bensley E, Chheda S, Schiff R, Stephens G, Zhou N (2020) Remaking banking customer experience in response to coronavirus. Retrieved from https://www.mckinsey.com/~/media/McKinsey/Industries/Financial%20Services/Our%20Insights/Remaking%20banking%20customer%20experience%20in%20response%20to%20coronavirus/Remakingbanking-customer-experience-in-response-to-coronavirus-vF.ashx . Accessed 25 May 2020

Braggion F, Manconi A, Zhu H (2018) Can Technology Undermine Macroprudential Regulation? Evidence from Peer-to-Peer Credit in China, Centre for Economic Policy Research, London, Retrieved from https://cepr.org/active/publications/discussion_papers/dp.php?dpno=12668 . Accessed 24 Mar 2020

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

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

Buehler K, Conjeaud O, Giudici V, Samandari H, Serino L, Vettori M, White O (2020) Leadership in the time of the coronavirus: COVID-19 response and implications for banks. Financ Serv Pract. Retrieved from https://www.researchgate.net/publication/343080322_Leadership_in_the_time_of_coronavirus_COVID-19_response_and_implications_for_banks . Accessed 15 Apr 2020

Camerinelli E (2017) Open bank, APIs, and Financial services ecosystems: the future of banking. Retrieved from https://www.softwareag.com/corporate/images/Aite_Group_Open_bank_api_and_financial_services_Research_Jul17_tcm389-167453.pdf . Accessed 7 Feb 2020

Corder GW, Foreman DI (2009) Nonparametric statistics for non-statisticians. Wiley, Hoboken, pp 99–105 ( ISBN 9780470454619 )

Book   MATH   Google Scholar  

Hafstad T, Zenna J, Johansson HZ, Crompton F, Ullgren D, Johnston J, Øyn MP (2017) PSD2 – Strategic opportunities beyond compliance. How PSD2 will open up the European financial landscape and strategies for how banks can take the leading positions, Evry, 8-56. Retrieved from https://ctmfile.com/assets/ugc/documents/PMK_Evry_psd2.pdf . Accessed 07 Jan 2020

Davradakis E, Santos R (2019) Blockchain, FinTechs and their relevance for international financial institutions. EIB Working Paper 2019/01 https://doi.org/10.2867/11329

Dorfleitner G, Hornuf L, Schmitt M, Weber M, Dorfleitner G, Hornuf L, Weber M (2017) The FinTech market in Germany. In: FinTech in Germany, pp 13–46. https://doi.org/10.1007/978-3-319-54666-7_4

Fernandez A (2019) Artificial intelligence in financial services. SSRN Electron J. https://doi.org/10.2139/ssrn.3366846

Financial Stability Board (FSB), https://www.fsb.org/work-of-the-fsb/financial-innovation-and-structural-change/fintech/ . Accessed 06 Jan 2020

Gans JS (2019) The fine print in smart contracts. SSRN Electron J. https://doi.org/10.2139/ssrn.3309709

Hannan, TH, McDowell JM (1984) The determinants of technology adoption: the case of the banking firm. RAND J Econ 15(2):328–335

Hornuf L, Haddad C (2019) The emergence of the global fintech market: Economic and technological determinants. Small Bus Econ 53(1):81–105. https://doi.org/10.1007/s11187-018-9991-x

Hsu TY (2021) Machine learning applied to stock index performance enhancement. J Bank Financ Technol. https://doi.org/10.1007/s42786-021-00025-6

Hutchison D (2018) Using virtual reality to explore science and literacy concepts. International Literacy Association. https://doi.org/10.1002/trtr.1720

Book   Google Scholar  

Karsh SA, Abufara Y (2020) The new era of financial technology n banking industry. J Southwest Jiaotong Univ. https://doi.org/10.35741/issn.0258-2724.55.4.54

Katsampoxakis I, Basdekis H, Anathreptakis K (2015) How firm and market characteristics affect profitability: an empirical study. Int J Corp Finance Account. https://doi.org/10.4018/IJCFA.2015010104

Katsampoxakis I, Basdekis H, Anathreptakis K (2018) How the Greek crisis determined firm profitability and optimal debt ratio. In: Zopounidis C, Christopoulos A, Kalantonis P (eds) Perspectives, trends, and applications in corporate finance and accounting. IGI Global Publications. https://doi.org/10.4018/978-1-5225-6114-9.ch001

Chapter   Google Scholar  

Katsampoxakis I (2021) ECB’s unconventional monetary policy and spillover effects between sovereign and bank credit risk. EuroMed J Bus. https://doi.org/10.1108/EMJB-09-2020-0103

Keliuotyte G, Smolskyte G (2019) Possibilities for financial technology sector development and its impact on banking sector profitability in Lithuania. Econ Cult 16(1):12–23

