essay on banking sector

Essay on Banking Sector

Students are often asked to write an essay on Banking Sector in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Banking Sector

What is the banking sector.

The banking sector is a part of our economy that provides financial services. It includes banks, credit unions, and other institutions. These places help us save money, get loans, and make payments. They play a big role in our daily lives and the economy.

Types of Banks

There are different types of banks. Commercial banks help businesses and individuals. Investment banks help companies raise money. Central banks control a country’s money supply. Each type of bank has a unique role and helps in different ways.

Banking Services

Banks offer many services. They keep our money safe in savings and checking accounts. They give loans for homes, cars, or businesses. They also provide credit cards, which let us borrow money to buy things and pay it back later.

Importance of the Banking Sector

The banking sector is very important. It helps us save and invest money. It makes it easy for us to buy things and pay bills. It also helps businesses grow by giving them loans. Without banks, managing money would be much harder.

Challenges in the Banking Sector

250 words essay on banking sector.

The banking sector is an important part of our society. It includes banks, which are places where people can keep their money safe. Banks also give loans to people and businesses, so they can buy things like houses or start new companies. This helps our economy grow.

There are different types of banks. Some are big and have branches all over the country, like State Bank of India. Others are small and only have a few branches, like local co-operative banks. There are also foreign banks, which come from other countries but have branches in our country.

Services Offered by Banks

Banks offer many services. They let us save our money in savings accounts. They also let us borrow money through loans. Banks even help us send money to other people through services like online banking and money transfers. These services make our lives easier and help us manage our money better.

Role of Banks in Economy

Banks play a big role in our economy. They help businesses grow by giving them loans. They also keep our money safe and help us save for the future. Without banks, it would be hard for our economy to grow and for people to manage their money.

In conclusion, the banking sector is a key part of our society and economy. It provides important services like savings accounts and loans, and helps businesses grow. It makes our lives easier and our economy stronger.

500 Words Essay on Banking Sector

There are different types of banks that provide different kinds of services.

1. Commercial Banks: These are the most common type of banks that we see around us. They provide services like accepting deposits, giving loans, and basic investment products.

3. Retail Banks: These banks deal directly with people rather than businesses. They offer services like savings and checking accounts, mortgages, personal loans, debit/credit cards, and certificates of deposit.

4. Central Banks: These are not like other banks. Every country has one central bank that manages the country’s money supply and keeps the economy stable.

Roles of the Banking Sector

Safekeeping of Money: Banks provide a safe place for people and businesses to keep their money. This money is also insured, so even if the bank goes out of business, people don’t lose their money.

Loans for Growth: Banks give loans to people and businesses. This money helps businesses to grow and create jobs. People use loans to buy homes, cars, or pay for education.

Managing the Economy: Banks, especially the central bank, help to manage the country’s economy. They control how much money is in the economy. Too much money can cause prices to go up very fast (inflation). Too little money can make the economy slow down.

Banking Sector and Technology

Technology is changing how banks work. Now, we can do most of our banking from a computer or a phone. This is called online banking or digital banking. We can check our account balance, transfer money, pay bills, and even apply for loans on the internet. This makes banking easier and faster. But it also needs good security to keep our money safe.

The banking sector is very important for our daily life and the economy. It helps us save money, gives loans for growth, and keeps the economy stable. With the help of technology, banking is becoming easier and faster. But we also need to remember about the safety of our money.

That’s it! I hope the essay helped you.

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• Essay On Bank

Essay on Bank

500+ words essay on bank.

Banks are an integral part of the modern economy. They play a major role in the economic growth and development of a country. The idea of banking evolved with the idea of money. In India, public sector banks (PSBs) have been working to provide banking services in urban and rural areas since 1970. These public sector banks account for nearly 70% of banking activity in India. With the help of this essay on banks, students will get to know the functions performed by banks and their importance for individuals and the country. To help students in improving their essay-writing skills, we have also compiled a list of CBSE Essays on different topics. By practising these essays, they can boost their writing skills and also score good marks on the English exam.

Meaning of Bank

Banks are mainly linked to depositing and lending money. In Indian society, moneylenders used to give money to people in ancient times. They charged a high rate of interest to people as there were no banks or banking systems available at that time. But, with the change in time, the banking system was introduced in India. Now, we have public sector banks and private banks.

A bank is a financial institution that deals with deposits, withdrawals and other related banking services. Bank receives money from those who want to save in the form of deposits, and it lends money to those who need it. A bank is a financial institution that works as an intermediary to accept deposits and channels those deposits into various lending activities. It does so through loans or capital markets. A bank establishes the connection between the customers who have capital surpluses and those with capital deficits. In India, all banks operate under the guidelines of the Reserve Bank of India, which is known as the banker’s bank.

Functions of Bank

Banking is the lifeline of the modern economy. It has played a very important role in the economic development of all the nations of the world. We can not think of modern commerce without banking. Banking is a business which seeks profits like any other business. The banking business mainly constitutes borrowing and lending as their basic functions. Now, banks are providing many other services to people, such as net banking, online shopping, mobile banking, granting loans and advances, short-term credit, pension payments, acting as a dealer in foreign currency etc. A common person can safely deposit their money in the banks.

How Important are Banks for Development?

Banks are the most important financial pillars. They play a vital role in the economic development of a country. The financing requirements of industries, trades, agriculture and other business are met with the help of banks. Therefore, if the banking system of a country becomes strong, then the development of the country will also be at a faster rate. In today’s economy, banks are not only dealing with money, but they are also contributing to the development of the nation. They play a crucial role in the disbursement of credit and the mobilisation of deposits to various sectors of the economy. Banks also represent the economic health of the country. The strength of a nation’s economy depends on the strength of the financial system, which depends on the banking system.

In India, banks play a crucial role in the social and economic growth of the country after independence. The banking sector in India accounts for more than half the assets of the financial sector. The Indian banks have shown much growth after the implementation of financial sector reforms.

Banks are the backbone of any country’s economy. They are responsible for running the economy and controlling the price of the markets. They perform various important functions. However, there are default NPAs, cases of corruption and security threat-related issues, but these can be resolved by implementing strict laws and rules by the government.

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Industries Overview

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• The banking industry is in a much healthier place now than it was after the financial crisis of 2008.
• As a result of the increasing complexity of the banking ecosystem, financial giants and disruptive startups are navigating challenges and opportunities daily.
• Do you work in the Banking industry? Get business insights on the latest tech innovations, market trends, and your competitors with data-driven research .

Banking Industry Overview

The banking industry is in a much healthier place now than it was after the financial crisis of 2008. Total global assets climbed to $154,211 in 2022, up 3.79 percent YoY from 148,583 in 2021, according to The Banker’s Top 1000 World Banks Ranking for 2022. 

With so much money to manage, major banks such as JPMorgan Chase, Bank of America, Wells Fargo, and more are releasing new features to attract new customers and retain their existing ones. On top of that, startups and neobanks with disruptive banking technologies are breaking into the scene, and traditional financial institutions are either competing with them or merging with them to improve their customer experience.

So let’s dive into the banking industry, the challenges it faces, and the road ahead.

Banking Industry Trends

The most prevalent trend in the financial services industry today is the shift to digital, specifically mobile and online banking (more on each of those in a bit). In today’s era of unprecedented convenience and speed, consumers don’t want to have to trek to a physical bank branch to handle their transactions. This is especially true of Millennials and the older members of Gen Z , who have started to become the dominant players in the workforce (and the biggest earners). 

This digital transformation caused increased competition from tech startups, as well as the consolidation of smaller banks and startups, contributing to a record-breaking 2021. However, global fintech funding has cooled this year as funding conditions have become more challenging across most of the world. In Q3 2022, overall fintech funding dropped 38% quarter-over-quarter (QoQ) to hit $12.9 Billion—comparable with Q4 2020 funding, according to CB Insights. 

Looking ahead, startups and scale up firms alike must demonstrate profitability and growth potential to earn back the trust of investors. 

Mobile Banking

To be frank, mobile banking is all but a requirement for consumers at this point. In Insider Intelligence’s Mobile Banking Competitive Edge Study in 2020,  over 45% of respondents said they identify mobile as a top-three factor that determines their choice of FI, up from 38.0% in 2019—making it the second most important factor behind fees.

When broken down by generation, 91% of millennials use it, 95% of Gen Xers, and 60% of Baby Boomers. Critically for the banks themselves, 64% of mobile banking users said that they would research a bank’s mobile capabilities before opening an account, and 61% say they would change banks if their bank offered a poor mobile banking experience.

Critically for the banks themselves, 74% of mobile banking users said that they would research a bank’s mobile capabilities before opening an account, and 49% say they would change banks for better mobile banking capabilities, per Insider Intelligence’s The US Mobile Banking Competitive Edge Report 2020. But we’ve now reached the point where simply having a mobile app isn’t enough for banks to attract and keep customers. Additional tools and features – such as the ability to put temporary holds on cards, view recurring charges, or scanning a fingerprint to log into an account –  are becoming increasingly necessary.

Online Banking

Online banking is extremely convenient, and is understandably one of the two main ways that consumers interact with their banks (along with mobile banking). But there is still a significant contingent of banking customers who want physical branches.

Despite an overwhelming reliance on digital banking channels and services such as chatbots and mobile banking apps, and the resulting decline in branch visits, consumers have maintained a preference for depositing checks in-branch, according to a recent Fiserv study. More than half (53%) of respondents said their top reason for visiting a branch in the past month was to deposit a check, compared with 41% who went to withdraw cash, and 36% who went to deposit cash.

Still, there’s no denying the rising prevalence of online banking, which has led to other innovations such as open banking. This system, implemented in the U.K., involves sharing customers’ financial information electronically and securely, but only under conditions that customers approve.

Open banking forces lenders to offer a digital “fire hose” of data that any third party can use to get standardized access — provided the startup is registered with the UK Financial Conduct Authority (FCA) and the customer agrees to share their data.

Investment Banking

Investment banking is a type of financial service in which a person or company advises individuals, businesses, or even governments on how and where to invest their money. For decades, this has been a human-to-human process that led to a mutually beneficial relationship.

