literature review on banking services

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• Published: 03 September 2022

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

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

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

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

Introduction

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

Issues of performance and risk management of banks

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

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

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

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

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

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

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

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

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

Data and research methods

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

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

Determining the appropriate keywords for exploring the data

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

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

Initial search results and limiting criteria

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

Data analysis tools and techniques

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

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

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

Bibliometric and network analysis

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

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

Source of publications

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

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

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

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

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

Location and affiliation analysis

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

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

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

Key author analysis

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

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

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

Keyword analysis

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

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

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

Citation analysis

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

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

Page Rank analysis

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

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

Content analysis

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

Regulation and profitability of banks

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

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

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

Regulation and NPA (risk-taking of banks)

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

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

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

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

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

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

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

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

NPA (risk-taking) in banks and profitability

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

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

Triad and the performance of banks

Regulation and triad.

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

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

Concentration banking and triad

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

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

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

Competition, the performance of banks, and triad

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

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

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

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

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

Transparency, corporate governance, and triad

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

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

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

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

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

Discussion of the findings

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

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

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

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

Research Implications of the study

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

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

Flexible but full enforcement of the regulations

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

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

Competition

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

No incentive to take risks

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

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

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

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

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

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

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

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

Conclusion of the study

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

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

Practical implications of the study

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

Limitations and scope for future research

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

Availability of data and materials

SCOPUS database.

Abbreviations

Systematic literature review

World Financial Crisis

Non-performing assets

Differential banking system

SCImago Journal Rank Indicator

Liquidity convergence ratio

Net stable funding ratio

Fast moving consumer goods

Regional rural banks

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‘SR’ performed Abstract, Introduction, and Data methodology sections and was the major contributor; ‘AS’ performed Bibliometric and Network analysis and conceptual framework; ‘GP’ performed citation analysis and discussion section; ‘VMB’ collated data from the database and concluded the article. All authors read and approved the final manuscript.

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

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• Bank performance
• Profitability
• Bibliometric analysis
• Scientometric analysis

Advances in mobile financial services: a review of the literature and future research directions

International Journal of Bank Marketing

ISSN : 0265-2323

Article publication date: 5 July 2022

Issue publication date: 24 January 2023

Using the theory, construct, method, moderator (TCMM) format, this framework-based review critically analyses the mobile financial services (MFSs) field through a detailed synthesis and analysis of a sample of mainstream empirical research published in various scientific journals within the period 2009–2020.

Design/methodology/approach

The authors followed a three-step structured approach suggested by Webster and Watson (2002) to search for the literature to synthesise the global perspectives on MFSs and their associated applications and systems. The literature research resulted in the identification of 115 most relevant articles.

The authors identified three major categories or domains within the MFSs comprising the entire spectrum of digital financial services. To facilitate the literature analysis, TCMM is developed and proposed as an organising framework. Moreover, the authors also developed and presented the comprehensive framework of MFS domains and explicitly identified 14 different research themes for future research in MFSs.

Originality/value

Prior attempts to synthesise and analyse mainstream academic research in MFSs have been scant and limited to a specific MFS domain: mobile banking or mobile payment. The authors synthesised a more extensive body of knowledge and provided a global perspective on the MFS field. Unlike the past literature reviews which followed traditional frameworks such as antecedents, decisions and outcome (ADO); TCCM; and 6 W Framework (who, when, where, how, what and why), the authors developed and proposed TCMM as organising framework.

• Mobile banking
• Mobile payments
• Mobile money
• Mobile financial services
• Theory-construct-method-moderator framework

Shaikh, A.A. , Alamoudi, H. , Alharthi, M. and Glavee-Geo, R. (2023), "Advances in mobile financial services: a review of the literature and future research directions", International Journal of Bank Marketing , Vol. 41 No. 1, pp. 1-33. https://doi.org/10.1108/IJBM-06-2021-0230

Emerald Publishing Limited

Copyright © 2022, Aijaz A. Shaikh, Hawazen Alamoudi, Majed Alharthi and Richard Glavee-Geo

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

An exciting transition has been taking place within the banking and payment fields in the last four decades. Branch banking has been taken over by branchless banking with anytime – anywhere services. Net (short for Internet) banking has been transformed mainly into mobile banking. The automated teller machines (ATMs), point-of-sale (POS) terminals and payment cards have been replaced with near-field communication (NFC)-enabled and contactless mobile payment applications, including mobile wallets and wearables. The chat-bots and robo-advisors have created an intelligent mobile banking and payment culture in many developed countries. Nonetheless, the consumers of branchless banking in Western countries have shown greater reliance on Internet- and mobile-based access to their banking accounts and to other value-added services, such as investments, advisory services, loans and mortgages. Consumers in non-Western or developing countries, on the other hand, have started adopting and using the mobile phone to execute traditional retail transactions such as fund transfers and paying utility bills. Mobile money has in fact played a significant role in transforming the socioeconomic conditions of many underprivileged and unbanked population segments in non-Western countries ( Glavee-Geo et al. , 2019 ; Karjaluoto et al. , 2021 ).

Given the increasing use of and demand for smartphones and mobile banking and payment services, research examining the consumer, management, policy and theoretical perspectives in the mobile financial service (MFS) area is underway ( Chawla and Joshi, 2017 ). However, efforts have been made to synthesise a more extensive body of knowledge in the MFS field, albeit with a limited scope and purpose. For example, Shaikh and Karjaluoto (2015) conducted a domain-specific structured review in the mobile banking adoption field from 2005 to 2014. In the context of the Gulf Cooperative Council countries and based on 46 articles, Alkhowaiter (2020) produced a comprehensive literature review and performed a meta-analysis of the factors affecting the use and adoption of digital banking and payment methods. Dahlberg et al. (2008) published a framework-based review in the mobile payment services field based on 73 articles published within the period from 1999 to 2006. Kim et al. (2018) conducted a systematic literature review based on 54 academic research papers in the areas of MFS, financial inclusion and developments. Unlike the previous research efforts, where the synthesis of the literature was limited to a specific MFS domain (mobile payments, mobile banking) or region (Gulf Cooperative Council countries), the purpose of our research endeavour was to conduct a framework-based review of the literature on the global MFSs.