Kołodziej M (2017) Virtual reality as the indicator of the modern banking. Financ Sci 2(31):44–51. https://doi.org/10.15611/nof.2017.2.04

Kruskal W (1952) Use of ranks in one-criterion variance analysis. J Am Stat Assoc 47(260):583–621. https://doi.org/10.1080/01621459.1952.10483441

Article   MATH   Google Scholar  

Lee I, Shin Y (2018) Fintech: Ecosystem, business models, investment decisions, and challenges. Bus Horiz 61(1):35–46

Liu FH, Norden L, Spargoli F (2020) Does uniqueness in banking matter? J Bank Finance. https://doi.org/10.1016/j.jbankfin.2020.105941

Meyer JP, Seaman MA (2013) A comparison of the exact Kruskal-Wallis Distribution to asymptotic approximations for all sample sizes up to 105. J Exp Educ 81(2): 139–156, https://www.jstor.org/stable/26594373 . Accessed 10 Jan 2020

Meyer JP, Seaman MA (2006) Expanded tables of critical values for the Kruskal–Wallis H statistic. In: Paper presented at the annual meeting of the American Educational Research Association, San Francisco. Critical value tables and exact probabilities from Meyer and Seaman are available for download at  http://faculty.virginia.edu/kruskal-wallis/Archived2018-10-17attheWaybackMachine . Acessed 17 Oct 2018

Mitra S, Karathanasopoulos A (2020) FinTech revolution: the impact of management information systems upon relative firm value and risk. J Bank Financ Technol 4:175–187. https://doi.org/10.1007/s42786-020-00023-0

Navaretti GB, Calzolari G, Pozzolo AF (2018) Fintech and banking: friends or foes? SSRN Electron J. https://doi.org/10.2139/ssrn.3099337

Omarini AE (2018) Banks and Fintechs: how to develop a digital open banking approach for the bank’s future. Int Bus Res 11(9):23. https://doi.org/10.5539/ibr.v11n9p23

Peters GW, Panayi E (2016) Understanding Modern Banking Ledgers Through Blockchain Technologies: Future of Transaction Processing and Smart Contracts on the Internet of Money. In: Tasca P, Aste T, Pelizzon L, Perony N (eds) Banking Beyond Banks and Money, New Economic Windows. Springer, Cham, pp 239–278. https://doi.org/10.1007/978-3-319-42448-4_13

Philippon T (2015) Has the US finance industry become less efficient? On the theory and measurement of financial intermediation. Am Econ Rev 105(4):1408–1438

Sanjay P, Kerri R (2017) An Ipsos point of view robo-advisors: the rise of automated financial advice. Retrieved from https://www.ipsos.com/sites/default/files/2017-07/IpsosMarketing_POV_RoboAdvisors.pdf . Accessed 17 Jan 2020

Saripalli SH (2021) Transforming Government banking by leveraging the potential of blockchain technology. J Bank Financ Technol. https://doi.org/10.1007/s42786-021-00035-4

Schlinder J, Nolens BN, Frost J, Armstrong P (2017) Artificial intelligence and machine learning in financial services—market developments and financial stability implications. Financial Stability Board, 45. Retrieved from http://www.fsb.org/2017/11/artificial-intelligence-and-machine-learning-in-financial-service/ . Accessed 15 Jan 2020

Siegel C (1988) Nonparametric statistics for the behavioral sciences, 2nd edn. McGraw-Hill, New York ( ISBN 0070573573 )

MATH   Google Scholar  

Spurrier JD (2003) On the null distribution of the Kruskal-Wallis statistic. J Nonparametr Stat 15(6):685–691. https://doi.org/10.1080/1048525031000163471

Article   MathSciNet   MATH   Google Scholar  

Villar AS, Khan N (2021) Robotic process automation in banking industry: a case study on Deutsche Bank. J Bank Financ Technol 5:71–86

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

Vives X (2019) Digital disruption in financial markets. Note by Professor Xavier Vives. OECD, 1–28, Retrieved from http://www.oecd.org/daf/competition/digital-disruption-in-financial-markets.htm . Accessed 09 Jan 2020

Wood GABA (2015) Advancing egalitarianism. In: Chuen LKDE (ed) Handbook of digital currency: bitcoin, innovation, financial instruments, and big Data. Elsevier, London, pp 385–401

Zachariadis M, Ozcan P (2017) The API economy and digital transformation in financial services: the case of open banking. SSRN Electron J. https://doi.org/10.2139/ssrn.2975199

Zetzsche DA, Buckley RP, Arner DW, Barberis JN (2017) From FinTech to TechFin: the regulatory challenges of data-driven finance. SSRN Electron J. https://doi.org/10.2139/ssrn.2959925

Download references

Open access funding provided by HEAL-Link Greece.

Author information

Charalampos Basdekis, Apostolos Christopoulos, Ioannis Katsampoxakis, Aikaterini Vlachou—alphabetical order.

