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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.


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.

figure 1

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.

figure 2

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.

figure 3

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.

figure 4

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.

figure 5

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.

figure 6

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.


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 ].

figure 7

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.


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

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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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The Oxford Handbook of Banking (2nd edn)

A newer edition of this book is available.

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10 Measuring the Performance of Banks: Theory, Practice, Evidence, and Some Policy Implications

Joseph P. Hughes is Professor of Economics at Rutgers University. He has been a Fellow of the Wharton Financial Institutions Center and a Visiting Scholar at the Federal Reserve Bank of Cleveland, the Federal Reserve Bank of Philadelphia, the Federal Reserve Bank of New York, and the Office of the Comptroller of the Currency. His research has been published in such journals as the American Economic Review, the Journal of Banking and Finance, the Journal of Economic Theory, the Journal of Financial Intermediation, the Journal of Financial Services Research, the Journal of Money, Credit, and Banking, and the Review of Economics and Statistics. He received his Ph.D from the University of North Carolina at Chapel Hill.

Loretta J. Mester is president and chief executive officer of the Federal Reserve Bank of Cleveland. In addition, she is an Adjunct Professor of Finance at the Wharton School, University of Pennsylvania, and a fellow at the Wharton Financial Institutions Center. She is the managing editor of the International Journal of Central Banking and a co-editor of the Journal of Financial Services Research. In addition, she is an associate editor of several other academic journals and serves on the management committee of the International Journal of Central Banking. Her publications include research on the organizational structure and production efficiency of financial institutions, the theory and regulation of financial intermediation, agency problems in credit markets, credit card pricing, central bank governance, and inflation. Her research has been published in the Journal of Finance, the American Economic Review, the Review of Financial Studies, and the Review of Economics and Statistics, among other journals. She received her Ph.D in economics from Princeton University.

  • Published: 07 April 2015
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The unique capital structure of commercial banking—funding production with demandable debt that participates in the economy’s payments system—affects various aspects of banking. It shapes banks’ comparative advantage in providing financial products and services to informationally opaque customers, their ability to diversify credit and liquidity risk, and how they are regulated, including the need to obtain a charter to operate and explicit and implicit federal guarantees of bank liabilities to reduce the probability of bank runs. These aspects of banking affect a bank’s choice of risk vs. expected return, which, in turn, affects bank performance. This chapter gives an overview of two general empirical approaches to measuring bank performance and discusses some of the applications of these approaches found in the literature. One application explains how better diversification available at a larger scale of operations generates scale economies that are obscured by higher levels of risk-taking. Studies of banking cost that ignore endogenous risk-taking find little evidence of scale economies at the largest banks while those that control for this risk-taking find large scale economies at the largest banks—evidence with important implications for regulation.

10.1 Introduction

What do commercial banks do? What are the key components of banking technology? What determines whether banks operate efficiently? Banks’ ability to ameliorate informational asymmetries between borrowers and lenders and to manage risks are the essence of bank production. The literature on financial intermediation suggests that commercial banks, by screening and monitoring borrowers, can help to solve potential moral hazard and adverse selection problems caused by the imperfect information between borrowers and lenders. Banks are unique in issuing demandable debt that participates in the economy’s payments system. This debt confers an informational advantage to banks over other lenders in making loans to informationally opaque borrowers. In particular, the information obtained from checking account transactions and other sources allows banks to assess and manage risk, write contracts, monitor contractual performance, and, when required, resolve non-performance problems. Bhattacharya and Thakor (1993) review the modern theory of financial intermediation, which takes an informational approach to banking.

That banks’ liabilities are demandable debt also gives banks an incentive advantage over other intermediaries. The relatively high level of debt in a bank’s capital structure disciplines managers’ risk-taking and their diligence in producing financial services by exposing the bank to an increased risk of insolvency. The demandable feature of the debt, to the extent that it is not fully insured, further heightens performance pressure and safety concerns by increasing liquidity risk. These incentives tend to make banks good monitors of their borrowers. Thus, banks’ unique funding by demandable debt that participates in the economy’s payments system gives banks both an incentive advantage and an informational advantage in lending to firms too informationally opaque to borrow in public debt and equity markets. The uniqueness of bank production, in contrast to the production of other types of lenders, is derived from the special characteristics of banks’ capital structure: the funding of informationally opaque assets with demand deposits. 1   Calomiris and Kahn (1991) and Flannery (1994) discuss the optimal capital structure of commercial banks.

But banks’ ability to perform efficiently—to adopt appropriate investment strategies, to obtain accurate information concerning their customers’ financial prospects, and to write and enforce effective contracts—depends in part on the property rights and legal, regulatory, and contracting environments in which they operate. Such an environment includes accounting practices, chartering rules, government regulations, and the market conditions (e.g., market power) under which banks operate. Differences in these features across political jurisdictions can lead to differences in the efficiency of banks across jurisdictions. 2

Banks’ unique funding by demand deposits motivates key components of the legal and regulatory environments that influence managerial incentives for risk-taking and efficiency. The participation of banks in the payments system leads to their regulation and, in particular, to restrictions on entry into the industry. The need to obtain a charter to open a bank confers a degree of market power on banks operating in smaller markets and, in general, permits banks to exploit valuable investment opportunities related to financial intermediation and payments. Government regulation and supervision promote banks’ safety and soundness with the aim of protecting the payments system from bank runs that contract bank lending and threaten macroeconomic stability. Protecting the payments system frequently involves deposit insurance. To the extent that the insurance is credible, it reduces depositors’ incentive to run banks when they fear banks’ solvency. Consequently, it reduces banks’ liquidity risk and, to the extent it is underpriced, gives banks the incentive to take additional risk for higher expected return.