In addition, Paul and Benito (2018) used the antecedents, decisions and outcome (ADO) format in their review article; Paul and Rosado-Serrano (2019) developed and used the theory, construct, characteristics and methodology (TCCM) model and Xie et al. (2017) used the 6 W Framework (who, when, where, how, what and why). We, on the other hand, used the Theory, Construct, Method, Moderator (TCMM) model after considering the nature of the MFS field and the articles selected and included in this framework-based review (quantitative/survey and mix-method approach). Survey articles provide objective information concerning the theory, constructs, method and moderators used in such articles ( Shaikh and Karjaluoto, 2015 ). Nonetheless, the purpose of introducing the TCMM model was to offer a new or better model while relying on the existing models, such as TCCM. Our suggested TCMM is somehow a close variant of TCCM model developed by Paul and Rosado-Serrano (2019) . Another purpose of developing the TCMM framework is to evaluate the extent to which previous research within the MFS field had used moderators in their studies. Similarly, the TCMM framework considered the use of “moderators” as a special type of constructs that can help researchers to develop novel and interesting relationships between constructs in MFS research.

The synthesis of these moderating variables as envisaged in the TCMM model could identify the gaps such as which variable (including the control variables) has been used extensively and rarely. In addition, moderators provide new insights and contingency relationships amongst constructs without which new perspectives of a phenomenon could be hidden. Moderator effects occur in situations where the moderator (an independent variable or construct) changes the strength or even the direction of a relationship between two constructs in the model ( Hair et al. , 2017 , p. 41). This framework-based review was meant to contribute to the understanding and distinction of various domains identified as falling within the wide ambit of MFSs. We offered new definitions of mobile banking, mobile payments and mobile money and proposed the TCMM model. We also developed and proposed a framework presenting the MFS ecosystem and explicitly identified the future research areas left unidentified by the research on MFSs to date.

While drafting the plan for the future research directions, we considered emerging themes such as pandemic (e.g. the COVID-19 pandemic), new regulatory frameworks (General Data Protection Regulations, Revised Payment Services Directive [PSD2]), technologies (wearables), methods (experimental), intelligent mobile banking and payment systems using chat-bots and the emergence of new demographic groups. The primary literature search resulted in 115 relevant articles published within the period from 2009 to 2020. The reason for the selection of a 12-year period for the review, from the beginning of 2009 to the end of 2020, is that MFSs received a significant boost only after the advent of the smartphone, which was introduced by Apple Corporation in 2007.

The major contribution of this literature review is the identification of three major MFS domains, which are defined as a wide range of traditional and value-added services, retail transactions, banking activities and information accessible through portable devices and wearables ( Dorfleitner et al. , 2019 ). These three domains comprising the entire spectrum of digital financial services are as follows: mobile banking services (including downloadable mobile applications), mobile payment services (including both proximate and contactless/remote mobile wallets and smart watches) and mobile money services (including branchless, short-message service [SMS], agency and money transfers). Moreover, we highlight herein several implications beneficial for banking and payment industry professionals (e.g. bank managers, digital marketing managers), regulators and policymakers. For example, the use of the TCMM model has identified several critical variables and consequences that affect consumer choices, behaviours, and attitudes towards the adoption of various MFS applications and systems. Therefore, bank marketing managers are better informed about the key factors that influence MFS adoption. This can help in the formulation and implementation of effective marketing strategies. In addition, MFSs have grown into a new subsector of the economy, supporting the financial inclusion programs started by government agencies in various countries. Our review has provided further insight into the different MFS domains, which would, for example, help regulatory authorities promote a cashless culture, document transactions, promote transparency, reduce the volume of the informal economy and reach out to the unbanked consumer segment.

For the organisation of the rest of this article, we present the research method that we used in our review in section 2 and define the frameworks and models widely accepted amongst the researchers within the MFS field and the choices of outcome constructs, moderators and determinants of adoption and use of MFSs in section 3 . We then present a comprehensive framework of the MFS ecosystem in section 4 , discuss the findings of the review and highlight their implications in section 5 . We allude to the study's limitations and explicitly identify the future research areas in section 6 .

2. Research method

To help identify the articles to include in our literature review, we relied on interdisciplinary journals and the journals in the business, marketing, retail, consumer behaviour and information system fields. Further, we employed the structured approach suggested by Webster and Watson (2002) to search for the most relevant literature within the MFS field, as presented and discussed below.

All the authors were made responsible for searching and including in the article the empirical studies that analysed the user behaviour, intention and beliefs in the pre-adoption, continuous use, sustained use or post-adoption of MFSs in different regions and markets, including developed, emerging and developing ones. This was done by scanning the abstract, introduction and method sections of the articles that were found. Articles on the most recognised multidisciplinary databases for peer-reviewed contents (Elsevier/ScienceDirect, ProQuest, Web of Science, EBSCOhost and Emerald) were accessed using different but relevant keywords, such as mobile financial services , mobile banking , mobile payments , mobile wallets , mobile money , agent banking , SMS banking , portable banking , branchless banking , banking for the poor , micro-banking and intelligent mobile banking .

We limited our literature search to the period 2009–2020. In total, the 115 most relevant journal articles (excluding conference proceedings and book chapters) were shortlisted and included in the review. The 115 articles thus provide a holistic overview of the MFS field and are considered valuable. The lead author summarised the articles in an MS Excel sheet with multiple columns for easy synthesis and retrieval of information. Some of these columns created in the Excel sheet featured the year of publication, context (location or research site), moderators analysed, theory/model/framework, construct/factors/antecedents and research methods that were used. The Excel sheet was subsequently examined by each of the remaining authors to ensure that the obtained articles were placed under the right categories. Finally, all the authors examined each article together to build a consensus before further analysis. Our analysis of the 115 articles included in our review revealed that the volume of published articles in the MFS field has increased since 2017. To be specific, we divided the 2009–2020 time period into three periods, each consisting of four years: 2009–2012, 2013–2016 and 2017–2020. In the first period, 31 peer-reviewed journal articles were published; in the second, 38, and in the third, 46.

During the data analysis process, each author performed a detailed analysis and interpretation of one domain from the proposed TCMM framework, and then wrote about the results of the analysis and interpretation in the findings section. The results of each author's analysis and interpretation were subsequently examined by all the authors for validation, synergy and consistency.

3. Findings

3.1 mobile financial services.

The term MFSs is used to represent an all-inclusive service portfolio for consumer segments accessing and using retail- and business-related banking and payment services on mobile devices. Considering the usefulness, ubiquity, convenience, outreach and low-cost benefits of MFSs, some authors (e.g. Dorfleitner et al. , 2019 ) have used the term MFSs to refer to microfinance or transformational banking; the term has also been used for the consumers living in remote areas and popularly recognised as unbanked or underbanked.

Before the advent of smartphones in 2007, low-cost and feature phones were primarily used to communicate through voice calls or SMS messages. The emergence of smartphones with Internet connectivity marked the turning point in the banking and payment industry, expanded cell phone use for value-added services, revolutionised the financial industry and paved the way for the creation of various smart and disruptive business models. Consequently, in less than a decade since smart devices first made their way into consumers' everyday lives, mobile commerce and mobile payments have become mainstream, outpacing the traditional banking and payment models, including branch, ATM, net, POS and SMS banking, referred to collectively by Shaikh and Karjaluoto (2015) as an alternative or alternate delivery channels .