Authors and Affiliations

Department of Economics, National & Kapodistrian University of Athens, Athens, Greece

Charalampos Basdekis

Hellenic Open University, Patra, Greece

Charalampos Basdekis, Apostolos Christopoulos & Aikaterini Vlachou

University of West Attica, Egaleo, Greece

Department of Business Administration, University of the Aegean, Chios, Greece

Apostolos Christopoulos

Department of Statistics and Actuarial, Financial Mathematics, University of the Aegean, Samos, Greece

Ioannis Katsampoxakis

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Ioannis Katsampoxakis .

Questionnaire of users/consumers

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Basdekis, C., Christopoulos, A., Katsampoxakis, I. et al. FinTech’s rapid growth and its effect on the banking sector. J BANK FINANC TECHNOL 6 , 159–176 (2022). https://doi.org/10.1007/s42786-022-00045-w

Download citation

Received : 07 October 2021

Accepted : 03 November 2022

Published : 28 November 2022

Issue Date : October 2022

DOI : https://doi.org/10.1007/s42786-022-00045-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Banking Industry
• Covid-19 pandemic
• Find a journal
• Publish with us
• Track your research

Search form

7 game-changing innovations that will re-boot banking.

Share this article

Estimated reading time: 5 minutes

Apps. Contactless. Bots. Blockchain. Biometrics, AI, The Cloud... . The financial services industry has committed itself to digital innovation over the last 10 years. It’s just the start. 

Banking might seem like a traditional industry. But it has always innovated. From bank notes to cheque books to credit and debit  cards, the banking sector’s big ideas have reverberated across the world.

The current pace of change, however, is at another level. Today, technological innovation is re-defining how banks operate and the services they offer to customers. 

In fact, it’s even re-framing what a bank is.

Let’s dive into seven of the biggest trends we can look forward to.  

#1. Digital innovation starts a new age of self-service

James Brown sang: ‘I don't want nobody to give me nothing. Open up the door. I'll get it myself.’

The Godfather of Soul was expressing – in his inimitable way – the human desire for autonomy. It’s a universal feeling. Any time that consumers are given the opportunity to take back a little control, they take it.

People also want instant gratification. Today, the desire for immediately delivered services is just as strong as the demand for self-service. It brings to mind another song lyric, this time from Queen. “I want it all! I want it now!”

Banking is a good example of an industry that has met these needs. Across its history, customers have always gravitated to self-service innovation – a process that started with ATMs and is now evident in the rise of mobile banking and chat bots.

The speed with which the mobile app has displaced the physical branch has been remarkable. According to 2021 research by Ipsos-Forbes , 76 per cent of Americans say they used their bank’s app in the last year for banking tasks such as depositing a check or viewing account balances.

But today’s apps do much more than providing an alternative to these ‘everyday’ banking services. Thanks in part to competition from fintechs, the banks have enhanced their apps with a constant stream of useful new features. Examples include:

•    Financial planning

Many banking apps now let customers group their payments by type. This way, they can see at a glance where their money is going. They can set caps on, say, coffee or personal grooming and receive alerts when they are near their limits.

•    Turn a card off and on

If a card is lost or stolen, it’s easy to disable it from the mobile app. Consumers can easily lock the card with a few taps on their phone. They can also report fraud directly from the app, or order a new one and use it to pay online or at stores right away. These features are proving incredibly popular. More than one billion people now use mobile wallets.

•    Spare change investing

Here’s an easy way for consumers to save: round up the money spent in a store and invest the ‘spare change’. For example, buy a coffee for $2.75, and let the app round it up to $3 and then invest the 25c. Many banking apps now offer this feature to their account holders.   

#2. Contactless payment: set to change the way we pay 

Contactless payment took a while to take off. However, by the end of the 2010s take-up was growing fast. Then, in 2020, the pandemic accelerated this usage. Now it’s ubiquitous on cards, mobile phones and wearables.  

Rising upper limits on contactless payments have helped. In the UK for example, the ceiling started at £15 in 2014, then rose to £30, before moving to £45 in April 2020. In October 2021, the limit was increased to £100 . 

Data shows what a difference this made. In July 2021, Visa confirmed it processed 1bn contactless transactions across Europe in 12 months. Its research also found that two-thirds of global consumers plan to increase their use of contactless payments in the future.

So there's no going back now. Customers are sticking with contactless. Indeed, Mastercard recently confirmed it will phase out its magnetic stripe cards from 2024 .

Contactless payment was made possible by the introduction of Near Field Communication tech . NFC is an upgrade of RFID technology – a chip that enables short-range communication between compatible devices. These devices can be anything from a card to a tag to a smartphone. 

But how does it actually enable in contactless payments? Let’s go deeper.

How does mobile payment work?

When phone makers started to put NFC and QR tech in their handsets, they made it possible for phones to become payment devices. Using NFC, Google and Apple gave banks and card networks the ability to de-materialize payment cards and place them in wallets such as Google Pay and Apple Pay. 

