**1. Introduction**

The Global Financial Crisis (GFC) showcased that banks driven solely by profit, earnings and share price maximisation alone would fail. Although, success or failure of banks is highly dependent on the bank's ability to make money, it is not the only determinant of bank soundness. Amongst the equally important success factors lies in adequate capital and liquidity holdings, quality assets and making sound management decisions, that leads to the creation of value. As such, Capital (C), Asset (A), Management (M), Earning (E), Liquidity (L) and Sensitivity (S) (CAMELS) are important determinants of bank's health and wellbeing [1–3].

AI is expected to deliver additional global economic output of \$13 trillion a year [4]; contribute \$15.7tr. to the global economy by 2030 [5] and is expected to increase productivity gains by 20–40% [6]. Several initiatives have emerged as a result where approximately \$1 trillion in costs is expected to be exposed to AI

transformation in financial services sectors by 2030, out of which \$450 million of this is in banking [6]. While, European Commission has increased its annual investments in AI by 70%. AI market is expected to be worth \$16.06 billion by 2022, growing at 62.9% compound annual growth rate [7].

The numerous efforts and initiatives in AI investment suggests that AI is here, and it is here to stay. As such, the chapter looks to critically assess how able are banks to effectively deploy AI into their daily operations to improve CAMELS from a bank's perspective. The chapter discusses opportunities proposed by AI that could influence bank soundness.

The chapter contributes to literature in several ways. The earlier researchers have emphasised on the application of AI on the financial sector as a whole [6, 8, 9] or comparative analysis of AI applications in specific areas as service providers such as credit evaluation, portfolio management, financial prediction and planning [10–13] or by examining customer experience [5, 6, 8]. Therefore, these studies are not sufficient to understand the opportunities proposed by AI from a bank's sole perspective. To fill this gap the chapter has taken a holistic approach in scrutinising the opportunities relished by banks solely in deploying AI. By doing this the chapter provides a significant insight into the important opportunities that AI technology can offer the banking industry to ensure its survival. The chapter also further considers bank soundness with the application of AI from various aspects of Capital (C), Asset (A), Management (M), Earning (E), Liquidity (L) and Sensitivity (S) (CAMELS) determinants of bank soundness. To the best of our knowledge, this chapter is the first reviewing deployment of AI in banking operation in light of CAMELS. Earlier research [1–3] has only emphasised on bank soundness from the CAMELS perspective. The chapter also more specifically focuses from both the service provider and customer end, providing further insight from a holistic perspective. Most importantly, the intention is to examine through the lens of CAMELS how sound are banks having applied AI into their processes.

The chapter is organised as follows: the next section presents a brief theoretical discussion on the importance of embracing AI. Section three introduces the literature gathering and research method. Section four presents result and discussions on the opportunities relished by banks on application of AI from CAMELS perspective. The last section concludes the chapter and highlights insight on further research.

#### **2. Literature review**

The banking sector is the heartbeat of the economy. Yet, despite central banks efforts to keep banks afloat by recapitalization, cash injections amongst other measures banks are still underperforming, failing, with one or two microfinance banks disappearing annually [14]. On top of this, The GFC worsened the situation by causing many more bank failures leading to concentration in the financial markets. To promote economic growth governments lowered entry barriers to encourage more players to enter and stimulate competition in the financial markets. In UK, new banks could enter the market with reduced capital and liquidity requirements [8]. This led to the growth of Fintech, technology-based companies that offer financial products at competitive rates. As well as Challenger banks whose competitive advantage lies in its digital technology build on Machine

**269**

papers.

*Artificial Intelligence and Bank Soundness: A Done Deal? - Part 1*

Learning (ML) outperforming UK's five big banks through fierce competition and subsector domination in the field [8, 15]. Studies have confirmed the sluggishness and weaknesses in the banking industry rest in the banks' inability to tap into AI solutions. Thus, the biggest game-changer for banks lies in its rapid adoption of AI technology. AI is a competitive advantage for banks. As it not only helps banks to remain competitive, but also to fight off weak profitability [5, 16–18]. As such, AI is no more an enabler or enhancer of productivity but a necessity that ensures

The incoming and future customers of banks are Millennials and Generation Z. These generations are more in tuned to technology-based services, and thus, demand more choices, flexibility, and control over banking. As such, banks need to embed AI into their operation to cater for the 21st century customers' expectations

Banks also work with large volumes of data. As such, it is inhumanly impos-

sible to process, find patterns, make fast and accurate decisions in a timely manner. AI on the other hand, is capable and has the capacity to conduct the job effortlessly in real time with increased data storage at a lower cost. The constant advancement in AI technology is also enhancing AI capabilities and capacities making it limitless [9] enabling banks to offer extraordinary services to its

The GFC and the opaqueness of the banking industry has led to increased scrutiny and regulation on banks. This makes digital platforms a necessity. Digital platforms ensure all data are consistently and systematically recorded in a logical and meaningful manner, making processes more transparent, increasing the reli-