The three domains identified in the MFS field (i.e. mobile banking, mobile payments and mobile money), although sometimes cross paths and overlap their scope and usage with regard to the nature of the transactions (micro and macro), consumer–bank relationship (with and without a formal bank account), consumer segmentation or types (banked, under-banked and un-banked), access methods (remote and proximity) and mobile devices (smart and traditional or feature devices) used to access such services, they differentiate from each other (See Table 1 ). For example, mobile devices used for conducting mobile banking include cell phones and tablets. Therefore, accessing banking services from a laptop or a personal computer is not considered mobile banking, rather, laptops are largely aligned with the online/Internet banking category ( Shaikh and Karjaluoto, 2015 ). Also, unlike mobile banking, a formal relationship between a person and a bank is not required in mobile payments. Third-party applications developed and provided by, for example, FinTech and telecom companies can be used to receive and send funds using mobile payment applications. Mobile money, on the other hand, is considered appropriate for that consumer segment which is popularly known as under-banked or un-banked ( Glavee-Geo et al. , 2019 ).

3.1.1 Mobile banking

In one of their highly cited articles, Shaikh and Karjaluoto (2015) offered a comprehensive definition of mobile banking: an innovative service for conducting financial and non-financial transactions using a mobile device, namely a mobile phone, smartphone or tab l et. Earlier, the segregation between the financial and non-financial services in mobile banking was not evident, which enlarged the scope and purpose of mobile banking. Nonetheless, a summary of the mobile banking definitions appearing in the historical and contemporary literature is given in Table 2 .

Mobile banking, also referred to as cell phone banking, is an innovative and cost-effective application of mobile commerce with extended capabilities, which is used virtually by bank account holders using web browser or downloadable mobile application on smart phones or tablet with internet connectivity to access the traditional and value-added financial and non-financial services including funds transfer, investment advices, utility bills payment, balance enquiry, security alerts or notifications, new product or service promotion, conveniently anytime anywhere.

3.1.2 Mobile payment

Unlike mobile banking, the mobile payment technology and services were introduced to broaden the scope of payment services, including the value-added services using different payment technologies, such as radio frequency, NFC and the quick response code. The key to mobile payment, including the mobile wallet, is the downloadable application. According to Karjaluoto et al. (2019) , the downloadable mobile applications for mobile payment contain several features and payment options, provide broader and more cost-effective service options and better protection, and primarily target banked and de-banked consumers. De-banked consumers refer to those who refuse to access and use various alternative delivery channels despite the availability of these to them and who refuse to maintain any formal relationship with any bank in the form not only of a checking account but also of a savings account ( Shaikh and Karjaluoto, 2016 ). Most of these de-banked consumers are Millennials, Generation Z and Generation Alpha and rely on value-added mobile-only financial and payment services ( Shaikh and Karjaluoto, 2019 ).

Mobile payments, also referred to as mobile wallet, is anytime anywhere payment mechanism offered by banking and non-banking entities including FinTech, which can be executed seamlessly in a proximity and remote mode by anyone with a handheld device and peer-to-peer or mobile payment application to access the value-added services and conduct micro and macro payments electronically including funds transfer, utility bills payment, making donations, mobile balance pop-up etc.

3.1.3 Mobile money

Various terms have been used to represent mobile money services, such as branchless banking , banking for the poor , mobile transfers , SMS banking and agent banking . According to the World Bank Global Findex Database (2018) , over 1.7 billion adults globally are unbanked. Yet, many of these unbanked people own a cell phone that can help them access formal payment and other financial services ( Glavee-Geo et al. , 2019 ).

Mobile money, defined as a financial innovation that provides transfers, payments and other financial services at a low or zero cost to individuals in developing countries where banking and capital markets are deficient and financial inclusion is low ( Pelletier et al. , 2020 ), has an enormous potential to reach the unbanked. It has been widely considered a crucial technology for escaping poverty and disparities. To obtain this revolutionary service's benefits, all that one needs is a feature phone with the standard network coverage. Unlike tellers, who provide customer service in bank branches, or ATMs, mobile money depends on an agent network and is based on a straightforward business logic: high volume, low value. This logic entails that mobile money promotes high transaction volume with low monetary value. This makes mobile money very different from mobile banking and mobile payment, both of which facilitate high-value, low-volume transactions. The explanation by Suárez (2016) and Heyer and Mas (2011) of the crux of mobile money and how it differs from the mobile banking and mobile payment technologies provide much relief. For example, mobile money can be implemented in emerging and developing countries where there are no financial alternatives or delivery channels available. The presence of any alternative delivery channel will dilute the mobile money initiative. Also, there must be a high mobile phone diffusion rate amongst a wider segment of the population destined to adopt and use mobile money. There must also be a sufficient demand for formal or documented financial services. A favourable regulatory environment supporting the market's supply side and technological innovation is required.

Mobile money, also referred to as branchless or agent banking, is a financial inclusion tool used in many developing and emerging countries by financially excluded rural or less privileged communities with no or limited access to formal banking services such as branches, ATMs, POS and Internet banking, to send and receive the funds and making micro payments across vast distances without being limited to location and time, using a feature phone with no internet connectivity using a simple short-message service (SMS) technology anytime anywhere.

3.2 Theory, construct, method, moderator framework (TCMM)

3.2.1 theoretical underpinnings (t).

Figure 1 provides a snapshot of the theories, models and frameworks used in the MFS field obtained from the literature included in our review. Nonetheless, from the perspective of method (see Figure 2 ), the articles' synthesis revealed that most of the studies included in the review had used technology of acceptance model (TAM) and its modifications (35 and 30%) and unified theory of acceptance and use of technology (UTAUT) and its modifications (24 and 21%). Instead of relying on a specific model or framework, the authors of 17 studies (15%) made their theoretical models consist of various factors and relationships, and made explicit assumptions and caveats underpin them. These new hypothesised relationships between and amongst various factors have provided several theoretical contributions.

3.2.2 Constructs or variables (C)

Perceived ease of use and its conceptually identical constructs ( effort expectancy , self-efficacy and complexity ) were found in 93 (81%) of the studies;

Consumer behavioural intention and closely related terms such as usage intention , intention to use and usage behaviour were found in 87 (76%) of the studies;

Perceived usefulness and its conceptually analogous constructs ( performance expectancy , perceived performance and relative advantage ) were found in 82 (71%) of the studies; and

Trust (including perceived trust ) was found in 68 (59%) of the studies.