This is convenient for customers, since they can load multiple cards into one wallet . It’s also very safe. Why? Because the user has to unlock the app (with a PIN or biometric method) before tapping on the reader. Meanwhile the industry has created advanced security frameworks to protect the stored payment credentials.

In 2021, the industry unveiled an important new innovation to its Card Verification Method on Consumer Devices (CD-CVM). It launched the EMV biometric payment card .

Introducing a contactless card with a fingerprint sensor

The new EMV biometric payment cards embed a fingerprint sensor on the card body to provide an extra element of authentication. This is a breakthrough innovation – especially for those consumers who love the convenience of contactless but worry about the lack of PIN entry.

Biometric payment cards also make it possible to increase spending caps. Some issuers will maintain PIN code entry for exceptionally high transactions, but otherwise contactless without a PIN code entry will become the new normal. 

It suits retailers too. No upgrade is required on the POS, as the biometrics check is directly performed on the card and nowhere else. Data is not kept on the bank's servers or sent over the air in store.

Various commercial deployments of these new biometric payment cards are underway. The biggest, by French bank BNP Paribas, is now rolling out in partnership with Thales .

Contactless payment extends to wearables

The other big contactless payment trend is extending the tech to new device types. Manufacturers are waking up to the idea that if you can put an NFC chip in a card, phone, watch or item of jewellery. As consumers become more used to paying with a tap, they are starting to embrace this idea.

Fintech start-ups are experimenting. In Japan, for example, EVERING recently launched a waterproof ceramic NFC ring . The battery-less product requires no charging, and marries fashion with technology. Thales provided the embedded chip and card personalisation services for the device. 

Wearable payment devices look good and they are also very secure. EVERING users, for example, can disable the ring via a mobile app linked to their credit card.  

#3. Banks are investigating new forms of biometric authentication

As we have seen from the contactless section above, strong authentication really matters. Passwords and PINs offer some protection, but they can be breakable – and people often forget them.

Biometrics offer a stronger protection: what you are, in addition to than what you know or what you possess.

Fingerprint ID may have started this evolution, but biometric innovation is now extending to more unique attributes. 

Many banks and card firms are exploring facial recognition as a way of authenticating a customer’s identity. Mastercard has already launched its ‘Identity Check Mobile’ feature, which is better known as ‘selfie pay’ . Here, the cardholder can verify his or her identity using the facial recognition technology in the phone. It eliminates the need to remember passwords to confirm online payments.

This kind of authentication is not only safe, it’s also quick. It can reduce the previously time-consuming ‘analogue’ process of creating a new account to just ten minutes.

Another form of biometrics attracting lots of attention is voice. Speaking your identity is not only secure and convenient, it is also better fitted to situations such as driving – keeping hands on the wheels and eyes on the road. 

A handful of banks have made it possible to make payments by voice. Royal Bank of Canada (RBC) lets customers ask Apple’s Siri assistant to pay their bills. Siri confirms the name from their payee list and the RBC app automatically debits the account and sends the payment, which is protected by Touch ID or face recognition.

It’s also worth considering the palm print. Palm-based identification relies on vein patterns, which are hidden beneath the skin. That makes them invisible and therefore a little safer than a fingerprint scan. In 2020, Amazon announced a payment system based on palm ID to be used at two of its stores in Seattle. The Amazon One scanner lets people pay by hovering their hand in mid-air .   

#4. Banking as a service…can any company be a bank?

Warren Buffett is possibly the world's most famous investor. He knows what he is doing. In June, his Berkshire Hathaway fund invested $500 million into Brazil's Nubank .

It did so because Nubank is now the world’s largest challenger bank. It has 34 million customers across Brazil, Colombia, and Mexico, and a valuation of $30 billion.

Nubank is one of dozens of digital-first banks that are now challenging the incumbents. They have mimicked disruptors in other industries (music, media etc.) by re-thinking the conventional user experience and targeting a demographic that are comfortable with new digital behaviours.

Most of these companies have replaced a branch network with an app. They use algorithms to pull in all sorts of contextual information that’s useful for their customers. Thus, they send push notifications whenever a customer makes a payment and provide rich data about a customer’s spending and habits in easy-to-understand graphics. 

They can do this because the underlying technological structure of banking is changing. In many regions, regulars have requested that banks open up access to bank accounts via bank APIs. This has radically changed the competitive environment. 

It's even led to the idea of Banking as a Service .

This describes a model in which banks can integrate their services into the products of non-bank businesses. It means any company can offer services such as bank accounts, debit cards, loans and payment services, without needing a banking licence of its own.

They just get permission from customers and use APIs and webhooks. 

In the UK, neobank Starling has rolled out a 'white label banking' service . It means that a fintech with a good idea can have its own bank account and payments capability without a banking licence.  