But now, with the rise of robo-advisors, artificial intelligence (AI) and robotic process automation are starting to infiltrate the money management space. Predictive analytics can help investors make wiser and more profitable decisions in real-time—while saving on costs. AI can, in some cases, also help identify M&A targets. Lastly, AI can help validate an investment banker’s hypothesis and lead to more informed future decisions.

Like what you’re reading? Click here to learn more about Insider Intelligence’s leading Financial Services research.

Banking as a Service (BaaS)

Because of tight regulations (particularly in the U.S.), not everyone can just open a bank. This is where  banking as a service  ( BaaS ) comes in to fill the gap.

BaaS platforms  enable fintechs and other third parties to connect with banks’ systems via APIs to build banking offerings on top of the providers’ regulated infrastructure. So, launching BaaS platforms helps banks benefit from fintechs entering the finance space, as it turns them into customers rather than just competitors.

While BaaS technically falls under the umbrella of open banking, it shouldn’t be confused with the aforementioned Open Banking system in the U.K.  Open banking encompasses all actions in which a bank opens its APIs to third parties and gives those players access to data or functionality. The UK’s Open Banking focuses on providing third parties with data from incumbent banks, while BaaS looks at how these players can get access to banks’ services.

Banking Regulations

Banking is involved in almost every aspect of American life, from consumers to businesses to stocks. Because of this, the federal government has instituted numerous regulations on the banking industry, though the severity of those restrictions has waxed and waned in the last decade.

After the financial crisis of 2008, the Obama administration enacted the Dodd–Frank Wall Street Reform and Consumer Protection Act in 2010. Dodd-Frank overhauled the U.S. financial regulation system in the aftermath of the crash. The most sweeping and impactful changes from the act included:

• The elimination of the Office of Thrift Supervision
• The creation of the Consumer Financial Protection Bureau (CFPB) to protect consumers against abuses and unfair practices tied financial services and products such as credit cards and mortgages
• The reassignment of responsibilities for agencies such as the Federal Deposit Insurance Corporation
• The creation of the Financial Stability Oversight Council and the Office of Financial Research to analyze potential threats to U.S. financial stability
• The expansion of the Federal Reserve’s powers to regulate particular institutions

In 2018, President Donald Trump signed into law the Economic Growth, Regulatory Relief and Consumer Protection Act (EGRRCPA), which rolled back some of the Dodd-Frank changes. Specifically, EGRRCPA raised the threshold under which the federal government deems banks too important to the financial system to fail from $50 billion to $250 billion.

It also eliminated the Volcker Rule (a federal regulation that largely forbade banks from conducting particular investment activities with their own accounts and restricted their dealings with hedge funds and private equity funds) for small banks with less than $10 billion in assets.

Despite the rollbacks, it’s still difficult in the U.S. to get a banking license, which has hampered some banking startups. On the other hand, this has increased mergers and acquisitions activity. As a result, regulation will be a key focal point for the banking industry in the coming years.

Banking Industry Analysis

With so many different facets of the banking industry undergoing change, it’s crucial for those connected to the banking industry to be informed and stay ahead. That’s why Insider Intelligence covers it all with our Banking vertical to keep you up to date on the latest banking trends and shakeups.

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Banking In India Essay | Essay on Banking In India for Students and Children in English

February 14, 2024 by Prasanna

Banking In India Essay:  A bank is a financial body that accepts deposits and channels them into lending through loans or capital markets. Banks thus, connect customers with lack of funds 1 and those with extra capital.

“Money plays the largest part in determining the course of history.” -Karl Marx

You can read more  Essay Writing  about articles, events, people, sports, technology many more.

Long and Short Essays on Banking In India for Kids and Students in English

Given below are two essays in English for students and children about the topic of ‘Banking In India’ in both long and short form. The first essay is a long essay on Banking In India of 400-500 words. This long essay about Banking In India is suitable for students of class 7, 8, 9 and 10, and also for competitive exam aspirants. The second essay is a short essay on Banking In India of 150-200 words. These are suitable for students and children in class 6 and below.

Long Essay on Banking In India 500 Words in English

Below we have given a long essay on Banking In India of 500 words is helpful for classes 7, 8, 9 and 10 and Competitive Exam Aspirants. This long essay on the topic is suitable for students of class 7 to class 10, and also for competitive exam aspirants.

The word ‘bank’ was borrowed from European languages, literally meaning ‘bench’ or ‘counter’. Banking system evolved in the 14 th century in Italy. By the 18 th century, merchants of London had started storing their gold with goldsmiths who charged a fee and issued receipts. A banker is a person who discharges his duties in the form of operating customer accounts and, paying and collecting cheques.

Banks borrow money by accepting the l money deposited in current accounts, by accepting term deposits and issuing securities on banknotes and bonds. They also create pew capital by giving loans. Banking activities can be for retail, in which the customers and small businesses are involved directly with the bank; for businesses for large corporate houses and for investments.

There are various types of banks such as commercial banks (which are engaged solely in banking activities), investment banks (for capital market activities), cooperative banks (non-profit banks), postal savings banks (associated with postal systems) and private banks (managing the assets of high net worth people).

In India, banking has its origin in the Vedic period. It is believed that the transition from money lending to banking must have occurred even before Manu, the great Hindu Jurist, who laid down rules relating to rates of interest. During the Mughal period, the indigenous bankers played a very important role in lending money and. financing foreign trade and commerce.

The first bank in India, though elemental, was established in 1786. From 1786 till today, the journey of Indian Banking System can be segregated into three distinct phases. They are Early Phase from 1786 to 1969 of commercial banks; Nationalisation of Commercial Banks upto 1991, prior to Indian banking sector reforms and New Phase of Indian Banking System with the advent of Indian Financial & Banking Sector Reforms after 1991.

The General Bank of India was set-up in the year 1786. The East India Company established the Bank of Bengal (1809), Bank of Bombay (1840) and Bank of Madras (1843) as independent units and called it Presidency Banks. These three banks were amalgamated in 1920 and Imperial Bank of India was established which started as private shareholders banks, for mostly European shareholders. For the first time exclusively by Indians, Punjab National Bank Ltd was set-up in 1894 with Headquarters at Lahore. During the first phase, the growth was very slow and banks also experienced periodic failures between 1913 and 1948. There were approximately 1100 banks, mostly small.

To streamline the functioning and activities of commercial banks, the Government of India came up with the Banking Companies Act, 1949 which was later changed to Banking Regulation Act, 1949 as per amendment Act of 1965 (Act No. 23 of 1965). Reserve Bank of India was vested with extensive powers for the supervision of banking in India as the Central Banking Authority. RBI is the Central Bank of the country since 1935. It regulates and controls credit, issues licenses and functions as the banker of all banks and the government.

During those days, public had lesser confidence in banks. As an aftermath, the deposit mobilisation was slow. Instead of banks, the savings bank facility provided by the Postal department was considered comparatively safer. Moreover, funds were largely given to traders. Government took major steps in the Indian Banking Sector Reforms after Independence. In 1955, it nationalised Imperial Bank of India with extensive banking facilities on a large scale, especially in rural and semi-urban areas. It formed the State Bank of India, to act as the principal agent of RBI and to handle banking transactions of the Union and State Governments all over the country.

It was on the efforts of the then Prime Minister of India, Mrs Indira Gandhi that 14 major commercial banks in the country were nationalised in 1960’s. The second phase of nationalisation, with Indian Banking Sector Reforms, was carried out in 1980 with the nationalisation of seven more banks. This step brought 80% of the banking segment in India under government ownership. After the nationalisation of banks, the branches of the public sector banks in India rose to approximately 800% in deposits and advances took a huge jump by 11000%.

Banking in the support of government ownership, gave the public implicit faith and immense confidence about the sustainability of these institutions. The third phase has introduced many more products and facilities in the banking sector in its reforms measure. In 1991, under the chairmanship of M Narasimham, a committee was set-up to suggest measures for banking sector reforms. Today, the country is flooded with foreign banks and their ATM stations. Efforts are being put in to give a satisfactory service to customers. Phone banking and net banking have been introduced. The entire system has become more convenient and swift. Time is given more importance than money. The financial system of India has shown a great deal of resilience. It is sheltered from any crisis triggered by external macroeconomics shock, unlike other East Asian Countries that had to suffer. This is largely due to flexible exchange rate regime, high foreign exchange reserves and reforms in the capital markets and banks. Presently, in India, the banking sector is segregated as public or private sector banks, cooperative banks and regional rural banks. Bouquet of services are available at the customer’s demand in today’s banking system. Different types of accounts and loans, have been facilitated with the advent of plastic money and money transfer across the globe. The last decade experienced a complete change in the financial and banking sector. The capital and financial markets, banking and non-banking institutions and financial instruments were redressed towards development.

Short Essay on Banking In India 350 Words in English

Below we have given a short essay on Banking In India is for Classes 1, 2, 3, 4, 5, and 6. This short essay on the topic is suitable for students of class 6 and below.

Industrial Development Bank of India (IDBI) is the tenth largest bank in the world in terms of development. With the advancement of technology, banking sector has become easier, faster, accurate and also timesaving. ATMs, Mobile Banking, SMS Banking and Net Banking are only the tips of an iceberg.

The enhanced role of the banking sector in the Indian economy, the increasing levels of deregulation along with the ascending levels of competition have facilitated globalisation of the Indian banking system and placed numerous demands on banks. Operating in this demanding environment has exposed them to various challenges. The last decade has witnessed major changes in the financial sector new banks, new financial institutions, new instruments, new windows, and new opportunities and along with all this, new challenges.

While deregulation has opened up new vistas for banks to augment revenues, it has entailed greater competition and consequently greater risks. Demand for new products, particularly derivatives, requires banks to diversify their product mix and also affect rapid changes in their processes and operations in order to remain competitive in the globalised environment.

Developing countries like India have a huge population. Banking must reach out to people even in the remote fragmented locations. Banks are also suffering from diminishing employee satisfaction. Losing out on potential and valuable customer base would be one of the consequences. Top level executives and human resource departments of various banks need to spend time and effort towards retention of their key employees. Banks have also come under the scanner recently, due to various scams and malpractices. The arrest of the Chairman of Syndicate Bank is the latest case in sight.