10.2 Banking Technology and Performance

10.2.1 banks’ risk menu and conflicting incentives for risk-taking.

Mispriced deposit insurance and policies that are too-big-to-fail (TBTF) can create a cost-of-funds subsidy that gives banks an incentive to take additional risk. 3 But banks also have an incentive to avoid risk to protect their valuable charter from episodes of financial distress. Distress involves liquidity crises resulting from runs by uninsured depositors, regulatory intervention in banks’ investment decisions, and even the loss of the charter when distress results in insolvency. As discussed in Hughes and Mester (2013b) , Marcus (1984) finds that banks with high-valued investment opportunities maximize their expected market value by pursuing lower-risk investment strategies that protect their charters and thereby preserve their ability to exploit these opportunities. On the other hand, banks with low-valued investment opportunities maximize their expected value by adopting higher-risk investment strategies that exploit the cost-of-funds subsidy of mispriced deposit insurance ( Keeley, 1990 ). Mid-range risk strategies do not maximize value. These dichotomous investment strategies as well as other sources of risk-taking and risk-avoidance fundamentally shape production decisions and must be taken into account when modeling bank production.

The risk environment banks face can be characterized by a frontier of expected return and return risk, which shows a bank’s menu of efficient investment choices. 4 In Figure 10.1 from Hughes and Mester (2013b) , a smaller bank’s menu of investment choices is given by the lower frontier. Consider a smaller bank that operates at point A. 5 To illustrate scale-related diversification, suppose a larger bank is created by scaling up the assets of this smaller bank. In principle, the larger bank can obtain better diversification of its assets, which reduces credit risk, and better diversification of its deposits, which reduces liquidity risk. Thus, the larger bank can efficiently produce the expected return of the smaller bank (point A) with less return risk (point A′). In fact, the larger bank will likely take advantage of its better diversification and produce a different (and perhaps more complicated) mix of financial services. Nonetheless, the risk-expected-return frontier of the larger bank lies above that of the smaller bank because the larger bank has a better menu of investment choices resulting from improved diversification.

Scale-related diversification and risk-return frontiers.

Textbooks point to better diversification, which reduces the costs of risk management, as a key source of scale economies. The link between better diversification and scale economies is apparent when comparing a larger bank operating at point A′ with one operating at point B. A larger bank operating at point A′ has the same expected return but lower risk than the smaller bank operating at point A, while a larger bank at point B operates with the same return risk as the smaller bank but obtains a higher expected return. At point B, the better diversification of deposits allows the larger bank to economize on liquid assets without increasing liquidity risk, while the better diversification of loans allows it to economize on equity capital without increasing insolvency risk. Thus, its expected return for the same risk as the smaller bank is higher.

Better diversification, however, does not necessarily mean that the larger bank operates with less risk; rather, it means the larger bank experiences a better risk-expected-return frontier. Heightened competition and lower-valued growth opportunities in the larger bank’s markets, or lower marginal costs of risk management might induce the larger bank to choose to produce its output with more risk in order to obtain a higher expected return—say the strategy at point C or point D.

A bank’s risk-taking is also influenced by external and internal mechanisms that discipline bank managers. Internal discipline can be induced or reduced by organizational form, ownership and capital structure, governing boards, and managerial compensation. External discipline might be induced or reduced by government regulation and the safety net, capital market discipline (takeovers, cost of funds, stakeholders’ ability to sell stock), managerial labor market competition, outside blockholders of equity and debt, and product market competition. 6 This operating environment can also create agency conflicts that influence managers’ incentives to pursue value-maximizing risk strategies. Managers whose wealth consists largely of their undiversified human capital tend to avoid riskier investment strategies that maximize the value of banks with poorer investment opportunities. However, the presence of a diversified outside owner of a large block of stock might encourage the board of directors to put in place a compensation plan that overcomes managers’ risk aversion and encourages value-maximizing risk-taking ( Laeven and Levine, 2009 ).

Thus, in order to measure the efficiency of bank production it is important to account for bank risk-taking and its efficiency.

10.2.2 The Empirical Measurement of Banking Technology and Performance

There are two broad approaches to measuring technology and explaining performance: non-structural and structural. Using a variety of financial measures that capture various aspects of performance, the non-structural approach compares performance among banks and considers the relationship of performance to investment strategies and other factors such as characteristics of regulation and governance. For example, the non-structural approach might investigate technology by asking how performance measures are correlated with such investment strategies as growing by asset acquisitions and diversifying or focusing the bank’s product mix. It looks for evidence of agency problems in correlations of performance measures and variables characterizing the quality of banks’ governance. While informal and formal theories may motivate some of these investigations, no general theory of performance provides a unifying framework for these studies.