#5. Machine learning. Efficiency that adds $1 trillion of value to banks every year?

AI and banking were made for each other. Artificially intelligent machines might struggle to stack boxes , but give them millions of documents to scan and they will humiliate any human competition.

This ability to analyse huge data sets to discern meaningful patterns is transforming banking. AI and machine learning can detect fraud, offer a more personalised customer service, improve the effectiveness of marketing, combat churn and much more.

The impact will be huge. Indeed, McKinsey estimates that AI technologies could potentially deliver banks up to $1 trillion of additional value each year.  

There are so many examples already out there. But here are two that stand out. In the US, JPMorgan Chase launched ‘contract intelligence’, which it also calls COIN. The tech specialises in reviewing the bank's commercial credit agreements . 

It says a manual review of the 12,000 agreements it issues every year takes 360,000 hours (or 173 years). COIN does it in seconds. 

The second example is HSBC's Anti-Money Laundering (AML) system. HSBC teamed with Quantexa to develop a customer surveillance system that identifies suspicious patterns and potential criminal networks in both bank and external data. It screens 5.8 million trade transactions a year against more than 50 different scenarios that indicate signs of money laundering.   

#6. Investing in the planet. Banking goes green

Not all innovation involves technology. Sometimes enterprises have to re-think their processes to align with customer concerns. Such is the case with green banking.

Green banking is a new trend that sees banks shift their strategies and activities to focus on sustainable technologies and environmentally friendly lending. 

Investment is one area of focus. It is already having an impact. The American Green Bank Consortium says green banks drove $1.69 billion total investment in clean energy and energy-efficient projects in 2020 alone.

But on a more ‘micro’ scale, many banks are now re-thinking their products, services and processes to make them more sustainable. 

Take single-use plastics. Banks use a lot of plastic material, so it makes sense to investigate how to recycle it. Suppliers such as Thales are on the case . The Thales Gemalto Recycled PVC card cuts down first-use PVC by 85%. 

Recycling is also on the agenda. In September 2019, Thales partnered with a payment card issuer to announce the introduction of the first-ever bank card made with 70% reclaimed plastic collected from beaches, islands and coastal communities. Each new card is made from approximately one plastic bottle.

And finally, Thales has even launched a card that doesn’t use plastic at all. The Thales Gemalto Bio-Sourced Cards is made from Poly Lactic Acid (PLA), which is produced from non-edible corn and is entirely biodegradable.  

#7. Blockchain: the next big revolution in digital banking?

In a sense, it’s possible to see most banking services as the process of moving assets from one account to another. Viewed this way, banking is all about databases – and finding the safest and quickest way of transferring information between them.  

For a growing number of specialists, blockchain offers a much better way of managing asset transfers than the current system. Blockchains are distributed ledgers, so they are not owned by a single entity. They cannot be manipulated and are accessible to all.

Proponents say this makes transactions cheaper and faster. And since asset provenance and credit history are recorded as immutable components, transactions become less risky.

One area where the blockchain is making impact earliest is cross border payments. According to the blockchain firm Ripple the current method of international payments, SWIFT, relies on ‘disco-era technology’ , which debuted in 1973.

Unsurprisingly, Ripple thinks its crypto-based alternative solves the 'problem' of international payments. So, what is the problem?

Well, even in an era of near-instant domestic payments, a cross-border transfer can take up to 10 days and cost up to 10 percent of the value of the payment. 

The reason for this is 'correspondent banking' in which banks hold accounts in overseas banks. They debit or credit these accounts when payments are made. But not all banks do correspondent banking, so they have to use partners. The complexity is compounded by the variety of bank processes, local rules and the fact that most processing is done manually. 

Blockchain-based systems replace this with transfers using cryptocurrency. A bank converts money into crypto and sends it to the target country, which converts it into local currency and makes the payment. These trades are instantaneous.

Now, the central banks of many nations are looking carefully at the potential of blockchain. And some very well established corporates are now harnessing blockchain too. They include Visa's B2B Connect network, JPMorgan Chase's Liink and IBM Blockchain World Wire .

It seems certain that technological innovation will transform banking as it has other industries. A world of change is coming. What your banking service looks like – and who provides it – will never be the same.  

Related articles:

  Biometrics in payment : the case of the biometric bank card (white paper)

7 benefits of biometric payment systems

A history of payment cards (infographic)

4 innovative ways to pay

Home — Essay Samples — Economics — Banking — Analysis of Technology and Innovation in Banking/finance Sector

Analysis of Technology and Innovation in Banking/finance Sector

• Categories: Banking Innovation Research

About this sample

Words: 1110 |

Published: Mar 19, 2020

Words: 1110 | Pages: 2 | 6 min read

Cite this Essay

Let us write you an essay from scratch

• 450+ experts on 30 subjects ready to help
• Custom essay delivered in as few as 3 hours

Get high-quality help

Dr Jacklynne

Verified writer

• Expert in: Economics Science Education

+ 120 experts online

By clicking “Check Writers’ Offers”, you agree to our terms of service and privacy policy . We’ll occasionally send you promo and account related email

No need to pay just yet!