The psychological science variables such as social influence , which is considered akin or similar to the variable subjective/social norms , also received much attention from previous research. In total, 57 studies (50%) examined the effects of social influence , including subjective/social norms , on various antecedents/variables in the context of MFS adoption and use. For example, previous studies ( Baptista and Oliveira, 2017 ; Oliveira et al. , 2014 ) found that social influence positively affects consumer use intention and adoption of MFSs. The variable social influence reflects the notion that user behaviour is influenced by the way the peers, friends or family members value IT and the related services ( Baptista and Oliveira, 2017 ), such as MFSs and their associated applications.

Considering the nature of online and mobile transactions, which are considered highly risky and prone to fraud and misuse, the variables perceived trust and perceived risk , both product-related factors, are also considered significant in the prior research, primarily affecting the adoption and use intention and the attitudes and behaviour of consumers. Consumer trust (initial, cognitive and emotional) was used as an independent and outcome construct in 68 studies (59%) while perceived risk was used 43 times (37%). Most of these studies examined the negative effect of perceived risk on various variables, such as attitude towards MFS adoption and use and behavioural intention to adopt and use MFSs ( Glavee-Geo et al. , 2017 ; Makanyeza and Makanyeza, 2017 ), relationship quality ( Chen, 2012 ) and performance expectancy ( Luo et al. , 2010 ).

3.2.3 Methods and markets (M)

Most of the studies that were included in our review used the quantitative or survey method (103 studies or 90%), and a few used mixed methods (12 studies or 10%). Most of the studies were conducted in emerging markets such as China (16 studies or 14%) and India (11 studies or 10%), followed by Taiwan (8 studies or 7%), South Korea (7 studies or 6%) and Ghana (6 studies or 5%). Five studies (or 4%) were conducted in Iran, Malaysia and the USA. Of the 115 studies included in our review, only three (or 3%) conducted a multi-country assessment (See Figure 3 ).

3.2.4 Moderators (M)

In addition to the main constructs (independent or dependent variables), several moderators (also known as contingent variables) were used in the reviewed research articles to examine how a moderator could affect the strength of the relationship between an independent variable and a dependent variable. Research has divided these moderators into three major categories: (1) the demographic moderators gender, age, profession and income ( Chaouali and Souiden, 2019 ; Glavee-Geo et al. , 2017 ; Baptista and Oliveira, 2017 ); (2) the cultural moderators individualism/collectivism, uncertainty avoidance, masculinity/femininity and power distance ( Baptista and Oliveira, 2015 ) and (3) the psychological moderators self-efficacy, perceived image, subjective norms, personal innovativeness ( Mohammadi, 2015 ), trust and perceived risk ( Chung and Kwon, 2009 ) (see Table 6 ).

For example, examining UTAUT2 with cultural moderators, Baptista and Oliveira (2015) provided new insights into the variables affecting the acceptance of mobile banking and how culture influences individual user behaviour regarding it. The study finding suggests that collectivism, uncertainty avoidance, short term and power distance are the most significant cultural moderators.

4. Comprehensive framework of MFS domains

The comprehensive framework of the MFS domains that we used in our review is shown in Figure 4 . This proposed framework has identified the service dynamics and has segregated the services offered by mobile banking into two domains: financial and non-financial. This segregation was identified earlier by Shaikh and Karjaluoto (2015) in their highly cited article entitled “Mobile banking adoption – a literature review”. The financial services accessed and executed by the consumers include fund transfer, cash withdrawal and utility bill payment. Non-financial services include balance inquiry, receiving essential notifications, chat-bots and a conversation with robo-advisor. Chawla and Joshi (2017) classified MFSs and the associated offerings into three broad categories: banking services, payment services and value-added services. Banking services largely represent innovative and downloadable mobile apps and website and text banking. Payment services include peer-to-peer payment, utility bill payment and POS banking using NFC payment mechanisms. Value-added services include virtual wallets, advisory including virtual support, personal financial management, cloud storage and wearables.

The term customer dynamics refers to the classification of the consumers into different domains considering their choices, behaviours, habits, use purpose and level of access to the banking and payment technologies and alternative delivery channels. Banked consumers can access and use the products, services and channels anytime, anywhere. Un-banked consumers, on the other hand, have limited or no access to banking and payment services. Here, mobile money technology and services provided relief to many.

The demographic or regional dynamics or classification and user dynamics mainly imply the applicability and feasibility of offering various MFSs to the demographically dispersed population. More specially, reaching a demographically dispersed potential consumer base and providing them with formal banking services have always been challenging. This is true of many unbanked segments in Africa ( Baptista and Oliveira, 2015 ). A novel retail mobile banking service initiative called branchless banking was introduced in the 1990s to several developing countries, such as Kenya and Ghana, and several emerging countries, such as Brazil and South Africa. For instance, the branchless banking scheme called M-Pesa introduced in Kenya in early 2007 was phenomenally successful ( Dermish et al. , 2011 ). It is now being considered a catalyst for much of the research done on branchless banking to date.

The institutional dynamics segregate all institutions that develop and deploy mobile-based financial and payment services, such as government and regulatory bodies, banking and microfinance entities and non-banking entities such as merchants, FinTech and third-party developers. In addition to the banking entities traditionally considered solely responsible for developing and deploying various banking and financial services and alternative delivery channels, the participation of non-banking entities in the MFS ecosystem is growing primarily due to the global recession in 2008 and the promulgation of PSD2 and open-banking regulation in 2018. This changing regulatory landscape has structurally disrupted the traditional banking ecosystem, transformed the retail banking and payment landscape, and has widened the scope and increased the use of MFSs.

Published in May 2018, PSD2 of the European Commission (EC) requires banking companies and credit unions to provide third-party app developers and service providers such as FinTech with access to their consumer data. This conspicuous development has transformed the banking and payment landscape, and thus also the bank–customer relationship. Moreover, these revolutionary guidelines will empower non-banking entities such as PayPal and technology titans such as Facebook to develop and deploy a wide range of banking, financial and payment products according to the needs and requirements of the consumers, thereby creating several challenges and competition for the diligently regulatory banks.

Concerning the COVID-19 pandemic and social distancing, as of this article's writing, the pandemic was still raging, and people worldwide were getting used to the new normal. The pandemic has created wide-ranging challenges and has worsened the situation for many traditional banking and payment players as it increased the demand for more digital, contactless, remote, safe and clean services. Consequently, the digital and remote retail payment services increased across the globe; consumers began availing of these services more frequently, and the use of publicly shared devices like ATMs and POS terminals was reduced exponentially. COVID-19 has boosted the demand for more remote services, including the demand for mobile-based financial and payment services.