The banking sector also introduced the All-Women’s Bank, known as Bhartiya Mahila Bank, in New Delhi. It was inaugurated by the then PM Manmohan Singh on 19 th November, 2013, to commemorate the 94 th birthday of Indira Gandhi. India will be the third nation after Pakistan and Tanzaniya, to have a bank dedicated to women. The bank will offer concession on loan rates to women. It would also motivate people interested in entrepreneurship to locally train women in vocational skills. The other goal is to promote ownership of assets among women customers, as assets serve as a back-up in cases of domestic violence.

However, the present governor of RBI, Raghuram Rajan has assured that this case shouldn’t be extrapolated to the entire system. Banks shouldn’t be just money-lending institutions, they should be ‘banks with a conscience’.

Banking In India Essay Word Meanings for Simple Understanding

• channel – a course into which something may be directed
• Retail – the sale of goods to ultimate consumers, usually in small quantities
• Indigenous – originating in and characteristic of a particular region or country
• Segregated – to separate or set apart from others or from the main body or group
• Distinct – different in nature or quality, dissimilar
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• Published: 18 June 2021

Financial technology and the future of banking

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

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

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

Introduction

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The theory of the banking firm: a revision

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

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

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

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

Therefor it can be said that,

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

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

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

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

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

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

Theoretically, it can be shown that,

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

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

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

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

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

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

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

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

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

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

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

The evolution of the business model in a digital world

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

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

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

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

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

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

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

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

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

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

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

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

Open banking

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

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

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

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

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

Discussion: strategic options

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

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

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

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

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

The client retention strategy (incumbents)

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

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

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

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

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

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

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

The client acquisition strategy (challengers)

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

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

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

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

The banking as a service strategy (new entrants)

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

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

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

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

The social media payment strategy (disintermediators and disruptors)

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

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

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

Further research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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2024 Theses Doctoral

Essays on Digital Banking

Koont, Naz K.

This dissertation studies how the digitalization of commercial banking affects bank competition, financial stability, and monetary policy transmission. In the first chapter, The Digital Banking Revolution: Reduced Form Evidence, I use hand-collected data and a novel identification strategy to show that after adopting digital platforms, banks branchlessly operate in more markets, and mid-size banks, those with relatively high quality digital platforms but without extensive branch networks, grow faster. Further, bank balance sheet composition tilts to uninsured deposits on the funding side, and to high income borrowers on the loan side. In the second chapter, The Digital Banking Revolution: Aggregate Effects on Competition and Stability, in order to disentangle the underlying mechanisms and quantify aggregate effects, I build a structural model of the U.S. banking system and compare the observed digital equilibrium to a counterfactual without digital platforms. The model allows for endogenous adoption of digital platforms, branch networks, market entry, and accounts for digitalization among non-banks. Digitalization decreases local and national market concentration, and average markups fall in deposit and loan markets, holding fixed the size of the banking sector. Consumers capture most of the surplus created by digitalization, however it accrues mostly to wealthier segments of the economy. As for stability, it increases the average market share of lightly-regulated mid-sized banks, increases the uninsured deposits ratio of the banking sector while re-sorting uninsured deposits towards larger digital banks, and doubles credit risks associated with lending in market segments that are less-well served by digital technologies. In sum, digital banking increases competition and poses risks to financial stability. In the third chapter, Destabilizing Digital "Bank Walks", which is co-authored with Tano Santos and Luigi Zingales, we study the impact of digital banking on the value of the deposit franchise and the transmission of monetary policy through bank balance sheets. We find that when the Fed funds rate increases, deposits flow out faster and the cost of deposits increases more in banks with a digital platform. The results are similar for insured and non-insured deposits. We find that correcting for digital betas and deposit outflows results in a deposit franchise value that is significantly lower for digital-broker banks relative to a traditional bank without digital platform. We apply this analysis to Silicon Valley Bank (SVB) and find that the reduced value of the deposit franchise explains why SVB was insolvent in early March 2023, even before the bank run occurred.

Geographic Areas

• United States
• Banks and banking--Computer network resources
• Banks and banking, Central--Econometric models
• Economic stabilization
• Monetary policy
• Bank failures--Econometric models

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Home — Essay Samples — Economics — Banking — Banking Sector and Ethical Issues Nowadays

Banking Sector and Ethical Issues Nowadays

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Published: Oct 11, 2018

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Banking Sector

Ethical issues.

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China’s Banking Sector Analysis Essay

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China’s banking sector is an important feature of the country’s financial system that has contributed to its position as the second largest economy in the world. Currently, China’s banking sector is under pressure due to rapid credit growth that has occurred in the last few decades (Wei and Inman par. 2). Banks have made it easy for state enterprises, businesses, borrowers, and local governments to acquire loans.

This has led to accumulation of bad loans that are threatening to destabilise the country’s economy. Financial experts have projected a rise in bad loans and a consequent decline in earnings growth that will financial risks in the banking industry (Wei and Inman par. 3).

The high number of borrowers who are unable to pay their loans has affected the country’s financial system adversely. The banks are currently implementing different strategies and mitigation measures that are aimed at strengthening their balance sheets in preparation for slow economic growth.

Raising capital is not a viable option for the banks because many investors have sold their stocks in these banks due to unfavourable financial outcomes and slow economic growth. The uncertainty in the financial markets has worsened the situation. The main cause of the problem is the use of poor financial strategies by banks in efforts to circumvent lending limits imposed by the government. Many banks have increased their off-balance-sheet loans in order to grow their earnings and capital (Wei and Inman par. 4).

However, this has affected their financial stability because it has increased the number of high-risk borrowers and debt. These unofficial financial transactions are collectively known as shadow banking. In June 2013, the Central Bank of China allowed interbank borrowing in order to mitigate the negative effects of shadow banking (Wei and Inman par. 7).

This move initiated a rise in borrowing costs among banks that caused frenzy in the country’s financial system because it threatened the stability of equity and bond markets. Many banks are pursuing different avenues to raise their capital bases.

For example, in 2013, Agricultural Bank of China, Industrial & Commercial Bank of China Ltd, Bank of China Ltd, and China Construction Bank Corporation sought an approval from the government in order to issue securities worth $44.1 billion to investors as a way of raising capital (Wei and Inman par. 9).

Financial analysts have criticised that move because of the state of China’s financial system. Even though China has the second largest economy in the world, it is founded on a shaky financial system. The growth of the country’s biggest banks in terms of market capitalisation has been fueled by shadow banking.

The greatest challenges facing China’s banking system are high-risk loans issued to local governments and off-balance-sheet lending. Local governments have high debts that could morph into bad loans because many of them have reported decreased revenues in the past few years (Wei and Inman par. 10). In order to lessen their financial risks, many banks are extending the maturity periods of loans held by local governments.

They are implementing mitigation strategies that have the potential to lower financial risks. China’s banking sector is not as healthy as the government depicts it to be. Slow economic growth and innumerable bad loans are threatening the stability of the banking industry. It is important for the government to assist banks financially.

Another challenge is rapid growth of banks that is not in line with their earnings. Many banks’ capital bases are not sufficient to sustain their rapid growth rates. According to the China Banking Association, many banks will experience significant decline in revenue due to bad loans and numerous nonperforming assets (Wei and Inman par. 12). Banks need to either raise more capital or give up their expansion programs.

Works Cited

Wei, Lingling, and Inman Daniel. Chinese Banks Feel Strains after Long Credit Binge: Rapid Loan Growth Has Led to Serious Debt Problems at Local Governments . 2013. Web.

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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.

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Financial Sector: Definition, Examples, Importance to Economy

Ariel Courage is an experienced editor, researcher, and former fact-checker. She has performed editing and fact-checking work for several leading finance publications, including The Motley Fool and Passport to Wall Street.

Ivestopedia / Michela Buttignol

What Is the Financial Sector?

The financial sector is a section of the economy made up of firms and institutions that provide financial services to commercial and retail customers. This sector comprises a broad range of industries including banks, investment companies, insurance companies, and real estate firms.

Key Takeaways

• The financial sector is a section of the economy made up of firms and institutions that provide financial services to commercial and retail customers.
• A strong financial sector is a sign of a healthy economy.
• The financial sector generates a good portion of its revenue from loans and mortgages and thrives in a low-interest-rate environment.
• The sector is comprised of many different industries including banks, investment companies, insurance companies, and real estate firms.

Understanding the Financial Sector

A large portion of this sector generates revenue from mortgages and loans, which gain value as interest rates drop. The health of the economy depends, in large part, on the strength of its financial sector. The stronger it is, the healthier the economy. A weak financial sector typically means the economy is weakening.

Many people equate the financial sector with Wall Street and the exchanges that operate on it. But there's much more to it than that. The financial sector is one of the most important parts of many developed economies. It is made up of brokers , financial institutions, and money markets—all of which provide the services needed to help keep Main Street functioning every day.

In order for an economy to remain stable, it needs to have a healthy financial sector. This sector advances loans for businesses so they can expand, grants mortgages to homeowners, and issues insurance policies to protect people, companies, and their assets. It also helps build up savings for retirement and employs millions of people.

The financial sector generates a good portion of its revenue from loans and mortgages. These gain value in an environment where interest rates drop. When rates are low, the economic conditions open up the doors for more capital projects and investment. When this happens, the financial sector benefits, meaning more economic growth.

Financial Sector Makeup

As mentioned above, the financial sector is made up of many different industries ranging from banks, investment houses, insurance companies, real estate brokers, consumer finance companies, mortgage lenders, and real estate investment trusts (REITs).

The financial sector is one of the largest portions of the S&P 500 . The largest companies within the financial sector are some of the most recognizable banking institutions in the world, including the following:

• JPMorgan Chase (JPM)
• Wells Fargo (WFC)
• Bank of America (BAC)
• Citigroup (C)

While these large companies dominate the sector, there are other, smaller companies that participate in the sector as well. Insurers are also a major industry within the financial sector, being made up of such companies as American International Group (AIG) and Chubb (CB).

Investing in the Financial Sector

Economists often tie the overall health of the economy with the health of the financial sector. If financial companies are weak, this is a detriment to the average consumer. Financial companies provide loans for businesses, mortgages to homeowners, and insurance to consumers. If these activities are restricted, it stunts growth in both small businesses and real estate.