Related Essays

2 pages / 1025 words

3 pages / 1372 words

3 pages / 1585 words

3 pages / 1371 words

Remember! This is just a sample.

You can get your custom paper by one of our expert writers.

121 writers online

Still can’t find what you need?

Browse our vast selection of original essay samples, each expertly formatted and styled

Related Essays on Banking

Throughout history, wars have been fought for a variety of reasons. From territorial disputes to ideological conflicts, the motivations for war are complex, multifaceted, and often contentious. However, there is a growing body [...]

According to scholars, a financial crisis is an expansive variety of situations in that some if not all of the available financial assets abruptly drop a large part of their original value(Martin and Milas, pp.443-459). Notably, [...]

Lucy Edwards, a former Bank of New York vice president, and her husband Peter Berlin was accused to the biggest cases of money laundering. The couple was admitted to the United states District in Manhattan after about 18 months [...]

Agrawal, A., & Singh, R. K. (2017). Management information system: Conceptual foundations, structure and development. IGI Global.Banomyong, R., & Supatn, N. (2016). Supply chain management in the digital age: Challenges, [...]

Financial innovation can be interpreted as common developments happening gradually in the financial services industry. This includes contemporary markets, technologies, instruments, or institutions. Fintech refers to a distinct [...]

Interbank funds transfer systems are arrangements through which funds transfers are made between banks for their own account or on behalf of their customers. Arrangements for interbank settlement are far more uniform. Private [...]

Related Topics

By clicking “Send”, you agree to our Terms of service and Privacy statement . We will occasionally send you account related emails.

Where do you want us to send this sample?

By clicking “Continue”, you agree to our terms of service and privacy policy.

Be careful. This essay is not unique

This essay was donated by a student and is likely to have been used and submitted before

Download this Sample

Free samples may contain mistakes and not unique parts

Sorry, we could not paraphrase this essay. Our professional writers can rewrite it and get you a unique paper.

Please check your inbox.

We can write you a custom essay that will follow your exact instructions and meet the deadlines. Let's fix your grades together!

Get Your Personalized Essay in 3 Hours or Less!

We use cookies to personalyze your web-site experience. By continuing we’ll assume you board with our cookie policy .

• Instructions Followed To The Letter
• Deadlines Met At Every Stage
• Unique And Plagiarism Free

• Help & FAQ

Essays on banking and financial innovation

• Center Ph. D. Students
• Research Group: Economics

Research output : Thesis › Doctoral Thesis

Access to Document

• Thesis Di Gong Final published version, 722 KB

Fingerprint

• Securitization Business & Economics 100%
• Financial Innovation Business & Economics 98%
• Banking Business & Economics 64%
• Macroprudential Regulation Business & Economics 44%
• Risk Taking Business & Economics 37%
• Systemic Risk Business & Economics 30%
• Forbearance Business & Economics 20%
• Bank Regulation Business & Economics 18%

T1 - Essays on banking and financial innovation

AU - Gong, Di

N2 - This dissertation consists of three chapters. Chapters 2 and 3 examine the ex-ante motivation and the ex-post impact of securitization. Departing from the traditional literature of bank-specific drivers for securitization, I investigate the tax incentive for securitization in a cross country setting. In addition, unlike the prior micro studies of the impacts of securitization, for instance, the adverse selection in the securitization market and so forth, I study the macro impact ofsecuritization on real economy. Another strand of my research focuses on banking regulation, especially macroprudential regulation. I am particularly interested in the fact that banks may ex-ante take risk in anticipation of regulatory forbearance in a systemic banking crisis and its implication for macroprudential regulation. Consequently, chapter 4 analyzes systemic risk-taking at banks in the presence of “too-manyto-fail” bailout guarantee. In sum, shedding light on securitization and systemic risk-taking in the banking sector, this dissertation contributes to the policy debate on bank regulation.

AB - This dissertation consists of three chapters. Chapters 2 and 3 examine the ex-ante motivation and the ex-post impact of securitization. Departing from the traditional literature of bank-specific drivers for securitization, I investigate the tax incentive for securitization in a cross country setting. In addition, unlike the prior micro studies of the impacts of securitization, for instance, the adverse selection in the securitization market and so forth, I study the macro impact ofsecuritization on real economy. Another strand of my research focuses on banking regulation, especially macroprudential regulation. I am particularly interested in the fact that banks may ex-ante take risk in anticipation of regulatory forbearance in a systemic banking crisis and its implication for macroprudential regulation. Consequently, chapter 4 analyzes systemic risk-taking at banks in the presence of “too-manyto-fail” bailout guarantee. In sum, shedding light on securitization and systemic risk-taking in the banking sector, this dissertation contributes to the policy debate on bank regulation.