The structural approach is choice-theoretic and, as such, relies on a theoretical model of the banking firm and a concept of optimization. The older literature applies the traditional microeconomic theory of production to banking firms in much the same way as it is applied to non-financial firms and industries. The newer literature views the bank as a financial intermediary that produces informationally intensive financial services and takes on and diversifies risks—unique, essential aspects of financial intermediation that are not generally taken into account in traditional applications of production theory. 7 For example, the traditional theory defines a cost function by a unique cost minimizing combination of inputs for any given level of outputs. Thus, the cost function gives the minimum cost of any given output vector without regard to the return risk implied by the cost-minimizing input vector. Ignoring the implied return risk may be appropriate for non-financial firms, but for financial institutions, return risk plays an essential role in maximizing the discounted flow of expected profits. First, return risk influences the rate at which future expected profits are discounted. Second, return risk affects the expected cost of financial distress. The bank with high-valued investment opportunities may find the level of risk associated with the cost-minimizing vector too high. If so, it may choose to reduce the credit risk of the given output vector by adding more labor and physical capital to improve credit evaluation and loan monitoring. In doing so it trades higher cost (lower profit) for lower profit risk to reduce the expected costs of financial distress and the discount rate on its expected cash flow, thus maximizing its market value. This tradeoff suggests that measuring bank performance by a cost metric or a profit metric that fails to account for endogenous risk-taking is likely to be seriously biased.

Notice in this example that risk influences the decision of how to produce a given output vector and, thus, must influence the cost of producing it. In Figure 10.1 , when the risk-expected-return frontier for the larger bank is narrowly interpreted as showing different investment strategies for producing the same output vector—the scaled-up outputs of the smaller bank—it is clear that larger banks with higher-valued investment opportunities are likely to choose a lower risk-expected-return strategy, say point B or A′, than banks with lower-valued opportunities, say point C or D. Since the cost of producing the scaled-up output vector is likely to differ along the frontier, the value-maximizing input vector and, hence, cost of the output, will be driven in part by risk considerations. And, these risk considerations imply that revenue influences cost when risk matters . How, then, can managers’ preferences for these production plans and their implied risk be represented?

Letting the output vector be represented by q , the input vector by x , and equity capital by k , the technology for producing a given output vector is represented by transformation function T ( x , k ; q ) ≤ 0. Points C and D in Figure 10.1 arise from different input vectors ( x , k ) that produce the given output q . Let z represent the production plan and price environment. Managers’ beliefs about how production plans interact with a given state of the world, s , to yield profit, π , imply a realization of profit, π = g( z , s ), that is conditioned on the state of the world. And managers’ beliefs about the probability distribution of states of the world imply a subjective distribution of profit that is conditional on the production plan: f(π ; z ). Under well-known restrictive conditions, this distribution can be represented by its first two moments, E(π ; z ) and S(π ; z ). 8

The traditional literature on bank production and efficiency assumes banks choose their production plan to minimize expected cost and maximize expected profit: managers rank production plans by their expected profit and cost, the first moment of their subjective probability distribution of profit, f(π ; z ), attached to each production plan. The newer research assumes bank managers maximize the utility of their production plans. Rather than define the utility function over the first two moments, the newer literature defines it over profit and the production plan, U(π ; z ), which is equivalent to defining it over the conditional probability distributions f(π ; z ). Utility maximization is a more general objective that subsumes profit maximization and cost minimization (e.g., Hughes, 1999 ; Hughes et al., 1999 ; Hughes et al., 2000 ; and Hughes, Mester, and Moon, 2001 ). However, when higher moments of the profit distribution influence managers’ preferences, managers may trade profit to achieve other objectives involving risk, say, value maximization. The model treats the choice of risk as endogenous.

Note, however, that the other objectives might reflect agency problems: Managers might take on too little risk in order to protect their jobs, or they might consume private benefits that reduce shareholder wealth. Thus, the utility-maximizing framework can explain inefficient as well as efficient production. When the output vector is held constant, the utility-maximizing cost of output can be derived from the utility-maximizing input demands. This cost function accounts for the choice of whether to produce the particular output vector using a method that has lower risk and lower expected return or a method with higher risk and higher expected return (e.g., point B versus point C in Figure 10.1 ). This choice depends on differences in the value of investment opportunities. In this case, managers’ ranking of production plans captures the profit and profit-risk environment they face.

How one gauges performance in structural models, then, depends on whether one views bank managers as ranking production plans by their first moments (i.e., minimum expected cost or maximum expected profit), or, more generally, by higher moments as well as the first moment, i.e., considerations involving risk. In the latter case, one would want to gauge the tradeoffs between risk and expected return being made by banks where there is less of an agency problem between owners and managers—that is, banks with strong corporate controls (see Hughes, Mester, and Moon, 2001 ). In both the structural and non-structural approaches, the performance metric and the specification of the performance equation reflect implicitly or explicitly an underlying theory of managerial behavior.

As a general specification of the structural and non-structural approaches, let y i represent the measure of the i th bank’s performance. Let z i be a vector of variables that capture key components of the i th bank’s technology (e.g., output levels and input prices) and τ i be a vector of variables affecting the technology (e.g., the ratio of nonperforming to total loans). Jensen and Meckling (1979) add a vector, θ i , of characteristics of the property-rights system, contracting, and regulatory environment in which the i th firm operates (e.g., whether the country has a deposit insurance scheme and the degree of investor protection that exists) and a vector, ϕ i , of characteristics of the organizational form and the governance and control environment of the i th firm (e.g., whether the bank is organized as a mutual or stock-owned firm, the degree of product market concentration, and the number of outside directors on its board). When the sample of banks used in the estimation includes financial institutions located in environments with different property rights and contracting environments or with different governance and control structures, estimating this model permits one to investigate how these differences are correlated with differences in bank performance.