Financial stocks are very popular investments to own within a portfolio. Most companies within the sector issue dividends and are judged on the overall strength of their financial health. During the financial crisis of 2007-2008 , the financial sector was one of the hardest hit, with companies like Lehman Brothers filing for bankruptcy. After an influx of government regulation and restructuring, the financial sector is considerably stronger.

Financial ETFs, such as the Financial Select Sector SPDR Fund (XLF)—the largest financial ETF—can provide investors with broad exposure to the sector.

As of the close of trading on Sept. 29, 2020, the financial sector had a combined market capitalization of $5.59 trillion. The sector has underperformed the S&P 500 index in the trailing 12 months (TTM), where the S&P 500 is up 14.3% while the S&P 500 Financials Sector has fallen 13.7%.

Special Considerations

Some of the positive factors that affect the financial sector include:

• Moderately rising interest rates. As rates rise, financial services companies can earn more on the money they have and on credit they issue to their customers. 
• Reducing regulation. Whenever the government decides to cut back on red tape, members of the financial sector will benefit. This means it could lessen the burden while increasing profits.
• Lower consumer debt levels. as consumers decrease their debt loads, they lessen the risk of defaults . This lighter load also means they may have a tolerance for more debt, further increasing profitability.

Conversely, investors should consider some of the negative factors that affect this sector as well:

• Rapid interest rate increases. If rates rise too quickly, demand for credit such as mortgages could drop, which could negatively affect certain parts of the financial sector. 
• Yield curve flattening. If the spread between long- and short-term interest rates drop too far, the financial sector could start to struggle.
• More legislation. Government regulation can have a big impact on the financial sector. While it may help protect consumers, more red tape can bog down a business that operates in financial services.

Fidelity. " Financials ." Accessed Sept. 30, 2020.

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Indian Economy

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Banking Sector: Opportunities and Challenges

• 01 Jan 2024
• 15 min read
• GS Paper - 3
• Banking Sector & NBFCs
• Growth & Development
• Monetary Policy

This editorial is based on “Banks are fine, but there are risks” which was published in The Hindu Business Line on 029/12/2023. The article points out that State finances, an overheated stock market, and inter-connected lending are concerns, even as banks are undeniably in good health. 

For Prelims: Banking Sector , Reserve Bank of India , Non-Performing assets , Prompt Corrective Actions . 

For Mains: Challenges in the Banking Sector 

In recent times, there has been a noticeable resurgence in India's banking system following almost a decade of grappling with escalating bad loan challenges. Thanks to the concerted efforts of policymakers and the proactive measures taken by banks, the sector is currently on a more secure footing.  

Nevertheless, considering historical patterns, the positive trajectory for Indian banks remains susceptible to the impact of monetary policies and external uncertainties, such as geopolitical risks. 

How have Indian Banks Evolved over the Years? 

• In the period before Independence (up to 1947), the Swadeshi Movement led to the establishment of numerous small, local banks, most of which faced failure primarily due to internal frauds, interconnected lending, and the amalgamation of trading and banking activities.  
• Indian banks enabled the consolidation of resources, mobilised through retail deposits, towards a limited number of business families or groups, consequently overlooking the flow of credit to the agriculture sector. 
• The government successfully severed the link between industry and banks by nationalising 20 major private banks in two phases (1969 and 1980) and introducing priority sector lending in 1972.  
• These measures led to a transition from 'class banking' to 'mass banking' and had a favourable effect on the widespread expansion of branch networks in rural India, substantial mobilisation of public deposits, and increased credit flow to agriculture and allied sectors. 
• During this period, significant reforms were implemented, including the issuance of new licences to private and foreign banks to introduce competition, improve productivity, and enhance efficiency.  
• These changes involved leveraging technology, introducing prudential norms, offering operational flexibility with functional autonomy, prioritising the implementation of best corporate governance practices, and fortifying the capital base in accordance with Basel norms .  
• From 2014 onward, the banking sector has embraced the JAM (Jan-Dhan, Aadhaar, and Mobile) trinity, and granted licences to Payments Banks and Small Finance Banks (SFBs) to attain last-mile connectivity in the pursuit of financial inclusion. 

What is the Current Status of the Indian Banking Regime? 

• Not too long ago, Indian lenders faced a dire situation with bad loans, leading to a spike in stressed assets. Government-owned banks were particularly affected, with gross NPAs reaching 14.6%.  
• To counter these challenges, the government and RBI implemented a 4R strategy— Recognize NPAs transparently, Resolution and recovery, Recapitalization of PSBs, and Reforms in the financial ecosystem.  
• After grappling with seething government and bad loan issues for nearly a decade, the Indian banking system has experienced a remarkable turnaround in 2023. 
• In FY23, the gross NPA ratio for banks in India plummeted to 4.41%, the lowest since March 2015. Cumulatively, PSBs crossed the Rs 1 lakh crore-mark in profit.  
• As per RBI's Financial Stability Report , the capital-to-risk-weighted assets ratio (CRAR) stands at a robust 16.8%, indicating a strong financial position for scheduled commercial banks.  
• This underscores the sound financial health of Indian banks, reflecting positively on their ability to absorb potential risks and maintain stability in the financial system. 
• Reforms introduced over the past eight years focused on credit discipline, responsible lending, improved governance , and the adoption of technology. Mergers of PSBs were instrumental in reducing NPAs. 
• Banks exhibit strong liquidity levels , measured by funds available for lending. Despite the RBI’s recent monetary stance of "withdrawal of accommodation," banks maintain a Liquidity Coverage Ratio at least 20% higher than the minimum requirement.  
• Additionally, major banks, including SBI, PNB, and Union Bank, demonstrate a capacity to lend "higher for longer," with Credit-Deposit ratios below 72%. 

What Obstacles Lie Ahead for the Indian Banking Sector? 

• Bank lending for upcoming infrastructure and capital investments, particularly those linked to State government entities, poses a risk of defaults due to stretched State finances.  
• Banks are advised to set internal exposure limits based on fiscal/financial assessments of individual States. 
• The seemingly runaway stock market , creating an illusion of wealth, presents a risk to retail exposures. Increased demat accounts and high PE ratios across sectors are indicators of this risk. 
• Integrated supervision and rigorous stress tests on retail portfolios are recommended to address this emerging risk. 
• The possibility of default becoming a contagion due to interconnected lending and lax governance norms poses a significant challenge.  
• Focused risk monitoring is necessary, emphasising that regulation cannot substitute for good governance. 
• The re-globalization of the world and geopolitical shifts may challenge  Small and medium-sized enterprises(SMEs), especially in the face of Free Trade Agreements (FTAs) and regional ambitions.  
• Banks need to carefully assess and prepare for potential risks to SMEs, considering potential disruptions to cash flows. 
• The character of liabilities is changing with digitisation and evolving consumption trends, impacting retail deposits. Banks with higher credit-deposit ratios may face challenges in liquidity coverage.  
• A structural shift in Indian savings requires caution and prudence from bankers, necessitating a careful watch amidst favourable conditions. 

How Can the Indian Banking Sector be Fortified Moving Ahead? 

• The second tier could include numerous mid-sized banks, including niche institutions, with a widespread presence across the economy.  
• Consistent with these suggestions, the government has already consolidated certain PSBs and taken measures to establish entities like a Development Finance Institution (DFI) and a Bad Bank. 
• Essentially, these specialised banks would facilitate financial access in specific areas such as retail, agriculture, and MSMEs.  
• Additionally, establishing proposed DFIs or niche banks as specialised entities would provide them with access to low-cost public deposits and enable improved asset-liability management. 
• Enhanced risk management can be achieved, and neo-banks have the opportunity to harness this technology for advancing digital financial inclusion and supporting the increased growth of an aspiring and emerging India. 
• In the realm of Indian banking, the implementation of technologies such as Blockchain holds the potential to facilitate prudential supervision, making oversight and control over banks more streamlined. 
• Until now, the occurrence of public sector banks failing has been infrequent, primarily due to the concealed sovereign guarantee, instilling greater trust in the public. Nevertheless, the ongoing privatisation of PSBs challenges this assurance.  
• Consequently, the upcoming wave of banking reforms should emphasise the necessity for increased individual deposit insurance and efficient orderly resolution mechanisms. This aims to reduce moral hazard and systemic risks, minimising the financial burden on the public treasury. 
• It could be beneficial for Distinctive Banks to consider listing on a reputable stock exchange and embracing the ESG (Environmental, Social Responsibility, and Governance) framework. This approach aims to enhance value for stakeholders over the long term. 
• To address vulnerabilities, the government should refine regulatory measures, enabling banks to develop diversified loan portfolios , instituting regulators for specific sectors, and granting increased authority to handle deliberate defaults effectively. 
• In order to establish a responsive banking system in a dynamic real economy, there is a requirement to promote the growth of the corporate bond market, thereby transitioning away from a bank-centric economic model. 
• Develop and implement internal risk models tailored to individual States, similar to the Bank Exposure Risk Index , to assess potential risks associated with lending to State government entities and infrastructure projects. 
• Recognize the changing nature of liabilities influenced by digitisation and evolving consumption trends. Develop strategies to adapt to shifts in retail deposits, especially in Tier 1 and 2 centres. 

Conclusion  

While celebrating the current success of the banking sector, it is crucial to adopt a proactive and vigilant stance to navigate the complexities and uncertainties of the times we live in. 

UPSC Civil Services Examination, Previous Year Question (PYQ) 

Prelims .

Q1. With reference to the Banks Board Bureau (BBB), which of the following statements are correct? (2022) 

• The Governor of RBI is the Chairman of BBB. 
• BBB recommends for the selection of heads for Public Sector Banks. 
• BBB helps the Public Sector Banks in developing strategies and capital raising plans.  

Select the correct answer using the code given below: 

(a) 1 and 2 only    (b) 2 and 3 only  (c) 1 and 3 only    (d) 1, 2 and 3 

Ans: B 

Q2. Consider the following events: (2018) 

• The first democratically elected communist party government formed in a State in India. 
• India’s then largest bank, ‘Imperial Bank of India’, was renamed ‘State Bank of India’. 
• Air India was nationalised and became the national carrier. 
• Goa became a part of independent India. 

Which of the following is the correct chronological sequence of the above events? 