M3 - Doctoral Thesis

SN - 978 90 5668 458 7

T3 - CentER Dissertation Series

PB - CentER, Center for Economic Research

CY - Tilburg

The Innovation Imperative for Banks Starts With Personalized Digital Experiences

The traditional banking model and business roadmap for financial institutions needs future-proofing.

Across today’s financial services landscape, digital increasingly rules the roost — making prioritizing innovation important for long-term success.

Staying relevant through innovative services and holistic convenience is frequently the best way to stay in business. Last week,  Bank of America  launched a “massive update” to its  mobile banking app , combining banking, investing and retiring into one unified app.

The new, unified digital platform from Bank of America consolidates into one mobile app what had been five different apps: Bank of America, Merrill Edge, My Merrill, Bank of America Private Bank and Benefits OnLine. It also brings several digital tools together in one place, including Bank of America’s  Life Plan  and  Net Worth Estimator Tool  offering.

The move comes at a critical juncture, as the pandemic forever changed consumer expectations from their banks, The rise of digital and  embedded banking  services and nonbank platforms has resulted in the commoditization of many banking products, creating a need for traditional banks to focus on fully owning the customer relationship with their clients and customers through personalized and relevant services.

After all, the very definition of what a bank is — what it does and what it can do — is changing. The downstream result is a contemporary financial services landscape that is competitive. Effective innovations can give firms a winning edge in the market.

Read also:   Ongoing Banking Turmoil Revives Business Model Debate

Navigating the Transformation of Banking and Financial Services

Against the backdrop of today’s landscape, banks are expected to operate with cost efficiency and robustness without making any mistakes. That alone is a difficult task. But banks are also expected to focus on innovation and growth as well as produce personalized services for every customer — and these two expectations can often be at odds.

In today’s digital age, where a seamless and convenient experience across various touchpoints has become table stakes, particularly within financial services, prioritizing innovation is critical to sustainable success.

Innovation can open doors to previously untapped markets. For example, younger generations are often more tech-savvy and inclined toward digital banking. By offering innovative solutions that cater to their preferences, banks can attract potential customers who may not have considered traditional banking options before.

“Historically, it was just  banks  competing with banks,”  William Artingstall , global co-head of cross-border payments and receivables at  Citi , told PYMNTS in October. “But increasingly, FinTechs and other disruptive entrants are leveraging solutions … innovations and competitive offerings … which can be costly and complex for banks to quickly stand up.”

PYMNTS Intelligence’s “ Growing Credit Union Membership via Lending and Omnichannel Banking Innovation ” revealed that 81% of credit union members look for innovation when shopping for a financial services provider, while 74% of non-credit union members said the same. Eight percent of credit union members said they transitioned to credit unions because their financial institutions failed to meet their innovation expectations.

See also:   The Cost of Legacy Payments in Light of Innovation’s ROI

Accessibility Redefined: Customers Flock to Convenience

It is becoming increasingly important for banks to use data analytics and artificial intelligence to offer personalized experiences to customers.

As  NCR Voyix  President  Doug Brown  told PYMNTS this month, helping banking clients deliver an  omnichannel  experience rests on real-time data. Personalization is paramount so data can help the banks be aware of what the customer wants and when, while setting an action plan to address the banking client’s concerns even before they set foot in the lobby.

Through insights gleaned from transaction histories and user behavior, banks can tailor product recommendations, financial advice and promotional offers to individual preferences and needs. This level of customization enhances customer engagement and satisfaction, fostering long-term relationships between banks and their clientele.

As technology continues to evolve, so too will the landscape of online banking. The rise of mobile banking applications, digital wallets and contactless payment methods exemplifies the ongoing innovation in financial services. Additionally, emerging technologies such as AI hold the potential to further revolutionize banking by facilitating secure and transparent transactions.

Recommended

Trending news, the big story.

Featured News

Partner with pymnts.

We’re always on the lookout for opportunities to partner with innovators and disruptors.

• 7982774960/ 9693730114
• infobankwhizz@gmail.com
• Descriptive
• Buy Courses
• Essay Topics
• Model Essays
• Login/Signup

Descriptive English मतलब Bank Whizz

Essay Writing on Role of technology in Banking Sector – RBI Grade B 2023

Write an argrumentative essay on “Role of technology in the banking sector and its impact on customers” for RBI Grade B 2023

The banking sector has undergone a significant transformation in recent years, thanks to the role of technology. Technology has revolutionized the banking industry by making it more efficient, secure, and accessible. This essay argues that the role of technology in the banking sector has had a positive impact on customers.

One of the most significant impacts of technology in the banking sector is the convenience it offers to customers. Customers can now access their bank accounts and conduct transactions from the comfort of their homes or offices, thanks to online and mobile banking. This has eliminated the need for customers to visit their bank branches, which can be time-consuming and inconvenient. Customers can now transfer funds, pay bills, and access account information with ease.