5. Discussion

The consumer behaviour and fast-emerging mobile and contactless technologies have widened the differences amongst the three domains and have therefore enriched the financial landscape. For instance, the institutions have been segregated to provide financial services to consumers. Here, unlike the banking sector, which was traditionally responsible for developing and deploying banking services, including mobile banking, the FinTech companies such as PayPal and the technology titans (Google, Facebook) are offering digital payment options and undertaking several initiatives to provide a host of services to the consumers on their cell phones and tablets. Unlike mobile money services, mobile banking and mobile payment services are diligently regulated and largely developed and deployed by banking companies and credit unions.

The new regulatory landscape has created a new breed of financial institutions such as FinTech offering mobile banking and payment services. In addition, the primary devices used for accessing and conducting mobile banking are mobile phones and tablets whereas laptops and personal computers are used to access and conduct Internet banking transactions. Further, the analysis of the literature suggests that the research on the actual continuous use of MFSs is particularly relevant and essential for the financial services sector, including banking companies, mainly for two major reasons. Firstly, the relationship between a customer and an organisation changes over time. Customer relationships' dynamic nature is especially important in service industries that offer continuous services, such as financial and insurance services ( Shaikh et al. , 2015 ). Secondly, a huge investment underpins mobile telephone and technology development and implementation and the underlying purpose of this investment is to create a sustainable and long-term relationship with the consumers, which is possible only when the consumer accepts and continuously uses the company's technology, service or product.

Our research revealed a trend in the evolution, development and growth of the MFS field. A shift in mobile banking and payment research was also observed. For example, in the 1990s, non-empirical studies (essentially focussing on conceptual work) and practitioner-oriented work in MFS dominated the literature. In the early 2000s, empirical research (e.g. survey studies, case studies, field studies) started dominating the literature, showing the maturity of the field.

The context and the technical aspects of the studies published in the MFS field also vary. For example, in the 1990s, SMS banking started to dominate MFSs. In 2007, after the advent of smartphones and other smart devices, the changing regulatory scenarios in many countries provided greater depth and support to the banking and non-banking industries. Consequently, downloadable mobile banking and payment applications were developed, providing access to traditional and value-added services. These developments widened the scope and increased the use of mobile banking and payment applications and services. Academic research on such applications and services started appearing in mainstream journals in the early 2000s, and such research has been sustained to this day.

Similarly, PDA use in conducting mobile banking transactions faded away after the introduction of smartphones in 2007. The services offered through mobile banking services vary considerably in scope and nature. For example, mobile banking includes non-financial mobile accounting (e.g. mini-bank statement, balance enquiry, chequebook request, service notifications and saving beneficiary details) and other value-added services, such as mobile brokerage (selling and buying financial instruments) and MFSs (utility bill payment, fund transfer, making donations and insurance policy subscription).

Like ATM and Internet banking, branchless banking has been considered a separate alternative delivery channel in various countries, such as Kenya, Ghana, Brazil, India and Pakistan. To deal with the regulatory aspects governing digital banking, several developing and emerging countries have drafted a separate set of regulations on branchless banking. Other striking advantages associated with branchless banking are (1) unlike mobile banking, branchless banking does not usually involve cutting-edge technology and sophisticated services and (2) the branchless banking channel is used mainly for payments and transfers, not for savings or credit, but these additional services may be offered in the future.

For the banking industry, COVID-19 has accelerated the transformation of banking from paper-based to digital/online, with the consumers' banking preferences and financial sentiments rapidly evolving. It has also fast-tracked the digitisation program across the banking and payment industry. Notwithstanding, not many articles have examined the role played by the COVID-19 pandemic in promoting the digital culture. However, it has been widely accepted ( Haapio et al. , 2021 ; McKinsey and Company, 2020 ; Goodell, 2020 ) that the new normal has brought about noticeable changes in consumer engagement behaviour when accessing and using digital payment services, including MFSs. The same is also evident from the volume of publications of articles in the MFS field. Out of 115 articles published during 2009–2020 and included in this review, a noticeable increase in the publication of the articles in the MFS was noticed during the last four years, i.e. since 2017. This trend continues and further accelerated since 2019. This is perhaps due to the COVID-19 related crises and the consumer choices for more remote services using mobile applications.

5.1 Implications for theory and industry

Our systematic review has offered important theoretical contributions. Its initial contribution is the conceptualisation, validation and segregation of three major domains: mobile banking, mobile payment and mobile money. As explained earlier, each of these domains follows a different path and targets a different consumer segment. Consequently, this noteworthy finding provides the research in the field with an opportunity to highlight the importance of each of these domains for improving customers' attitudes, behaviour and intention regarding the adoption and use of MFSs and how each of these domains meet the consumer variant needs for more innovative and portable banking and payment services.

From a careful reading of the literature, it was observed that research has identified four distinct research streams: (1) consumer pre-adoption resistance behaviour towards business information systems ( Laukkanen et al. , 2009 ), (2) consumer pre-adoption acceptable behaviour towards business information systems ( Hanafizadeh et al. , 2014 ), (3) consumer post-adoption or continuous use behaviour towards business information systems ( Bhattacherjee, 2001 ; Shaikh and Karjaluoto, 2015 , 2016 ) and (4) consumer pre- and post-adoption behaviours towards business information systems ( Kim and Son, 2009 ). Two major research domains, pre-adoption or acceptance and post-adoption or continuous use, were considered paramount when investigating MFSs globally. We also found that the individual acceptance of information systems remained a central and recurrent theme in consumer behaviour and business information system research in the MFS field ( Bhattacherjee and Sanford, 2006 ), but little empirical evidence of the continuous or sustained use of MFSs is available. This is of much concern as the long-term development of MFSs relies on users continued use of them ( Yuan et al. , 2016 ).

Our TCMM framework-based review expanded the previous research by identifying and reporting the similarities amongst various variables, which provides vital information to the research when (1) constructing or modifying models or frameworks with added variables, (2) avoiding the overlapping of the variables and (3) seeking to improve the effectiveness and usability of the theoretical models. For example, our findings indicate that the variable perceived usefulness is akin to the variables performance expectancy , perceived benefit , relative advantage and perceived performance ; perceived ease of use is similar to its antecedents effort expectancy , perceived self-efficacy and complexity ; social influence is similar to subjective/social norm ; facilitation conditions is similar to perceived behavioural control ; perceived financial cost is akin to its antecedent perceived financial resources and perceived credibility is similar to its antecedents perceived security and privacy and structural assurance .