(a) 4 – 1 – 2 – 3    (b) 3 – 2 – 1 – 4  (c) 4 – 2 – 1 – 3    (d) 3 – 1 – 2 – 4 

Mains 

Q. Pradhan Mantri Jan Dhan Yojana (PMJDY) is necessary for bringing unbanked to the institutional finance fold. Do you agree with this for the financial inclusion of the poorer section of the Indian society? Give arguments to justify your opinion. (2016)

Utilization of artificial intelligence in the banking sector: a systematic literature review

• Original Article
• Published: 11 August 2022
• Volume 28 , pages 835–852, ( 2023 )

Cite this article

• Omar H. Fares   ORCID: orcid.org/0000-0003-0950-0661 1 ,
• Irfan Butt 1 &
• Seung Hwan Mark Lee 1  

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This study provides a holistic and systematic review of the literature on the utilization of artificial intelligence (AI) in the banking sector since 2005. In this study, the authors examined 44 articles through a systematic literature review approach and conducted a thematic and content analysis on them. This review identifies research themes demonstrating the utilization of AI in banking, develops and classifies sub-themes of past research, and uses thematic findings coupled with prior research to propose an AI banking service framework that bridges the gap between academic research and industry knowledge. The findings demonstrate how the literature on AI and banking extends to three key areas of research: Strategy, Process, and Customer. These findings may benefit marketers and decision-makers in the banking sector to formulate strategic decisions regarding the utilization and optimization of value from AI technologies in the banking sector. This study also provides opportunities for future research.

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Introduction

Digital innovations in the modern banking landscape are no longer discretionary for financial institutions; instead, they are becoming necessary for financial institutions to cope with an increasingly competitive market and changing customer expectations (De Oliveira Santini, 2018 ; Eren, 2021 ; Hua et al., 2019 ; Rajaobelina and Ricard, 2021 ; Valsamidis et al., 2020 ; Yang, 2009 ). In the era of modern banking, many new digital technologies have been driven by artificial intelligence (AI) as the key engine (Dobrescu and Dobrescu, 2018 ), leading to innovative disruptions of banking channels (e.g., automated teller machines, online banking, mobile banking), services (e.g., imaging of checks, voice recognition, chatbots), and solutions (e.g., AI investment advisors and AI credit selectors).

The application of AI in banking is across the board, with uses in the front office (voice assistants and biometrics), middle office (anti-fraud risk monitoring and complex legal and compliance workflows), and back office (credit underwriting with smart contracts infrastructure). Banks are expected to save $447 billion by 2023, by employing AI applications. Almost 80% of the banks in the USA are cognizant of the potential benefits offered by AI (Digalaki, 2022 ). Indeed, the emergence of AI has generated a wealth of opportunities and challenges (Malali and Gopalakrishnan, 2020 ). In the banking context, the use of AI has led to more seamless sales and has guided the development of effective customer relationship management systems (Tarafdar et al., 2019 ). While the focus in the past was on the automation of credit scoring, analyses, and the grants process (Mehrotra, 2019 ), capabilities evolved to support internal systems and processes as well (Caron, 2019 ).

The term AI was first used in 1956 by John McCarthy (McCarthy et al., 1956 ); it refers to systems that act and think like humans in a rational way (Kok et al., 2009 ). In the aftermath of the dot com bubble in 2000, the field of AI shifted toward Web 2.0. era in 2005, and the growth of data and availability of information encouraged more research in AI and its potential (Larson, 2021 ). More recently, technological advancements have opened the doors for AI to facilitate enterprise cognitive computing, which involves embedding algorithms into applications to support organizational processes (Tarafdar et al., 2019 ). This includes improving the speed of information analysis, obtaining more accurate and reliable data outputs, and allowing employees to perform high-level tasks. In recent years, AI-based technologies have been shown to be effective and practical. However, many corporate executives still lack knowledge regarding the strategic utilization of AI in their organizations. For instance, Ransbotham et al. ( 2017 ) found that 85% of business executives viewed AI as a key tool for providing businesses with a sustainable competitive advantage; however, only 39% had a strategic plan for the use of AI, due to the lack of knowledge regarding implementation of AI for their organizations.

Here, we systematically analyze the past and current state of AI and banking literature to understand how it has been utilized within the banking sector historically, propose a service framework, and provide clear future research opportunities. In the past, a limited number of systematic literature reviews have studied AI within the management discipline (e.g., Bavaresco et al., 2020 ; Borges et al., 2020 ; Loureiro et al., 2020 ; Verma et al., 2021 ). However, the current literature lacks either research scope and depth, and/or industry focus. In response, we seek to differentiate our study from prior reviews by providing a specific focus on the banking sector and a more comprehensive analysis involving multiple modes of analysis.

In light of this, we aim to address the following research questions:

What are the themes and sub-themes that emerge from prior literature regarding the utilization of AI in the banking industry?

How does AI impact the customer's journey process in the banking sector, from customer acquisition to service delivery?

What are the current research deficits and future directions of research in this field?

Methodology

Selection of articles.

Adhering to the best practices for conducting a Systematic Literature Review (SLR) (see Khan et al., 2003 ; Tranfield et al, 2003 ; Xiao and Watson, 2019 ), we began by selecting the appropriate database and identifying keywords, based on an in-depth review of the literature. Research papers were extracted from Web of Science (WoS) and Scopus. These databases were selected to complement one another and provide access to scholarly articles (Mongeon and Paul-Hus, 2016 ); this was also the first step in ensuring the inclusion of high-quality articles (Harzing and Alakangas, 2016 ). The following query was used to search the title, abstract, and keywords: “Artificial intelligence OR machine learning OR deep learning OR neural networks OR Intelligent systems AND Bank AND consumer OR customer OR user.” The keywords were selected, based on prior literature review, with the goal of covering various business functions, especially focusing on the banking sector (Loureiro et al., 2020 ; Verma et al., 2021 ; Borges et al., 2020 ; Bavaresco et al., 2020 ). The initial search criteria yielded 11,684 papers. These papers were then filtered by “English,” “article only” publications, and using the subject area filter of “Management, Business Finance, accounting and Business,” which resulted in 626 papers.

In this study, we used the preferred reporting method for systematic reviews and meta-analyses (PRISMA) to ensure that we follow the systematic approach and track the flow of data across different stages of the SLR (Moher et al., 2009 ). After extracting the articles, each of the 626 papers was given a distinctive ID number to help differentiate the papers; the ID number was maintained throughout the analysis process. The data were then organized using the following columns: “ID number,” “database source,” “Author,” “title,” “Abstract,” “keywords,” “Year,” Australian Business Deans Council (ABDC) Journals, “and keyword validation columns.”

The exclusion of papers was done systematically in the following manner: a) All duplicate papers in the database were eliminated (105 duplicates); b) as a second quality check, papers not published in ABDC journals (163 papers) were omitted to ensure a quality standard for inclusion in the review,Query a practice consistent with other recent SLRs (Goyal and Kumar, 2021 ; Nusair et al., 2019 ; Pahlevan-Sharif et al., 2019 ); c) in order to ensure the relevance of articles included, and following our research objectives, we excluded non-consumer-related papers, searching for consumers (consumer, customer, user) in the title, abstract, and keywords; this resulted in the removal of 314 papers; d) for the remaining 48 papers, a relevance check was manually conducted to determine whether the papers were indeed related to AI and banking. Papers that specifically focused on the technical computational process of AI were removed (4 papers). This process resulted in the selection of 44 articles for subsequent analyses.

Thematic analysis

A thematic analysis classifies the topics and subtopics being researched. It is a method for identifying, analyzing, and reporting patterns within data (Boyatzis, 1998 ). We followed Chatha and Butt ( 2015 ) to classify the articles into themes and sub-themes using manual coding. Second, we employed the Leximancer software to supplement the manual classification process. The use of these two approaches provides additional validity and quality to the research findings.

Leximancer is a text-mining software that provides conceptual and relational information by identifying concept occurrences and co-occurrences (Leximancer, 2019 ). After uploading all the 44 papers onto Leximancer, we added “English” to the stoplist, which removed words such as “or/and/like” that are not relevant to developing themes. We manually removed irrelevant filler words, such as “pp.,” “Figure,” and “re.” Finally, our results consisted of two maps: a) a conceptual map wherein central themes and concepts are identified, and b) a relational cloud map where a network of connections and relationships are drawn among concepts.

Thematic map

RQ 1: What are the themes and sub-themes that emerge from prior literature regarding the utilization of AI in the banking industry?

We began with a deductive approach to categorize articles into predetermined themes for the theme identification process. We then employed an inductive approach to identify the sub-themes and provide context for the primary themes (See Fig. 1 ). The procedure for determining the primary themes included, a) reviewing previous related systematic literature reviews (Bavaresco et al., 2020 ; Borges et al., 2020 ; Loureiro et al., 2020 ; Verma et al., 2021 ), b) identifying keywords and developing codes (themes) from selected papers; and c) reviewing titles, abstracts, and full papers, if needed, to identify appropriate allocation within these themes. Three primary themes were curated from the process: Strategy, Processes, and Customers (see Fig.  2 ).

Themes by timeline

In the Strategy theme (21 papers), early research shows the potential uses and adoption of AI from an organizational perspective (e.g., Akkoç, 2012 ; Olson et al., 2012 ; Smeureanu et al., 2013 ). Data mining (an essential part of AI) has been used to predict bankruptcy (Olson et al., 2012 ) and to optimize risk models (Akkoç, 2012 ). The increasing use of AI-driven tools to drive organizational effectiveness creates greater business efficiency opportunities for financial institutions, as compared to traditional modes of strategizing and risk model development. The sub-theme Organizational use of AI (14 papers) covers a range of current activities wherein banks use AI to drive organizational value. These organizational uses include the use of AI to drive business strategies and internal business activities. Medhi and Mondal ( 2016 ) highlighted the use of an AI-driven model to predict outsourcing success. Our findings indicate the effectiveness of AI tools in driving efficient organizational strategies; however, there remain several challenges in implementing AI technologies, including the human resources aspect and the organizational culture to allow for such efficiencies (Fountain et al., 2019 ). More recently, there has been a noticeable focus on discussing some of the challenges associated with AI implementation in banking institutions (e.g., Jakšič and Marinč, 2019 ; Mohapatra, 2020 ). The sub-theme Challenges with AI (three papers) covers a range of challenges that organizations face, including the integration of AI in their organizations. Mohapatra ( 2020 ) characterizes some of the key challenges related to human–machine interactions to allow for the sustainable implementation of AI in banking. While much of the current research has focused on technology, our findings indicate that one of the main areas of opportunity in the future is related to adoption and integration. The sub-theme AI and adoption in financial institutions (six papers) covered a range of topics regarding motivation, and barriers to the adoption of AI technology from an organizational standpoint. Fountain et al. ( 2019 ) conceptually highlighted some barriers to organizational adoption, including workers’ fear, company culture, and budget constraints. Overall, in the Strategy theme, organizational uses of AI seemed to be the most prominent, which highlights the consistent focus on technology development compared with technology implementation. However, the literature remains limited in terms of discussions related to the organizational challenges associated with AI implementation.