Allowing for random error, the performance equation to be estimated takes the form,

The specification of the vectors z i and τ i differs between the structural and non-structural approaches.

10.2.3 The Structural Approach to Bank Efficiency Measurement: Cost Minimization, Profit Maximization, and Managerial Utility Maximization

The traditional structural approach usually relies on the economics of cost minimization or profit maximization, where the performance equation (1) denotes a cost function or a profit function. Occasionally, the structural performance equation denotes a production function. While estimating a production function might tell us if the firm is technically efficient , that is, if managers organize production such that the firm maximizes the amount of output produced with a given amount of inputs (so that the firm is operating on its production frontier), we are more interested in economic efficiency , that is, whether the firm is responding to relative prices in choosing its inputs and outputs to minimize cost and/or to maximize profit, which subsumes technical efficiency. Risk plays no explicit role in these performance functions, although some papers include one or more dimensions of risk in the estimation as control variables (see Berger and Mester, 1997 and 2003 , and Mester, 2008 , for further discussion). Including risk components as controls does not fully capture the tradeoff between risk and expected return that banks face. While including risk, e.g., the variance of profit, in the cost function would control for the second moment of return, higher moments would not be taken into account, and these higher moments may be an important element in the bank’s production decision. So the standard cost function conditioned on risk is unlikely to capture important considerations in banking production and value maximization. In addition, as discussed below, the assumptions of cost minimization and profit maximization underlying the standard structural approach have been tested and rejected by some papers in the literature. See, for example, Evanoff (1998) , Evanoff, Israilevich, and Merris (1990) , Hughes et al. (1996 , 2000 ), Hughes, Mester, and Moon (2001) , and Hughes and Mester (2013b) .

In the newer literature, the optimization problem is managerial utility maximization, where the manager ranks production plans not just by their first moment—expected profit—but also by higher moments, such as skewness and kurtosis risk, as well as variance risk, that characterize profit risk. The utility-maximizing cost function is derived from the profit function, conditioned on the output vector. As such, the cost function includes arguments that characterize revenue. In Figure 10.1 the larger bank can produce its scaled-up output vector with a menu of production plans that differ by their expected profit and profit risk. The utility-maximizing cost function captures the plan that maximizes managerial utility and thus, reflects a risk-expected return tradeoff.

To specify the utility-maximizing performance equation (1), Hughes et al. (1996 , 1999 , 2000 ) adapt the Almost Ideal Demand System to derive a utility-maximizing profit equation and its associated input demand equations. This profit function does not necessarily maximize profit, since it follows from managers’ assessment of risk and risk’s effect on asset value; it might also reflect managers’ concerns about their job security. Profit maximization (cost minimization) can be tested by noting that the standard translog profit (cost) function and share equations are nested within the model and can be recovered by imposing the parameter restrictions implied by profit maximization (cost minimization) on the coefficients of this adapted system. Hughes et al. (1996 , 1999 , 2000 ) and Hughes and Mester (2013b) test these restrictions in their applications and reject the hypothesis of profit maximization (and cost minimization).

Both newer and traditional performance functions can differ by the definition of cost they use: accounting (cash-flow) cost excludes the cost of equity capital, while economic cost includes it. The challenge of specifying economic cost is in estimating the cost of equity capital. McAllister and McManus (1993) arbitrarily pick the required return and assume it is uniform across banks. Clark (1996) and Fiordelisi (2007) use the Capital Asset Pricing Model to estimate it. Fiordelisi (2007) describes the resulting profit function as “economic value added.” Alternatively, the quantity of equity capital can be substituted for its price. In these cases of restricted cost and profit functions, the expense of equity capital is excluded from the empirical measure of cost and profit.

The traditional structural performance equation can be fitted to the data as an average relationship, which assumes that all banks are equally efficient at minimizing cost or maximizing profit, subject to random error, ε i , which is assumed to be normally distributed. Alternatively, it can be estimated as a frontier to capture best observed practice and to gauge X-inefficiency, the difference between the best-observed practice performance and achieved performance. The literature has used four basic methods for estimating the frontier: stochastic frontier, the distribution-free approach, the thick frontier, and data envelopment analysis (DEA). Berger and Mester (1997) review the estimation methods and present evidence on scale economies, cost X-inefficiency, and profit X-inefficiency using the stochastic frontier and distribution-free methods. 9