Technology has also made banking transactions more secure. With the implementation of measures such as two-factor authentication and biometric identification, customers can be sure that their transactions are safe and secure. This has reduced the incidence of fraud and made it more difficult for cybercriminals to steal customer information.

The role of technology in the banking sector has also increased the speed and efficiency of transactions. Automated teller machines (ATMs) and online banking have reduced the time it takes for customers to access their funds and conduct transactions. Customers can now withdraw cash, deposit cheques, and transfer funds quickly and easily.

Another significant impact of technology on customers is the access it has provided to banking services. Technology has made it possible for banks to offer their services to customers who previously did not have access to banking services. This has had a positive impact on financial inclusion, especially in developing countries.

In conclusion, the role of technology in the banking sector has had a positive impact on customers. It has made banking more convenient, secure, and accessible. Technology has also increased the speed and efficiency of transactions and contributed to financial inclusion. However, it is important for banks to ensure that they maintain the privacy and security of their customers’ information to ensure that technology continues to have a positive impact on customers.

2018 Theses Doctoral

Essays on Innovation

Datta, Bikramaditya

This dissertation analyzes problems related to barriers to innovation. In the first chapter, “Delegation and Learning”, I study an agency problem which is common in many contexts involving financing of innovation. Consider the example of an entrepreneur, who has an idea but not the money to implement it, and an investor, who has the money but not the idea. In such a case, how should a financial contract between the investor and the entrepreneur look like? How much money should the investor provide the entrepreneur? How should the surplus be divided between them in case the idea turns out to be profitable? There are certain common elements in situations such as these. First, there is an element of learning. This is because initially it is unknown if the idea is profitable or not and hence the idea has to be tried out in the market and both the investor and entrepreneur learn about the profitability of the idea from observing market outcomes. Second, there is an element of delegation in the above situation. This is because decision rights regarding where and when should the idea be tried out is typically in the hands of the entrepreneur and he knows his idea better than the investor. Finally, the preferences of the investor and the entrepreneur might not be aligned. For instance, the investor may receive private benefits, monetary or reputational, from launching products even when these are not profitable. In such a case, how should a contract that incentivizes the entrepreneur to act in the investor’s interest look like? To study these issues, I develop a model in which a principal contracts with an agent whose ability is uncertain. Ability is learnt from the agent’s performance in projects that the principal finances over time. Success however also depends on the quality of the project at hand, and quality is privately observed by the agent who is biased towards implementation. I characterize the optimal sequence of rewards in a relationship that tolerates an endogenously determined finite number of failures and incentivizes the agent to implement only good projects by specifying rewards for success as a function of past failures. The fact that success becomes less likely over time suggests that rewards for success should increase with past failures. However, this also means that the agent can earn a rent from belief manipulation by deviating and implementing a bad project which is sure to fail. I show that this belief-manipulation rent decreases with past failures and implies that optimal rewards are front-loaded. The optimal contract resembles the arrangements used in venture capital, where entrepreneurs must give up equity share in exchange for further funding following failure. In the second chapter, “Informal Risk Sharing and Index Insurance: Theory with Experimental Evidence”, written with Francis Annan, we study when does informal risk sharing act as barrier or support to the take-up of an innovative index-based weather insurance? We evaluate this substitutability or complementarity interaction by considering the case of an individual who endogenously chooses to join a group and make decisions about index insurance. The presence of an individual in a risk sharing arrangement reduces his risk aversion, termed “Effective Risk Aversion” — a sufficient statistic for index decision making. Our analysis establishes that such reduction in risk aversion can lead to either reduced or increased take up of index insurance. These results provide alternative explanations for two empirical puzzles: unexpectedly low take-up for index insurance and demand being particularly low for the most risk averse. Experimental evidence based on data from a panel of field trials in India, lends support for several testable hypotheses that emerge from our baseline analysis. In the third chapter, “Investment Timing, Moral Hazard and Overconfidence”, I study how overconfidence and financial frictions impact entrepreneurs by shaping their incentives to learn. I consider a real option model in which an entrepreneur learns about the quality of project he has, prior to implementation. Success depends on the quality of the project as well as the unknown ability of the entrepreneur. The possibility of the entrepreneur diverting investor funds to his private uses, creates a moral hazard problem which leads to delayed investment and over-experimentation. An entrepreneur who is overconfident regarding his ability, under-experiments and over invests compared to an entrepreneur who has accurate beliefs regarding his ability. Such overconfidence on behalf of the entrepreneur creates inefficiencies when projects are self financed, but reduces inefficiencies due to moral hazard in case of funding by investors.

• Technological innovations
• Entrepreneurship
• Entrepreneurship--Economic aspects

More About This Work

• DOI Copy DOI to clipboard