In the Processes theme (34 papers), after the dot com bubble and with the emergence of Web 2.0, research on AI in the banking sector started to emerge. This could have been triggered by the suggested use of AI to predict stock market movements and stock selection (Kim and Lee, 2004 ; Tseng, 2003 ). At this stage, the literature on AI in the banking sector was related to its use in credit and loan analysis (Baesens et al., 2005 ; Ince and Aktan, 2009 ; Kao et al., 2012 ; Khandani et al., 2010 ). In the early stages of AI implementation, it is essential to develop fast and reliable AI infrastructure (Larson, 2021 ). Baesens et al. ( 2005 ) utilized a neural network approach to better predict loan defaults and early repayments. Ince and Aktan ( 2009 ) used a data mining technique to analyze credit scores and found that the AI-driven data mining approach was more effective than traditional methods. Similarly, Khandani et al. ( 2010 ) found machine-learning-driven models to be effective in analyzing consumer credit risk. The sub-theme, AI and credit (15 papers), covers the use of AI technology, such as machine learning and data mining, to improve credit scoring, analysis, and granting processes. For instance, Alborzi and Khanbabaei ( 2016 ) examined the use of data mining neural network techniques to develop a customer credit scoring model. Post-2013, there has been a noticeable increase in investigating how AI improves processes that go beyond credit analysis. The sub-theme AI and services (20 papers) covers the uses of AI for process improvement and enhancement. These process-related uses of technology include institutional uses of technology to improve internal service processes. For example, Soltani et al. ( 2019 ) examined the use of machine learning to optimize appointment scheduling time, and reduce service time. Overall, regarding the process theme, our findings highlight the usefulness of AI in improving banking processes; however, there remains a gap in practical research regarding the applied integration of technology in the banking system. In addition, while there is an abundance of research on credit risk, the exploration of other financial products remains limited.

In the Customer theme (26 papers), we uncovered the increasing use of AI as a methodological tool to better understand customer adoption of digital banking services. The sub-theme AI and Customer adoption (11 papers) covers the use of AI as a methodological tool to investigate customers’ adoption of digital banking technologies, including both barriers and motivational factors. For example, Arif et al. ( 2020 ) used a neural network approach to investigate barriers to internet-banking adoption by customers. Belanche et al. ( 2019 ) investigate factors related to AI-driven technology adoption in the banking sector. Payne et al. ( 2018 ) examine the drivers of the usage of AI-enabled mobile banking services. In addition, bank marketers have found an opportunity to use AI to better segment, target, and position their banking products and services. The sub-theme, AI and marketing (nine papers), covers the use of AI for different marketing activities, including customer segmentation, development of marketing models, and delivery of more effective marketing campaigns. For example, Smeureanu et al. ( 2013 ) proposed a machine learning technique to segment banking customers. Schwartz et al. ( 2017 ) utilized an AI-based method to examine the resource allocation in targeted advertisements. In recent years, there has been a noticeable trend in investigating how AI shapes customer experience (Soltani et al., 2019 ; Trivedi, 2019 ). The sub-theme of AI and customer experience (Papers 11) covers the use of AI to enhance banking experience and services for customers. For example, Trivedi ( 2019 ) investigated the use of chatbots in banking and their impact on customer experience.

Table 1 highlights the number of papers included in the themes and sub-themes. Overall, the papers related to Processes (77%) were the most frequently occurring, followed by Customer (59%) and Strategy-based (48%) papers. From 2013 onward, there was an increase in the inter-relation between all three areas of Strategy, Processes, and Customers. Since 2016, there has been a surge in research linking the themes of Processes and Customers. More recently, since 2017, papers combining Customers with Strategy have become more frequent.

Leximancer analysis

A Leximancer analysis was conducted on all the papers included in the study. This resulted in two major classifications and 56 distinct concepts. Here, a “concept” refers to a combination of closely related words. When referring to “concept co-occurrence,” we refer to the total number of times two concepts appear together. In comparison, the word association percentage refers to the conditional probability that two concepts will appear side-by-side.

Conceptual and relational analyses

Conceptual analysis refers to the analysis of data based on word frequency and word occurrence, whereas relational analysis refers to the analysis that draws connections between concepts and captures the co-occurrences between words (Leximancer, 2019 ). As Fig.  3 shows, the most prominent concept is “customer,” which provides additional credence to our customer theme. The concept “customer” appeared 2,231 times across all papers. For the concept “customer,” some of the key concept associations include satisfaction (324 co-occurrences and 64% word association), service (185 co-occurrences and 43% word association), and marketing (86 co-occurrences and 42% word association). This may imply the importance of utilizing AI in improving customer service and satisfaction, and in marketing to retain and grow the customer base. For instance, Trivedi ( 2019 ) examined the factors affecting chatbot satisfaction and found that information, system, and service quality, all have a significant positive association with it. Ekinci et al. ( 2014 ) proposed a customer lifetime value model, supported by a deep learning approach, to highlight key indicators in the banking sector. Xu et al. ( 2020 ) examined the effects of AI versus human customer service, and found that customers are more likely to use AI for low-complexity tasks, whereas a human agent is preferred for high-complexity tasks. It is worth noting that most of the research related to the customer theme has utilized a quantitative approach, with limited qualitative papers (i.e., four papers) in recent years.

Concept map of content of all papers included in the study

Not surprisingly, the second most prominent concept is “banking,” which is expected as it is the sector that we are examining. The concept “banking” appeared 1,033 times across all the papers. In the “banking” concept, some of the key concept associations include mobile (248 co-occurrences and 88% word association), internet (152 co-occurrences and 82% word association), adoption (220 co-occurrences and 50% word association), and acceptance (71 co-occurrences and 42% word association). This implies the importance of utilizing AI in mobile- and internet-banking research, along with inquiries related to the adoption and acceptance of AI for such uses. Belanche et al. ( 2019 ) proposed a research framework to provide a deeper understanding of the factors driving AI-driven technology adoption in the banking sector. Payne et al. ( 2018 ) examined digital natives' comfort and attitudes toward AI-enabled mobile banking activities and found that the need for services, attitude toward AI, relative advantage, and trust had a significant positive association with the usage of AI-enabled mobile banking services.

Figure  4 highlights the concept associations and draws connections between concepts. The identification and classification of themes and sub-themes using the deductive method in thematic analysis, and the automated approach using Leximancer, provide a reliable and detailed overview of the prior literature.

Cloud map of content of all papers included in the study

Customer credit solution application-service blueprint

RQ 2: How does AI impact the banking customer’s journey?

A service blueprint is a method that conceptualizes the customer journey while providing a framework for the front/back-end and support processes (Shostack, 1982 ). For a service blueprint to be effective, the core focus should be on the customer, and steps should be developed based on data and expertise (Bitner et al., 2008 ). As previously discussed, one of the key research areas, AI and banking, relates to credit applications and granting decisions; these are processes that directly impact customer accessibility and acquisition. Here, we develop and propose a Customer Credit Solution Application-Service Blueprint (CCSA) based on our earlier analyses.

Not only was the proposed design developed but the future research direction was also extracted from the articles included in this study. We also validated the framework through direct consultation with banking industry professionals. The CCSA model allows marketers, researchers, and banking professionals to gain a deeper understanding of the customer journey, understand the role of AI, provide an overview of future research directions, and highlight the potential for future growth in this field. As seen in Fig.  5 , we divided the service blueprint into four distinct segments: customer journey, front-stage, back-stage, and support processes. The customer journey is the first step in building a customer-centric blueprint, wherein we highlight the steps taken by customers to apply for a credit solution. The front-stage refers to how the customer interacts with a banking touchpoint (e.g., chatbots). Back-stage actions provide support to customer-facing front-stage actions. Support processes aid in internal organizational interactions and back-stage actions. This section lays out the steps for applying for credit solutions online and showcases the integration and use of AI in the process, with examples from the literature.

Customer credit solution application journey

Acquire customer

We begin from the initial step of customer acquisition, and proceed to credit decision, and post-decision (Broby, 2021 ). In the acquisition step, customers are targeted with the goal of landing them on the website and converting them to active customers. The front-stage includes targeted ads , where customers are exposed to ads that are tailored for them. For instance, Schwartz et al. ( 2017 ) utilized a multi-armed bandit approach for a large retail bank to improve customer acquisition, and proposed a method that allows bank marketers to maintain the balance between learning from advertisement data and optimizing advertisement investment. At this stage, the support processes focus on integrating AI as a methodological tool to better understand customers' banking adoption behaviors, in combination with utilizing machine learning to evaluate and update segmentation activities. The building block at this stage, is understanding the factors of online adoption. Sharma et al. ( 2017 ) used the neural network approach to investigate the factors influencing mobile banking adoption. Payne et al. ( 2018 ) examined digital natives' comfort and attitudes toward AI-enabled mobile banking activities. Markinos and Daskalaki ( 2017 ) used machine learning to classify bank customers based on their behavior toward advertisements.

Visit bank’s website & apply for a credit solution

At this stage, banking institutions aim to convert website traffic to credit solution applicants. The integration of robo-advisors will help customers select a credit solution that they can best qualify for, and which meets their banking needs. The availability of a robo-advisor can enhance the service offering, as it can help customers with the appropriate solution after gathering basic personal financial data and validating it instantly with credit reporting agencies. Trivedi ( 2019 ) found that information, system, and service quality are key to ensuring a seamless customer experience with the chatbot, with personalization moderating the constructs. Robo-advisors have task-oriented features (e.g., checking bank accounts) coupled with problem-solving features (e.g., processing credit applications). Following this, the data collected will be consistently examined through the use of machine learning to improve the offering and enhance customer experience. Jagtiani and Lemieux ( 2019 ) used machine learning to optimize data collected through different channels, which helps arrive at appropriate and inclusive credit recommendations. It is important to note that while the proposed process provides immense value to customers and banking institutions, many customers are hesitant to share their information; thus, trust in the banking institution is key to enhancing customer experience.