In the stochastic frontier method, the error term, ε i , consists of two components; one is a two-sided random error that represents noise (ν i ), and the other is a one-sided error representing inefficiency (μ i ). The stochastic frontier approach disentangles the inefficiency and random error components by making explicit assumptions about their distributions. The inefficiency component measures each bank’s extra cost or shortfall of profit relative to the frontier—the best-practice performance observed in the sample. 10 Let y i denote either the cost or profit of firm i . The stochastic frontier gives the highest or lowest potential value of y i given z i , τ i ,ϕ i , and θi ,

where ε i ≡ μ i   + ν i is a composite error term comprising ν i , which is normally distributed with zero mean, and μ i , which is usually assumed to be half-normally distributed and negative when the frontier is fitted as an upper envelope in the case of a profit function and positive when the frontier is fitted as a lower envelope as in the case of a cost function. β are parameters of the deterministic kernel, F( z i , τ i ,   ϕi ,   θi | β ), of the stochastic frontier. The i th bank’s inefficiency is usually estimated by the mean of the conditional distribution of µ i given ε i , i.e., E(µ i |ε i ). The difference between best observed practice and achieved performance gauges managerial inefficiency in terms of either excessive cost— cost inefficiency —or lost profit— profit inefficiency . Expressing the shortfall and excess as ratios of their frontier (best observed practice) values yields profit and cost inefficiency ratios. While the fitted stochastic frontier identifies best-observed-practice performance of the banks in the sample, it cannot explain the behavior of inefficient banks. A number of papers have surveyed investigations of bank performance using these concepts: for example, Berger and Humphrey (1997) , Berger and Mester (1997) , and Berger (2007) .

As discussed in Hughes et al. (2000) and Mester (2008) , since inefficiency is derived from the regression residual, selection of the characteristics of the banks and the environmental variables to include in the frontier estimation is particularly important. These variables define the peer group that determines best-practice performance against which a particular bank’s performance is judged. If something extraneous to the production process is included in the specification, this might lead to too narrow a peer group and an overstatement of a bank’s level of efficiency. Moreover, the variables included determine which type of inefficiency gets penalized. If bank location, e.g., urban versus rural, is included in the frontier, then an urban bank’s performance would be judged against other urban banks but not against rural banks, and a rural bank’s performance would be judged against other rural banks. If it turned out that rural banks are more efficient than urban banks, all else equal, the inefficient choice of location would not be penalized. An alternative to including the variable in the frontier regression is to measure efficiency based on a frontier in which it is omitted and then see how it correlates with efficiency. Several papers have looked at the correlations of efficiency measures and exogenous factors, including Mester (1993) , Mester (1996) , Mester (1997) , and Berger and Mester (1997) . Mester (1997) shows that estimates of bank cost efficiency can be biased if bank heterogeneity is ignored. See also Bos et al. (2005) on the issue of whether certain differences in the economic environment belong in the definition of the frontier.

Since the utility-maximizing profit function explains inefficient as well as efficient production, it cannot be fitted as a frontier. To gauge inefficiency, Hughes et al. (1996) and Hughes, Mester, and Moon (2001) estimate a best-observed-practice risk-return frontier and measure inefficiency relative to it. The estimated utility-maximizing profit function yields a measure of expected profit for each bank in the sample, and, when divided by equity capital, the expected profit is transformed into expected return on equity, E(π i / k i ). Each bank’s expected (or, predicted) return is a function of its production plan and other explanatory variables. When the estimation of the profit function allows for heteroscedasticity, the standard error of the predicted return (profit), σ i , which is a measure of econometric prediction risk, is also a function of the production plan and other explanatory variables and varies across banks in the sample. 11 The estimation of a stochastic frontier similar to (2) gives the highest expected return at any particular risk exposure:

where ν i is a two-sided error term representing noise, and μ i is a one-sided error term representing inefficiency. A bank’s return inefficiency is the difference between its potential return and its noise-adjusted expected return, gauged among its peers with the same level of return risk. (Note, however, that if a bank’s managers are taking too much or too little risk relative to the value-maximizing amount, this inappropriate level of risk is not taken into account by this measure of inefficiency.)

Koetter (2006) uses the model of managerial utility maximization and the associated measure of risk-return efficiency developed in Hughes et al. (1996 , 1999 , 2000 ) to investigate the efficiency of universal banks in Germany between 1993 and 2004. Comparing the measure of return efficiency with cost and profit efficiency estimated by standard formulations, he finds evidence that efficient banks using a low-risk investment strategy score poorly in terms of standard profit efficiency measures, since they also expect lower profit.

Hughes, Mester, and Moon (2001) take this a step further by recognizing that the utility-maximizing choices of bank managers need not be value maximizing to the extent that there are agency problems within the firm and managers are able to pursue their own, non-value-maximizing objectives. To identify the value-maximizing banks among the set of all banks, they select the quarter of banks in the sample that have the highest predicted return efficiency. These banks are the mostly likely group to be maximizing value or, at least, producing with the smallest agency costs. One can use this set of efficient banks to gauge characteristics of the value-maximizing production technology. For example, mean scale economies across this set of banks would indicate whether there were scale economies as banks expand output along a path that maximizes value. In contrast, mean scale economies across all banks would indicate whether there were scale economies as banks expand output along a path that maximizes managers’ utility, but this can differ from the value-maximizing expansion path to the extent that managers are able to pursue their own objectives and these objectives differ from those of outside owners.

While the model of managerial utility maximization yields a structural utility-maximizing profit function that includes as special cases the standard maximum profit function and a value-maximizing profit function, it is, nevertheless, based on accounting measures of performance. An alternative model developed by Hughes and Moon (2003) gauges performance using the market value of assets. They develop a utility-maximizing q-ratio function derived from a model where managers allocate the potential (frontier) market value of their firm’s assets between their consumption of agency goods (market-value inefficiency) and the production of market value, which, given their ownership stake, determines their wealth. The utility function is defined over wealth and the value of agency goods and is conditioned on capital structure, outside blockholder ownership, stock options held by insiders, and other managerial incentive variables. The authors derive a utility-maximizing demand function for market value and for agency goods (inefficiency). Hence, their q -ratio equation is structural and, consequently, enjoys the properties of a well-behaved consumer demand function. The authors use these properties to analyze the relationship between value (or inefficiency) and the proportion of the firm owned by insiders, which is their opportunity cost of consuming agency goods.