Another significant contribution of the TCMM framework-based review is the development of the “Comprehensive framework of MFS domains” as shown in Figure 4 . We applied the TCMM framework to analyse MFS research and outline roadmaps for the future research in the three major research domains. Summarising the prioritisation of the variables affecting the consumer adoption and use of MFSs provide useful information for the research. For example, the results of our review suggest that the variables perceived ease of use (including effort expectancy , perceived self-efficacy and complexity ), perceived usefulness (including performance expectancy , perceived benefit , relative advantage and perceived performance ), trust , social influence (including subjective and social norms ) and risk are the significant drivers of the behavioural intentions to adopt, resist and continuously use MFSs.

Our review suggests that consumers' decision to adopt and continuously use various innovative banking and payment services is primarily dominated by two major factors: the ease of use and usefulness of the services, which implies that the companies should simplify their offers and increase their customer utility. This will help the executives and marketing professionals effectively engage their customers across all touchpoints or alternative delivery channels to build customer commitment and achieve customer retention ( Lemke et al. , 2011 ). SMS-based mobile banking and payment services provide limited options and are considered less hedonic. Downloadable banking and payment applications provide high security and a wide range of services to consumers. Adding more hedonic features to SMS-based banking and payment, such as those that produce pleasure and provide leisure will increase the consumers' adoption and sustained use of such services, especially in emerging and developing countries.

The perceived value of MFSs has been sparsely used as an exogenous and endogenous variable in the extended research. In the simplest terms, price is what you pay for a service or product while value is what you get for what you pay. Particularly at the present time, when the benefits and advantages of MFSs are being considered, we believe that the industry players must have a clear understanding of what value creation means and must develop a value-minded approach. Unlike mobile banking and payment services, USSD- and SMS-based branchless banking services' uptake looks considerably high, especially in developing and emerging countries. Banking companies and other financial institutions should continue investing in the mobile money or branchless banking business and developing models of such to provide sustainable financial services, obtain an additional revenue source and increase their consumer base. After all, for most of the ‘bottom-of-the-pyramid underbanked and unbanked population’, it is either mobile or nothing ( Dogbevi, 2010 ; Glavee-Geo et al. , 2019 ).

6. Limitations and future research agenda

Our review was not without any limitations. One of its major limitations is the type of studies considered and included in the review. Although MFSs have received greater attention from academicians and practitioners of late, the practitioner-oriented articles published in renowned and predominantly practitioner-oriented journals were not considered and included in our review. In addition, our review was dominated by survey studies; non-survey studies were excluded from the review. Other study limitations and a comprehensive list of the future research directions are discussed below.

6.1 Mobile money, financial inclusion and the bottom-of-the-pyramid consumers

As evident from the TCMM framework and the resulting “Comprehensive framework of MFS domains” shown in Figure 4 , few empirical studies on branchless banking (mobile money) were found, which were searched to contribute to the understanding of the bottom-of-the-pyramid consumers' adoption and use behaviour. In other words, the low levels of financial inclusion of a large number of mobile phone subscribers in emerging and developing countries make it imperative to investigate if an expansion of mobile phone deployment can generally contribute to social welfare, consumer well-being, greater financial inclusion ( Ghosh, 2016 ) and the greater use of MFSs.

6.2 New methodical domains, including experiments and simulations

While a strong quantitative tendency characterised the articles that were included in our review, a few empirical studies grounded in a mix-method approach, including qualitative and quantitative methods, were found (cf. Lashitew et al. , 2019 ). Quantitative modelling and measurement were used to explain MFS adoption and continuous use in specific contexts. Our review also showed the lack of certain methodological domains, such as experiments and simulations. Most of the cause–effect relationships implicitly argued for in the MFS literature were based on correlational studies. Future research may consider using other research methods, such as experimental research and simulation, in examining the various domains of MFSs. Methodological innovations in MFS research will provide robustness of the findings, a strong validation of theories and potentially new theory development.

6.3 Visualisation approaches and the mobile financial services field

Future studies should also consider using bibliometric networks to visualise publications within the three main fields (mobile banking, mobile payments and mobile money) with regard to citation, co-citation, bibliographic coupling and keyword co-occurrence. The visualisation approaches, such as the distance-, graph- and timeline-based approaches ( Van Eck and Waltman, 2014 ), can help provide insightful findings in the area of MFSs.

6.4 Requirement of more comparative or multi-country assessments

Comparative studies of different countries can also help explore the differences amongst countries in consumer perceptions of the perceived value of MFSs due to the differences in culture, preferences, demographics and institutional contexts amongst countries. Although PSD2 was primarily meant for the European Union (EU) member countries, some non-EU member countries have also adopted it. Therefore, studies on the impact of PSD2 on the MFS users/consumers, banks and non-financial actors in non-EU member countries may be insightful. The possibility of PSD2 creating innovation opportunities and challenges outside the EU or the European Economic Community (EEC) cannot be underemphasised. Future studies investigating the impact of MFSs on consumers within and outside the EU/EEC will be useful to policymakers and managers for policy reforms and service design decisions regarding MFSs in such regions.

6.5 New regulations: the key driving force for mobile financial services

The EC developed and implemented PSD2 to create a safer and more inclusive and innovative European payment system. Amongst the many objectives of PSD2 are to protect consumers when they pay online and to promote the development of an innovative online and mobile payment culture ( European Commission, 2015 ). Collaboration with FinTech presented strategic opportunities despite the initial technical challenges ( Brodsky and Oakes, 2017 ). The implementation of PSD2 presents many worthwhile research possibilities. For example, future studies can investigate if the outcomes envisaged by the regulation have been met. The impact of PSD2 on banks, bank customers and non-banking actors can be better examined through qualitative interviews to contribute to the understanding of the directive's challenges and success factors. Large-scale quantitative data collection through a survey of MFS users/consumers in the EU member countries and beyond can help establish a robust relationship between the implementation success factors and/or barriers and their impact on customer value.

6.6 Open banking and mobile financial services

PSD2 implementation supports open banking. Open banking is a collaborative model in which banking data are shared through an application programming interface between two or more unaffiliated parties to deliver enhanced capabilities to the marketplace ( Brodsky and Oakes, 2017 ). However, while open banking provides enhanced value and benefits to end-users, it also creates data security challenges. Future research in the MFS field can explore the impact of PSD2 on risk, data security and value creation. PSD2 is expected to usher in an entirely new financial service ecosystem and lead to fiercer competition between banks and non-banks, in which banks' roles may shift markedly ( Brodsky and Oakes, 2017 ). Research examining open-banking models in the MFS field and their impact on customer experience is a future-study option.