Receive a decision

After the data have been collected through the online channel, data mining and machine learning will aid in the analysis and provide optimal credit decisions. At this stage, the customer receives a credit decision through the robo-advisor. The traditional approaches for credit decisions usually take up to two weeks, as the application goes to the advisory network, then to the underwriting stage, and finally back to the customer. However, with the integration of AI, the customer can save time and be better informed by receiving an instant credit decision, allowing an increased sense of empowerment and control. The process of arriving at such decisions should provide a balance between managing organizational risk, maximizing profit, and increasing financial inclusion. For instance, Khandani et al. ( 2010 ) utilized machine learning techniques to build a model predicting customers' credit risk. Koutanaei et al. ( 2015 ) proposed a data mining model to provide more confidence in credit scoring systems. From an organizational risk standpoint, Mall ( 2018 ) used a neural network approach to examine the behavior of defaulting customers, so as to minimize credit risk, and increase profitability for credit-providing institutions.

Customer contact call center

At this stage, we outline the relationship between humans and AI. As Xu et al. ( 2020 ) found that customers prefer humans for high-complexity tasks, the integration of human employees for cases that require manual review is vital, as AI can make errors or misevaluate one of the C's of credit (Baiden, 2011 ). While AI provides a wealth of benefits for customers and organizations, we refer to Jakšič and Marinč's ( 2019 ) discussion that relationship banking still plays a key role in providing a competitive advantage for financial institutions. The integration of AI at this stage can be achieved by optimizing banking channels. For instance, banking institutions can optimize appointment scheduling time and reduce service time through the use of machine learning, as proposed by Soltani et al. ( 2019 ).

General discussion

Researchers have recognized the viable use of AI to provide enhanced customer service. As discussed in the CCSA service advice, facilities, such as robo-advisors, can aid in product selection, application for banking solutions, and time-saving in low-complexity tasks. As AI has been shown to be an effective tool for automating banking processes, improving customer satisfaction, and increasing profitability, the field has further evolved to examine issues pertaining to strategic insights. Recent research has been focused on investigating the use of AI to drive business strategies. For instance, researchers have examined the use of AI to simplify internal audit reports and evaluate strategic initiatives (Jindal, 2020 ; Muñoz-Izquierdo et al., 2019 ). The latest research also highlights the challenges associated with AI, whether from the perspective of implementation, culture, or organizational resistance (Fountain et al., 2019 ). Moreover, one of the key challenges uncovered in the CCSA is privacy and security concerns of customers in sharing their information. As AI technologies continue to grow in the banking sector, the privacy-personalization paradox has become a key research area that needs to be examined.

In addition, the COVID-19 pandemic has brought on a plethora of challenges in the implementation of AI in the banking sector. Although banks' interest in AI technologies remains high, the reduction in revenue has resulted in a decrease in short-term investment in AI technologies (Anderson et al., 2021 ). Wu and Olson ( 2020 ) highlight the need for banking institutions to continue investing in AI technologies to reduce future risks and enhance the integration between online and offline channels. From a customer perspective, COVID-19 has led to an uptick in the adoption of AI-driven services such as chatbots, E-KYC (Know your client), and robo-advisors (Agarwal et al., 2022 ).

Future research directions

RQ 3: What are the current research deficits and the future directions of research in this field?

Tables 2 , 3 , and 4 provide a complete list of recommendations for future research. These recommendations were developed by reviewing all the future research directions included in the 44 papers. We followed Watkins' ( 2017 ) rigorous and accelerated data reduction (RADaR) technique, which allows for an effective and systematic way to analyze and synthesize calls for future research (Watkins, 2017 ).

Regarding strategy, as AI continues to grow in the banking industry, financial institutions need to examine how internal stakeholders perceive the value of embracing AI, the role of leadership, and multiple other variables that impact the organizational adoption of AI. Therefore, we recommend that future research investigate the different factors (e.g., leadership role) that impact the organizational adoption of AI technologies. In addition, as more organizations use and accept AI, internal challenges emerge (Jöhnk et al., 2021 ). Thus, we recommend examining the different organizational challenges (e.g., organizational culture) associated with AI adoption.

Regarding processes, AI and credit is one of the areas that has been extensively explored since 2005 (Bhatore et al., 2020 ). We recommend expanding beyond the currently proposed models and challenging the underlying assumptions by exploring new aspects of risks presented with the introduction of AI technologies. In addition, we recommend the use of more practical case studies to validate new and existing models. Additionally, the growth of AI has evoked further exploration of how internal processes can be improved (Akerkar, 2019 ). For instance, we suggest investigating AI-driven models with other financial products/solutions (e.g., investments, deposit accounts, etc.).

Regarding customers, the key theories mentioned in the research papers included in the study are the Technology Acceptance Model (TAM) and diffusion of innovation theories (Anouze and Alamro, 2019 ; Azad, 2016 ; Belanche et al., 2019 ; Payne et al., 2018 ; Sharma et al., 2015 , 2017 ). However, as customers continue to become accustomed to AI, it may be imperative to develop theories that go beyond its acceptance and adoption. Thus, we recommend investigating different variables (e.g., social influence and user trends) and methods (e.g., cross-cultural studies) that impact customers' relationship with AI. The gradual shift toward its customer-centric utilization has prompted the exploration of new dimensions of AI that influence customer experience. Going forward, it is important to understand the impact of AI on customers and how it can be used to improve customer experience.

Limitations and implications

This study had several limitations. During our inclusion/exclusion criteria, it is plausible that some AI/banking papers may have been missed because of the specific keywords used to curate our dataset. In addition, articles may have been missed due to the time when the data were collected, such as Manrai and Gupta ( 2022 ), who examined investors' perceptions of robo-advisors. Second, regarding theme identification, there may be a potential bias toward selecting themes, which may lead to misclassification. In addition, we acknowledge that the papers were extracted only from the WoS and Scopus databases, which may limit our access to certain peer-reviewed outlets.

This research provides insights for practitioners and marketers in the North American banking sector. To assist in the implementation of AI-based decision-making, we encourage banking professionals to consider further refining their use of AI in the credit scoring, analysis, and granting processes to minimize risk, reduce costs, and improve customer experience. However, in doing so, we recommend using AI not only to improve internal processes but also as a tool (e.g., chatbots) to improve customer service for low-complexity tasks, thereby directing employees' efforts to other business-impacting activities. Moreover, we recommend using AI as a marketing segmentation tool to target customers for optimal solutions.

This study systematically reviewed the literature (44 papers) on AI and banking from 2005 to 2020. We believe that our findings may benefit industry professionals and decision-makers in formulating strategic decisions regarding the different uses of AI in the banking sector, and optimizing the value derived from AI technologies. We advance the field by providing a more comprehensive outlook specific to the area of AI and banking, reflecting the history and future opportunities for AI in shaping business strategies, improving logistics processes, and enhancing customer value.

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Cybersecurity in Banking: Importance, Threats, Challenges

Home Blog Security Cybersecurity in Banking: Importance, Threats, Challenges

As we transition to a digital economy, cybersecurity in banking is becoming a serious concern. Utilizing methods and procedures created to safeguard the data is essential for a successful digital revolution. The effectiveness of cybersecurity in banks influences the safety of our Personally Identifiable Information (PII), whether it be an unintentional breach or a well-planned cyberattack.

The stakes are high in the banking and financial industry since substantial financial sums are at risk and the potential for significant economic upheaval if banks and other financial systems are compromised. With an exponential increase in financial cybersecurity, there is high demand for the profession of cybersecurity. Take a look at the best Security certifications .

What is Cybersecurity in Banking?

The arrangement of technologies, protocols, and methods referred to as "cybersecurity" is meant to guard against attacks, damage, malware, viruses, hacking, data theft, and unauthorized access to networks, devices, programs, and data.

Protecting the user's assets is the primary goal of cyber security in banking. As more people become cashless, additional acts or transactions go online. People conduct transactions using digital payment methods like debit and credit cards, which must be protected by cybersecurity.

Current State of Cybersecurity in Banks

The market for IT security in banking has maintained its rapid growth in 2024. Since financial institutions are primary attack targets, investments in protection continue to scale. The market value reached $38.72 billion in 2021 , and projections see a compound growth rate of 22.4% and a value of $195.5 billion by 2029.

Between June 2018 and March 2022, Indian banks reported 248 successful data breaches by hackers and criminals; the government notified Parliament on Aug 2, 2022.

The Indian government has reported 11,60,000 cyber-attacks in 2022. It is estimated to be three times more than in 2019. India has been the target of serious cyberattacks, such as the phishing attempt that nearly resulted in a $171 million fraudulent transaction in 2016 against the Union Bank of India.

Another instance of a cyberattack involving online banking was Union Bank of India, resulting in a substantial loss. One of the officials fell for the phishing email and clicked on a dubious link, which allowed the malware to hack the system. The attackers entered the system using fake RBI IDs.

Banks have been mandated to strengthen their IT risk governance framework, which includes a mandate for their Chief Information Security Officer to play a proactive role in addition to the Board and the Board's IT committee playing a proactive role in ensuring compliance with the necessary standards.

Reasons Why Cybersecurity is Important in Banking

The banking industry has prioritized cybersecurity highly. Building credibility and trust is the cornerstone of banking, so it becomes much more essential. Here are five factors that demonstrate the significance of cybersecurity in banking industry and why you should care:

• Everyone looks to be entirely cashless and using digital payment methods like debit and credit cards. In this case, ensuring that the required cybersecurity safeguards are in place to protect your privacy and data is critical.
• After data breaches, it could be difficult to trust financial institutions. That's a significant issue for banks. Data breaches caused by a shoddy cybersecurity solution may easily lead to their consumer base moving their business elsewhere.
• The majority of the time, when a bank's data is compromised, you lose time and money. Recovery from the same can be unpleasant and time-consuming. It would entail canceling cards, reviewing statements, and keeping a watchful lookout for issues.
• Inappropriate use of your private information might be very harmful. Your data is sensitive and could expose a lot of information that could be exploited against you, even if the cards are revoked and fraud is swiftly dealt with.
• Banks need to be more cautious than most other firms. That is the price for banks to retain the kind of valuable personal data they do. If the bank's information is not safeguarded against risks from cybercrime, it could be compromised.