10.2.4 The Non-Structural Approach to Bank Efficiency Measurement

The non-structural approach to bank performance measurement usually focuses on achieved performance and measures y i , in equation (10.1) by a variety of financial ratios, e.g., return-on-asset, return-on-equity, or the ratio of fixed costs to total costs. However, some applications have used measures of performance that are based on the market value of the firm (which inherently incorporates market-priced risk), for example, Tobin’s q-ratio (which is the ratio of the market value of assets to the book value of assets); the Sharpe ratio (which measures the ratio of the firm’s expected excess return over the risk-free return to the volatility of this excess return (as measured by the standard deviation of the excess return)); or an event study’s cumulative abnormal return, CAR (the cumulative error terms of a model predicting banks’ market return around a particular event). Other applications have measured performance by an inefficiency ratio obtained by estimating either a non-structural or structural performance equation as a frontier. The non-structural approach then explores the relationship of performance to various bank and environmental characteristics, including the bank’s investment strategy, location, governance structure, and corporate control environment. For example, the non-structural approach might investigate technology by asking how performance ratios are correlated with asset acquisitions, the bank’s product mix, whether the bank is organized as a mutual or stock-owned firm, and the ratio of outside to inside directors on its board. While informal and formal theories may motivate some of these investigations, no general theory of performance provides a unifying framework for these studies.

Using the frontier methods in a non-structural approach, Hughes et al. (1997) proposed a proxy for Jensen and Meckling’s agency cost: a frontier of the market value of assets fitted as a potentially nonlinear function of the book-value investment in assets and the book value of assets squared. This frontier gives the highest potential value observed in the sample for any given investment in assets. For any bank, the difference between its highest potential value and its noise-adjusted achieved value represents its lost market value—a proxy for agency cost ( X -inefficiency). Several studies have used either this systematic lost market value or the resulting noise-adjusted q-ratio to measure performance: Hughes et al. (1999) , Hughes, Mester, and Moon (2001) , Hughes et al. (2003) , Hughes and Moon (2003) , DeJonghe and Vander Vennet (2005) , Baele, De Jonghe, and Vander Vennet (2006) , and Hughes and Mester (2013b) .

Habib and Ljungqvist (2005) specified an alternative market-value frontier as a function of a variety of managerial decision variables, including size, financial leverage, capital expenditures, and advertising expenditures. Thus, the peer grouping on which the frontier is estimated is considerably narrower than the wide grouping based on investment in assets, and inefficient choices of these conditioning values are not accounted for in the measurement of agency costs.

10.2.5 Specifying Outputs and Inputs in Structural Models of Production

In estimating the standard cost or profit function or the managerial utility maximization model, one must specify the outputs and inputs of bank production. The intermediation approach ( Sealey and Lindley, 1977 ) focuses on the bank’s production of intermediation services and the total cost of production, including both interest and operating expenses. Outputs are typically measured by the dollar volume of the bank’s assets in various categories. As mentioned above, an exception is Mester (1992) , who, to account for the bank’s screening and monitoring activities, measured outputs as loans previously purchased (which require only monitoring), loans currently originated for the bank’s own portfolio, loans currently purchased, and loans currently sold. Inputs are typically specified as labor, physical capital, deposits and other borrowed funds, and, in some studies, equity capital. While the intermediation approach treats deposits as inputs, there has been some discussion in the literature about whether deposits should be treated as an output since banks provide transactions services for depositors. Hughes and Mester (1993) formulated an empirical test for determining whether deposits act as an input or output. Consider variable cost, VC , which is the cost of nondeposit inputs and is a function of the prices of nondeposit inputs, w , output levels, y , other variables affecting the technology, τ, and the level of deposits, x . If deposits are an input, then ∂VC/∂x < 0: Increasing the use of some input should decrease the expenditures on other inputs. If deposits are an output, then ∂VC/∂x >: 0 Output can be increased only if expenditures on inputs are increased. Hughes and Mester’s empirical results indicate insured and uninsured deposits are inputs at banks in all size categories.

10.2.6 Specifying Capital Structure in Performance Equations

Typically, cost and profit functions are measured without considering the bank’s capital structure, which results in a seriously mis-specified model that omits an important funding input, equity capital. However, the newer literature recognizes the importance of bank managers’ choice of risk and capital structure on bank performance. Some of the first structural models to include equity capital as an input are Hancock (1985 , 1986 ), Hughes and Mester (1993) , McAllister and McManus (1993) , Clark (1996) , and Berger and Mester (1997) .

As discussed in Hughes and Mester (1993) , Berger and Mester (1997) , Hughes (1999) , and Mester (2008) , a bank’s insolvency risk depends not only on the riskiness of its portfolio, but also on the amount of financial capital it has to absorb losses. Insolvency risk affects bank costs and profits through (1) the risk premium the bank has to pay for uninsured debt, (2) the intensity of risk management activities the bank undertakes, and (3) the discount rate applied to future profits. A bank’s capital level also directly affects costs by providing an alternative to deposits as a funding source for loans.