6.7 Mobile financial applications

The research on the adoption and use of downloadable mobile banking/payment applications (mobile communication technologies are ubiquitous and span a wide range of applications) is highly limited, perhaps overlooked by the previous research. Future studies should consider investigating consumer attitudes towards and behaviour regarding the use of these applications against the backdrop of increased penetration of smartphones and increased use of innovative transactional applications for payment purposes.

6.8 New demographic groups, including millennials, generation Z and generation alpha

Our review showed that the previous studies in the MFS field also focussed on the impact of demographics (e.g. gender differences in MFS adoption/use). The new demographic groups (the millennials, generation Z and generation alpha) allow MFS research regarding such groups' needs, expectations and preferences. Research that also seeks to combine psychological variables with innovation adoption theories to better explain the MFS phenomenon will lead to new insights and will contribute to theory building. For example, the recently developed picky shopper scale ( Cheng et al. , 2021 ) differentiates between picky by acceptance and picky by rejection . Future research can integrate the picky shopper scale into studies comparing the shopping behaviours and innovation adoption of generation X, generation Y and the millennials using MFSs as a context.

6.9 Mobile money and the associated challenges

MFSs have seen many innovations and digital transformations in recent years. For example, mobile money ( Glavee-Geo et al. , 2019 ; Senyo and Osabutey, 2020 ) is a form of FinTech innovation that enables financial transactions through mobile services and is a driver of financial inclusion. Unlike formal banking services, mobile money technology relies on an agent network ( Glavee-Geo et al. , 2019 ). FinTech is a disintermediation force where disruptive technologies are the main drivers ( Das, 2019 ). While mobile money agents play a vital role in this transformation in most of the countries where mobile money has been introduced, cases of fraud and other exploitative activities have been reported ( Akomea-Frimpong et al. , 2019 ). Future empirical studies can investigate the impact of such behaviours (fraud, exploitation) on the adoption and use of mobile money, and its ethical considerations. In addition, the mobile money agents' role as service agents also requires further research, most especially when the actions or inactions of the agents can have a significant impact on the service levels.

6.10 Non-financial value-added services

Much emphasis has been placed on examining the financial aspects of MFSs, and their non-financial aspects have been sparsely examined. Some of these non-financial services are real-time and important account messaging, including service notifications and alerts, which have created a new research domain dealing with non-financial transactions. Nonetheless, very few attempts have been made to consider the importance of non-financial services and the role that they play in providing a greater experience to the consumers. For example, examining the key marketing drivers of consumer experience with non-financial transactions available on mobile banking apps, Shaikh et al. (2020) found that the consumer awareness, usefulness and ease of use of non-financial transactions play significant roles in increasing consumers' sustained use of mobile financial apps. Future research may also examine the effect of the digital notifications in such apps on the attitudes and behaviours of consumers.

6.11 A dedicated scale for mobile financial services

On top of the future research endeavours mentioned in the previous sections, developing dedicated scales for MFSs will benefit both scholarly research and practice when such scales are used in the survey design. The development of dedicated scales for MFSs is thus recommended.

6.12 Mobile financial services and the COVID-19 pandemic

The COVID-19 pandemic has brought about significant disruptions in the social and economic lives of people all over the world. Social distancing, restrictions on mass gatherings and avoidance of physical touchpoints due to the risk of infection have led to a shift from paper-based and other physical touchpoint/contacts (e.g. ATMs) to online transactions. It can be argued that the COVID-19 pandemic has accelerated the digitisation process across the banking, payment and retail sectors. Future research should examine the role played by the pandemic in promoting a digital financial culture. Hence, future studies should consider the impact of the COVID-19 pandemic on digital financial transformation and digitalisation.

6.13 Artificial intelligence (AI)-enabled mobile financial services

The term artificial intelligence (AI) was coined by John McCarthy in 1957 and referred to computers with cognitive skills similar to humans, resulting in immense efficiency gains for firms that use it, and for their clients ( Russell and Norvig, 1995 ). The popular AI tools used in the banking and payment industry include robo-advisors, chat-bots, conversational AI, biometric authentication, call centre agent matching, account management and fraud detection ( Mistry, 2018 ). Despite these motivations, the impact and use of AI in the banking and payment sector have not been studied to date ( Deubner, 2021 ). As such, with the rise of AI, the roles and behaviours of bank and retail customers need to be re-evaluated ( Jakšič and Marinč, 2019 ). Despite the desire of the payment industry to have their customers interact with their AI-enabled solutions, it is unknown if their customers have the desire to do so ( Payne et al. , 2018 ), thereby leaving a huge research gap in the examination of such phenomenon. Therefore, future studies in the area of AI-based mobile banking and payment are recommended.

6.14 Artificial intelligence-enabled mobile banking and payment services (AI-MBPSs) and gender disparity

Future research on AI-MBPSs will be consequential if they will also examine gender differences in the adoption and use of AI-MBPSs, especially in countries traditionally considered to have a male-dominated society, with significant gender disparity. Such research may solicit the experiences of female customers when accessing and using AI-MBPSs, thereby providing deep insights into the role of gender in AI-MBPS adoption and use. To the best of our knowledge, no previous study has examined the gender differences in AI-MBPS adoption and use.

Snapshot of the theories, models, and frameworks used in the mobile financial services field

Summary of models, theories, frameworks used in the mobile financial services literature

The demographic distribution of the articles conducted on mobile financial services

Comprehensive framework of MFS domains

Difference between mobile banking, mobile payment, and mobile money

Studies on mobile payment

Studies on mobile money

Frequency of use of the constructs in the review's sample of studies published in the mobile finance service domain from 2009 to 2020 (frequency > 10)

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Further reading

Akturan , U. and Tezcan , N. ( 2012 ), “ Mobile banking adoption of the youth market: perceptions and intentions ”, Marketing Intelligence and Planning , Vol.  30 No.  4 , pp.  444 - 459 , doi: 10.1108/02634501211231928 .

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LITERATURE REVIEW ON E-BANKING SERVICES

2014, res publication

Banks adopt E-banking as a means to replace their traditional delivery channel through branch banking mainly due to the cost of setting up of physical branches and increased overheads associate with maintaining them. While adopting any new channel of service delivery, service is one of the primary benefit which a customer expects from the service provider. The consumers compares the benefits and weigh them against the costs associated with the service. E-Banking services are gradually replacing the traditional banking services. In order to gain competitive advantage over the competing banks, the banks are continuously improving their services through e-banking services. This paper has examined reviews collected in the area of e-banking services which includes Internet Banking, ATM banking, Mobile banking etc.