Top Cybersecurity Threats Faced by Banks

Cybercrimes have increased frequently over the past several years to the point where it is thought that they are one of the most significant hazards to the financial sector. Hackers have improved their technology and expertise, making it difficult for any banking sector to thwart the attack consistently. The following are some dangers to banks' cybersecurity:

1. Phishing Attacks

One of the most frequent problems with cyber security in banking sector is phishing assaults. They can be used to enter a financial institution's network and conduct a more severe attack like APT, which can have a disastrous effect on those organizations ( Advanced Persistent Threat ). In an APT, a user who is not permitted can access the system and use it while going unnoticed for a long time. Significant financial, data and reputational losses may result from this. According to the survey , phishing assaults on financial institutions peaked in the first quarter of 2021.

The term "Trojan" is used to designate several dangerous tactics hackers use to cheat their way into secure data. Until it is installed on a computer, a Banker Trojan looks like trustworthy software. However, it is a malicious computer application created to access private data processed or kept by online banking systems. This kind of computer program has a backdoor that enables access to a computer from the outside.

Around the globe, there were roughly 54,000 installation packages for mobile banking trojans in the first quarter of 2022. There has been an increase of more than 53% compared to last year's quarter. After declining for the first three quarters of 2021, the number of trojan packages targeting mobile banking increased in the fourth quarter.

3. Ransomware

A cyber threat known as ransomware encrypts important data and prevents owners from accessing it until they pay a high cost or ransom. Since 90% of banking institutions have faced ransomware in the past year, it poses a severe threat to them.

In addition to posing a threat to financial cybersecurity, ransomware also affects cryptocurrency. Due to their decentralized structure, cryptocurrencies allow fraudsters to break into trading systems and steal money.

4. Spoofing

Hackers use a clone site in this type of cyberattack. By posing as a financial website, they; 

• Design a layout that resembles the original one in both appearance and functionality.
• Establish a domain with a modest modification in spelling or domain extension.

The user can access this duplicate website via a third-party messaging service, such as text or email. Hackers can access a user's login information when the person is not paying attention. Seamless multi-factor authentication can solve a lot of these issues.

The Reserve Bank of India (RBI) reported bank frauds of 604 billion Indian rupees in 2022. From more than 1.3 trillion rupees in 2021, this was a decline.

Applications of Cybersecurity in Banking

Cybersecurity threats are constantly evolving, and the banking sector must take action to protect itself. Hackers adapt when new defenses threaten more recent attacks by developing tools and strategies to compromise security. The financial cybersecurity system is only as strong as its weakest link. It is critical to have a selection of cybersecurity tools and approaches available to protect your data and systems. Here are a few crucial cybersecurity tools:

1. Network Security Surveillance

Network monitoring is known as continuously scanning a network for signs of dangerous or intrusive behavior. It is frequently utilized with other security solutions like firewalls, antivirus software, and IDS (Intrusion Detection System). The software allows for either manual or automatic network security monitoring.

2. Software Security

Application security safeguards applications that are essential to business operations. It has features like an application allowing listing and code signing and could help you synchronize your security policies with file-sharing permissions and multi-factor authentication. The use of AI in cybersecurity will inevitably improve software security.

3. Risk Management

Financial cybersecurity includes risk management, data integrity, security awareness training, and risk analysis. Essential elements of risk management include risk evaluation and the prevention of harm from those risks. Data security also addresses the security of sensitive information.

4. Protecting Critical Systems

Wide-area network connections help avoid attacks on massive systems. It upholds the rigid safety standards set by the industry for users to follow when taking cybersecurity steps to protect their devices. It continuously monitors all programs and performs security checks on users, servers, and the network.

How to Make Banking Institutions Cyber Secure?

Security ratings are a great approach to indicate that you're concerned about the organization's cybersecurity. Still, you must also demonstrate that you're following industry and regulatory best practices for IT security and making long-term decisions based on that knowledge. A cybersecurity framework may be beneficial. You can go for Ethical Hacking training to enhance your knowledge further.

Top Cybersecurity Framework for Banks

A cybersecurity framework provides a common language and set of standards for security leaders across countries and industries to understand their security postures and those of their vendors. With a framework, it becomes easier to define the processes and procedures your organization must take to assess, monitor, and mitigate cybersecurity risk.

Let us take a look at some common financial cybersecurity frameworks:

1. NIST Cybersecurity Framework

The former president's executive order, Improving Critical Infrastructure Cybersecurity, asked for increased cooperation between the public and private sectors for recognizing, analyzing, and managing cyber risk. In response, the NIST Cybersecurity Framework was created. NIST has emerged as the gold standard for evaluating cybersecurity maturity, detecting security weaknesses, and adhering to cybersecurity legislation even when compliance is optional. To achieve NIST compliance , organizations can follow the guidelines outlined in the NIST Cybersecurity Framework and undergo rigorous assessments to ensure they meet the necessary standards.

2. The Bank of England's CBEST Vulnerability Testing Framework

CBEST vulnerability testing methodology was developed by the UK Financial Authorities in collaboration with CREST (the Council for Registered Ethical Security Testers) and Digital Shadows. It is an intelligence-led testing framework. CBEST's official debut took place on June 10, 2013.

CBEST leverages intelligence from reputable commercial and government sources to find possible attackers for a specific financial institution. Then, it imitates these potential attackers' methods to see how successfully they can breach the institution's Defenses. This enables a company to identify the weak points in its system and create and implement corrective action plans.

3. Cybersecurity and Privacy Framework for Privately Held Information Systems (the CIPHER Framework) 

Computer systems that organizations, both public and private, control and that hold personal data gathered from their clients are referred to as PHISs (Privately Held Information Systems).

CIPHER framework addresses electronic systems, digital information kinds, and methods for data sharing, processing, and upkeep (not paper documents).

The CIPHER methodological framework's primary goal is to suggest procedures and best practices for protecting privately held information systems online (PHIS). The following are the main features of CIPHER methodological framework: 

• Technology independence (versatility) refers to the ability to be used by any organization functioning in any field, even as existing technologies deteriorate or are replaced by newer ones. 
• PHIS owners, developers, and citizens are the three primary users who focus on this user-centric approach. 
• Practicality - outlines possible precautions and controls to improve or verify whether the organization is safeguarding data from online dangers. 
• It is simple to use and doesn't require specialized knowledge from businesses or individuals. 

Challenges in Implementing Cybersecurity in Banking

Some contributing elements have presented a significant challenge to digital cybersecurity in banking. The following are some of these: 

• Lack of Knowledge:  The general public's understanding of cybersecurity has been relatively low, and few businesses have significantly invested in raising that awareness. 
• Budgets That are Too Small and Poor Management:  Due to the low priority given to cybersecurity, it frequently receives short budgetary shrift. Cybersecurity continues to receive little attention from top management, and programs that assist it are accorded low priority. They might have underestimated how serious these risks are, which is why. 
• Identities and Access are Poorly Managed:  The core component of cybersecurity has always been identity and access management, especially now when hackers are in control and might access a business network with just one compromised login. Although there has been a little progress in this area, much work still needs to be done. 
• Increase in Ransomware:  Recent computer attacks have brought our attention to the growing threat of ransomware. Cybercriminals are beginning to employ various techniques to avoid being identified by endpoint protection code that concentrates on executable files. 
• Smartphones and Apps:  The majority of banking organizations now conduct business primarily through mobile devices. Every day the base grows, making it the best option for exploiters. Due to increased mobile phone transactions, mobile phones have become a desirable target for hackers. 
• Social Media:  Hackers have increased their exploitation as a result of social media adoption. Customers that are less knowledgeable expose their data to the public, which the attackers abuse.

Cybersecurity in Banking Sector as a Career

The banking sector is a prime target for cyber-attacks due to the sensitive financial data it handles. As digital transformation continues to reshape banking, the need for strict cybersecurity measures grows.

This demand has created numerous career opportunities for cybersecurity professionals within the banking industry. According to the Bureau of Labor Statistics, the employment of information security analysts is projected to grow 33% from 2020 to 2030, much faster than the average for all occupations.

The table below explores the job outlook for cybersecurity roles in the banking sector, highlighting key responsibilities, skills, and average salary.

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Every organization is concerned about cyber security. It is crucial for banks to have the proper cyber security solutions and procedures in place, especially for institutions that store a lot of personal data and transaction lists. Banking cyber security is an issue that cannot be bargained with. Hackers are more likely to target the banking sector as digitalization advances. 

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Frequently Asked Questions (FAQs)

The goal of cybersecurity in the banking sector is to protect consumer assets. The bank should also take action to thwart the hackers. The number of financial-related acts is growing as more individuals work.

Through fraudulent transactions, cyberattacks can result in significant financial losses for the customer and the banks. Attackers who steal sensitive data from a banking institution may sell it. Data that has been stolen is later misused.

Antivirus software is typically used on bank computers, firewalls, fraud detection, and website encryption, which encrypts data so that only the intended receiver can read it. Your financial institution likely implements these security precautions if you bank online.

Vitesh Sharma

Vitesh Sharma, a distinguished Cyber Security expert with a wealth of experience exceeding 6 years in the Telecom & Networking Industry. Armed with a CCIE and CISA certification, Vitesh possesses expertise in MPLS, Wi-Fi Planning & Designing, High Availability, QoS, IPv6, and IP KPIs. With a robust background in evaluating and optimizing MPLS security for telecom giants, Vitesh has been instrumental in driving large service provider engagements, emphasizing planning, designing, assessment, and optimization. His experience spans prestigious organizations like Barclays, Protiviti, EY, PwC India, Tata Consultancy Services, and more. With a unique blend of technical prowess and management acumen, Vitesh remains at the forefront of ensuring secure and efficient networking solutions, solidifying his position as a notable figure in the cybersecurity landscape.

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