It is apparent that banks cannot exist without the help of AI in moving

The research is conducted as a conceptual chapter with the aim to provide a deeper understanding of the opportunities parted by AI from a service provider and customer perspective. To answer the research question on how able banks are to effectively deploy AI into their daily operations to improve CAMELS from a bank's perspective, a systematic review of the literature and objective observations were undertaken to examine banks through the lens of bank soundness determinants of CAMELS. The observations found in existing literature are gathered to assemble a framework categorized by CAMELS **Figure 1**. The literature was gathered through the Scopus database as a main source of finding existing literature. The database offers a wide range of management and business-related studies relevant for the topic of research. In addition, other databases such as Google Scholar, Social Science Research Network (SSRN), SpringerLink and IEEE Xplore were also examined. Journal articles since the period 2000–2020 were extracted using the prescribed keywords of Bank, Bank soundness, Financial Sector, Artificial Intelligence (AI), CAMELS. Only articles that were available in full text, published in scholarly, peer reviewed journal were chosen to be closely examined. The search was also conducted using the backward and forward approach where reference list of articles was utilised to find further research

*DOI: http://dx.doi.org/10.5772/intechopen.95539*

offering a range of services, in seconds, 24/7.

ability and confidence in the banking system [5, 12].

survival and sustainability.

customers.

forward.

**3. Research methods**

#### *Artificial Intelligence and Bank Soundness: A Done Deal? - Part 1 DOI: http://dx.doi.org/10.5772/intechopen.95539*

*Operations Management - Emerging Trend in the Digital Era*

growing at 62.9% compound annual growth rate [7].

influence bank soundness.

ing applied AI into their processes.

further research.

**2. Literature review**

transformation in financial services sectors by 2030, out of which \$450 million of this is in banking [6]. While, European Commission has increased its annual investments in AI by 70%. AI market is expected to be worth \$16.06 billion by 2022,

The numerous efforts and initiatives in AI investment suggests that AI is here, and it is here to stay. As such, the chapter looks to critically assess how able are banks to effectively deploy AI into their daily operations to improve CAMELS from a bank's perspective. The chapter discusses opportunities proposed by AI that could

The chapter contributes to literature in several ways. The earlier researchers have emphasised on the application of AI on the financial sector as a whole [6, 8, 9] or comparative analysis of AI applications in specific areas as service providers such as credit evaluation, portfolio management, financial prediction and planning [10–13] or by examining customer experience [5, 6, 8]. Therefore, these studies are not sufficient to understand the opportunities proposed by AI from a bank's sole perspective. To fill this gap the chapter has taken a holistic approach in scrutinising the opportunities relished by banks solely in deploying AI. By doing this the chapter provides a significant insight into the important opportunities that AI technology can offer the banking industry to ensure its survival. The chapter also further considers bank soundness with the application of AI from various aspects of Capital (C), Asset (A), Management (M), Earning (E), Liquidity (L) and Sensitivity (S) (CAMELS) determinants of bank soundness. To the best of our knowledge, this chapter is the first reviewing deployment of AI in banking operation in light of CAMELS. Earlier research [1–3] has only emphasised on bank soundness from the CAMELS perspective. The chapter also more specifically focuses from both the service provider and customer end, providing further insight from a holistic perspective. Most importantly, the intention is to examine through the lens of CAMELS how sound are banks hav-

The chapter is organised as follows: the next section presents a brief theoretical discussion on the importance of embracing AI. Section three introduces the literature gathering and research method. Section four presents result and discussions on the opportunities relished by banks on application of AI from CAMELS perspective. The last section concludes the chapter and highlights insight on

The banking sector is the heartbeat of the economy. Yet, despite central banks efforts to keep banks afloat by recapitalization, cash injections amongst other measures banks are still underperforming, failing, with one or two microfinance banks disappearing annually [14]. On top of this, The GFC worsened the situation by causing many more bank failures leading to concentration in the financial markets. To promote economic growth governments lowered entry barriers to encourage more players to enter and stimulate competition in the financial markets. In UK, new banks could enter the market with reduced capital and liquidity requirements [8]. This led to the growth of Fintech, technology-based companies that offer financial products at competitive rates. As well as Challenger banks whose competitive advantage lies in its digital technology build on Machine

**268**

Learning (ML) outperforming UK's five big banks through fierce competition and subsector domination in the field [8, 15]. Studies have confirmed the sluggishness and weaknesses in the banking industry rest in the banks' inability to tap into AI solutions. Thus, the biggest game-changer for banks lies in its rapid adoption of AI technology. AI is a competitive advantage for banks. As it not only helps banks to remain competitive, but also to fight off weak profitability [5, 16–18]. As such, AI is no more an enabler or enhancer of productivity but a necessity that ensures survival and sustainability.

The incoming and future customers of banks are Millennials and Generation Z. These generations are more in tuned to technology-based services, and thus, demand more choices, flexibility, and control over banking. As such, banks need to embed AI into their operation to cater for the 21st century customers' expectations offering a range of services, in seconds, 24/7.

Banks also work with large volumes of data. As such, it is inhumanly impossible to process, find patterns, make fast and accurate decisions in a timely manner. AI on the other hand, is capable and has the capacity to conduct the job effortlessly in real time with increased data storage at a lower cost. The constant advancement in AI technology is also enhancing AI capabilities and capacities making it limitless [9] enabling banks to offer extraordinary services to its customers.

The GFC and the opaqueness of the banking industry has led to increased scrutiny and regulation on banks. This makes digital platforms a necessity. Digital platforms ensure all data are consistently and systematically recorded in a logical and meaningful manner, making processes more transparent, increasing the reliability and confidence in the banking system [5, 12].

It is apparent that banks cannot exist without the help of AI in moving forward.