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Internet Banking becomes user friendly in today generation. Customer feels internet banking is safe and secure. Many application like online fund transfer, Payment of Income tax, mobile phone recharges, paying electricity bills, paying Dth recharge more. Customer doesn't have to go to the bank for transactions. Instead, customer can access your account any time and from any part of the world, and do so when you have the time, and not when the bank is open. For busy executives, students, and homemakers, e-banking is a virtual blessing. The research was conducted in Thiruvannamalai, Tamil Nadu. The research was based on consumer interested and perception about usage of electronic banking system and transaction.

In Today's scenario role of e-banking is very valuable. Without e-banking no banks can work. In this study we analyse, how much e-banking used in Public and Private sectors bank? (in reference to SBI and HDFC bank) Objective of the study is to find the consumer satisfaction in respect of e-banking and the perception of employees for using e-banking in Public and Private sectors banks. The method of the study is Primary and Secondary both. Study showed perception of customer regarding service quality and satisfaction of employee in internet banking services. As well as this study analyze the working style as a comparison between Public and Private sectors banks in respect of SBI and HDFC bank.

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Today traditional banking services, based on lending and accepting deposits related. The emergence of knowledge-based economy and the wider evolution of communication technology, banking services have undergone profound changes during the past decades. In order to provide the quality, customer service delivery and minimum transaction cost, banks have invested to a great extent in ICT and have adopted ICT networks for delivering a wide range of banking technologies and e-banking services in recent year. In this context, this study revealed that income, gender and age wise factors are placing an important role towards the usage of o electronic banking. The research confirmed the conceptual framework stating that if skills can be upgrade there will be a greater demand for E-Banking among customers.

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Electronic banking (e-banking) is a tool whose appropriate, accurate and timely utilization can lead to a successful performance in a competitive world. In other words, expanding e-banking should be considered for realizing customer orientation and customer satisfaction. However, when different types of e-banking services are provided but their quality is not acceptable, not only the customers would not be satisfied but they would be complaining about them. Considering the fact that all the organizations are seeking to attract new customers and improve their satisfaction, this issue is a critical one particularly in banks since they have a constant contact with the customers. On the other hand, the competition among banks and loan institutions as well as other financial supplies is increasing. Hence, realizing a competitive advantage seems essential for the survival of the banks. Modern banking services, which are closely related to information and communication technology, are among the most important factors in realizing competitive advantage for the banks and attracting new customers and increasing their satisfaction. In this study, using the field research method, we investigate the relationship between the usage of electronic services and satisfaction as well as attracting new customers in different branches of Eqtesade Novin Bank in Urmia. 1. INTRODUCTION With the increasing spread of information technology (IT), all the aspects of human life have fundamentally changed so that the modern world is in the course of a complete alteration. It can be said that the current industrial world have to embrace this change and being constant will cause interference in social, political and economic relationships of the individuals in a community or even in the international relations arena. Developing or lack thereof information technology in some societies has caused interference with the relations or the increase of relations among some countries. Modern communication technologies have conquered time and space dimensions and have changed the modern world into a global village so that it seems the modern human being has entered another world. During the two last decades of the twentieth century, three important innovations; namely fax, cellphone and the internet, have shown that how the expansion of communication can change the service industry and the daily life routines of people. Advancement in information and communication technologies (ICT) has both improved the supply of services and decreased the service costs. The impact of information and communication technology (ICT) in the field of trade and commerce has led to structural alterations in global trade as well as the emergence of a phenomenon called e-commerce, a process in which all the products will be exchanged through communicative or computerized connection networks or both of them. For instance, the internet, as a new channel for economic exchange, has provided the organizations with new resources for income generation and different opportunities and the volume of exchanges through internet is increasing on a daily basis and the companies avoiding this technology will soon be vanished from the face of the market arena. With the development of electronic systems, geographical distance has lost its meaning, which has led to an increasing competition among different companies and institutions including the banks. In order to reach the potential opportunities of the market and to overcome the different barriers and threats present in the complex business environment, the banks should possess competitive advantage. The electronic banking system is a context for reaching this competitive advantage. Nowadays, many banks in the global arena provide electronic services and an increasing majority of the customers tend to do their banking activities through electronic systems and without actually going to the bank branches. Using electronic banking services, the customers of the banks would be able to do their banking activities when and where they please and the banks will also enjoy lower operational costs due to the decrease in the number of staff and branches.

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Competition and Efficiency in the Mexican Banking Industry pp 9–35 Cite as

Literature Review of Banking Studies

• Sara G. Castellanos ,
• Gustavo A. Del Ángel &
• Jesús G. Garza-García  

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Banks are important in mobilizing and allocating savings in an economy and can solve important moral hazard and adverse selection problems by monitoring and screening borrowers and depositors. Besides, banks are important in directing funds where they are most needed in an efficient manner and have direct implications on capital allocation, industrial expansion, and economic growth (Berger, Demirguc-Kunt, and Haubrich 2003; Levine 1997). Banks also play an important role in diminishing informational asymmetries and risks in the financial system. Hence, the study of the banking industry and its impact on the economy is of the utmost importance. The effects of concentration and competition on bank performance are pertinent since they have important policy implications. A recent global trend of consolidation in the banking sector has intensified, generating important debates on its effects on the profitability of banks, consumer costs, the efficiency in allocating resources in an economy, and on overall financial stability.

• Data Envelopment Analysis
• Market Power
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• Banking Sector
• Foreign Bank

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Castellanos, S.G., Del Ángel, G.A., Garza-García, J.G. (2016). Literature Review of Banking Studies. In: Competition and Efficiency in the Mexican Banking Industry. Palgrave Macmillan, New York. https://doi.org/10.1057/9781137518415_2

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

Omar h. fares.

Ted Rogers School of Retail Management, Toronto Metropolitan University, 350 Victoria St, Toronto, ON M5B 2K3 Canada

Seung Hwan Mark Lee

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.

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.

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. ​ Fig.1). The 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 ).

Thematic map

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 ​ Table1 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.

Thematic count

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 ​ Tables2, 2 , ​ ,3, 3 , and ​ and4 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 ).

Detailed future research directions—Theme: Strategy

Detailed future research recommendations—Theme: Processes

Detailed future research recommendations—Theme: Customer

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.

Biographies

has a Master of Science in Management from Toronto Metropolitan University.

Dr. Irfan Butt

is Assistant Professor of Marketing at Toronto Metropolitan University.

Dr. Seung Hwan Mark Lee

is a Professor of Retail Management at Toronto Metropolitan University.

See Tables ​ Tables2, 2 , ​ ,3 3 and ​ and4 4 .

Declarations

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Publisher's Note

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

Contributor Information

Omar H. Fares, Email: [email protected] .

Irfan Butt, Email: [email protected] .

Seung Hwan Mark Lee, Email: [email protected] .

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