Most studies use the cash-flow (accounting) concept of cost, which includes the interest paid on debt (deposits) but not the required return on equity, as opposed to economic cost, which includes the cost of equity. Failure to include equity capital among the inputs can bias efficiency measurement. If a bank were to substitute debt for some of its financial equity capital, its accounting (cash-flow) costs could rise, making the less capitalized bank appear to be more costly than a well-capitalized bank. To solve this problem, one can include the level of equity capital as a quasi-fixed input in the cost function. The resulting cost function captures the relationship of cash-flow cost to the level of equity capital, and the (negative) derivative of cost with respect to equity capital—the amount by which cash-flow cost is reduced if equity capital is increased—gives the shadow price of equity. The shadow price of equity will equal the market price when the amount of equity minimizes cost or maximizes profit. Even when the level of equity does not conform to these objectives, the shadow price nevertheless provides a measure of its opportunity cost. Hughes, Mester, and Moon (2001) find that the mean shadow price of equity for small banks is significantly smaller than that of larger banks. This suggests that smaller banks over-utilize equity relative to its cost-minimizing value, perhaps to protect charter value. On the other hand, larger banks appear to under-utilize equity relative to its cost-minimizing value, perhaps to exploit a deposit subsidy and the subsidy due to the TBTF doctrine. In both cases, these capital strategies, while not minimizing cost, may be maximizing value.

10.2.7 Specifying Output Quality in the Performance Equation

In measuring efficiency, one should control for differences in output quality to avoid labeling unmeasured differences in product quality as differences in efficiency. Controls for loan quality, such as non-performing loans to total loans by loan category or loan losses, are sometimes included in the cost or profit frontier as controls (see Mester, 2008 , for further discussion). As discussed in Berger and Mester (1997) , whether it is appropriate to include nonperforming loans or loan losses in the cost or profit function depends on the extent to which these variables are exogenous. They would be exogenous if caused by economic shocks (bad luck), but could be endogenous to the extent that management is inefficient or has made a conscious decision to cut short-run expenses by cutting back on loan origination and monitoring resources. Berger and Mester (1997) attempt to solve this problem by using, as a control variable, the ratio of nonperforming loans to total loans in the bank’s state. This state average would be nearly entirely exogenous to any one bank, but can control for negative shocks that affect bank output quality.

The variable, nonperforming loans, can also play a role as a quasi-fixed “input” whose quantity rather than price is included in the performance equation. As such, its “cost” is excluded from the performance metric, either cost or profit. Its price is the expected loan-loss rate. Hence, when the cost of nonperforming loans, i.e., loan losses, is excluded from the performance measure, a case can be made for including the level of nonperforming loans, and when the performance measure is net of loan losses, the logic suggests that the loss rate be included in the specification of the performance equation.

10.3 Applications of the Structural Approach

10.3.1 performance in relation to organizational form, governance, regulation, and market discipline.

An increasing number of papers using structural models are exploring the importance of governance and ownership structure to the performance of banks. The structural model is first used to obtain a frontier-based measure of inefficiency. Then inefficiency is regressed on a set of explanatory variables.

Using confidential regulatory data on small, closely held commercial banks, DeYoung, Spong, and Sullivan (2001) use a stochastic frontier to measure banks’ profit efficiency. They find banks that hire a manager from outside the group of controlling shareholders perform better than those with owner-managers; however, this result depends on motivating the hired managers with sufficient holdings of stock. They calculate an optimal level of managerial ownership that minimizes profit inefficiency. Higher levels of insider holdings lead to entrenchment and lower profitability.

Berger and Hannan (1998) consider the relationship of bank cost efficiency, estimated by the distribution-free technique and a stochastic frontier, to product market discipline, gauged by a Herfindahl index of market power. They find that the reduced discipline of concentrated markets is associated with a loss of cost efficiency far more significant than any welfare loss due to monopoly pricing.

DeYoung, Hughes, and Moon (2001) use the model of managerial utility maximization developed by Hughes et al. (1996 , 2000 ) to estimate expected return and return risk. Using these values, they estimate a stochastic risk-return frontier as in equation (3) to obtain each bank’s return inefficiency. They consider how banks’ supervisory CAMEL ratings are related to their size, their risk-return choice, and their return inefficiency. They find that the risk-return choices of efficient banks are not related to their supervisory rating, while higher-risk choices of inefficient banks are penalized with poorer ratings. Moreover, the risk-return choices of large inefficient banks are held to a stricter standard than smaller banks and large efficient banks.

Two studies by Mester (1991 , 1993 ) investigate differences in scale and scope measures for stock-owned and mutual savings and loans by estimating average cost functions. She finds evidence of agency problems at mutual S&Ls, as evidenced by diseconomies of scope, prior to the industry’s deregulation, and evidence that these agency costs were lessened after the deregulation in the mid-1980s.

Using data for the period 1989–1996, Altunbas, Evans, and Molyneux (2001) estimate separate and common frontiers for three organizational forms in German banking: private commercial, public (government-owned) savings, and mutual cooperative banks. They argue that the same technology of intermediation is available to all so that the choice of technology is a management decision whose efficiency should be compared among all types of forms. The private sector appears to be less profit and cost efficient than the other two sectors. These results are especially clear in the case of the common frontier, but they are also obtained from the estimation of separate frontiers.

10.3.2 Uncovering Evidence of Scale Economies by Accounting for Risk and Capital Structure

Former Federal Reserve Chairman Alan Greenspan (2010) summarized the literature on scale economies in banking: “For years the Federal Reserve had been concerned about the ever-growing size of our largest financial institutions. Federal Reserve research had been unable to find economies of scale in banking beyond a modest size.” (p. 231) But in fact, many investigators, including some at the Fed, have found evidence of scale economies even at the largest financial institutions. This research includes, for example, Hughes et al. (1996) , Berger and Mester (1997) , Hughes and Mester (1998) , Hughes, Mester, and Moon (2001) , Berger and Mester (2003) , Bossone and Lee (2004) , Feng and Serletis (2010) , Wheelock and Wilson (2012) , and Hughes and Mester (2013b) .

The Greenspan observation raises the fundamental question: Are scale economies in banking illusive or elusive? The investment strategies of many of the largest financial institutions constituted ground zero in the recent banking crisis, and their rescue under the TBTF doctrine has prompted some prominent policymakers to call for breaking up the largest banks. For example, Fisher and Rosenblum (2012) assert, “Hordes of Dodd-Frank regulators are not the solution; smaller, less complex banks are. We can select the road to enhanced financial efficiency by breaking up TBTF banks—now.” Hoenig and Morris (2012) call for limiting the government safety net to the core activities of commercial banks including lending, deposit taking, providing liquidity and credit intermediation services, and disallowing banks from doing certain non-core banking activities, including engaging in broker-dealer activities, making markets in derivatives or securities, trading derivatives and securities for their own account or their customers, or sponsoring hedge funds or private equity funds. Tarullo (2011) , however, questions whether breaking up banks would lead to efficiency and suggests there is a tradeoff between concerns for systemic risk and efficiency: “An additional concern would arise if some countries made the tradeoff by limiting the size or configuration of their financial firms for systemic risk reasons at the cost of realizing genuine economies of scope or scale, while other countries did not. In this case, firms from the first group of countries might well be at a competitive disadvantage in the provision of certain cross-border activities.” And Powell (2013) indicates that if the current regulatory reform agenda succeeds in substantially reducing the likelihood of bank failure and minimizing the externalities caused by a large bank failure, then in his view this would be preferable to breaking up the banks, since such a break-up would “likely involve arbitrary judgments, efficiency losses, and a difficult transition.”

While textbooks assert that scale economies characterize banking (e.g., Kohn, 2004 and Saunders and Cornett, 2010 ), these economies elude many empirical studies because the studies generally fail to account for the effects of endogenous risk-taking on banks’ cost as bank size increases. Textbooks cite diversification as one component of the technology that generates scale economies. As discussed above, in Figure 10.1 , the larger bank enjoys a better risk-expected-return tradeoff and chooses its risk exposure on that improved frontier to maximize managerial utility, which is likely associated with expected shareholder value in the absence of severe agency problems. The increase in cost due to the larger output will depend on the investment strategy the larger bank chooses. For example, as a bank scales up its output and moves from point A to point A′, diversification has resulted in lower risk and cost is likely to have increased less than proportionately than the increase in output. If risk-taking is costly, then the investment strategy at point C may result in, say, a proportional increase in cost compared to operating at point A, while the investment strategy at point D may imply a more than proportional increase in cost. Hughes (1999) contends that studies of how cost varies with output that ignore the effects of endogenous risk-taking on cost are likely to identify the technology as constant returns to scale when larger banks tend to produce at point C and as scale diseconomies when larger banks tend to produce at point D. To the extent that larger banks are generally more risky than smaller banks ( Demsetz and Strahan, 1997 ), the naïve econometric investigation of banking cost that ignores endogenous risk-taking is likely to find that larger banks experience constant returns to scale or even scale diseconomies. Hughes, Mester, and Moon (2001) call the effect on cost from moving from point A to point A′, the diversification effect —diversification leads to a decline in risk for the same level of expected profit. They call the effect on cost of moving from point A′, which resulted from better scale-related diversification, to point C or D, the risk-taking effect .

Accounting for endogenous risk-taking—isolating the diversification effect—in estimating scale economies requires controlling for revenue as well as cost. While the traditional cost function does not incorporate any revenue terms, the utility-maximizing cost function incorporates revenue because it is derived from the utility maximizing profit function, conditioned on the output vector and as noted earlier, it reflects bank managers’ choice of risk as well as expected return. In Figure 10.1 , suppose that the smaller bank chooses to produce its output vector with the investment strategy at point A and the large bank chooses to produce its output vector with the strategy at point D. Scale economies estimated in the neighborhood of point A refer to the increase in cost for a small proportional increase in outputs given the investment strategy at point A. If expanded output allows for better diversification that lowers costs for given expected return, then the estimated scale economies would compare cost at point A to cost at point A′. In this way, it would isolate the diversification effect and avoid the bias of measuring scale economies at point D relative to point A. 12

Hughes and Mester (2013b) estimate several traditional cost functions and the risk-return-driven cost function for US bank holding companies in the years 2003, 2007, and 2010. In all three years, estimates derived from the traditional minimum cost functions, which do not take into account the banks’ risk-expected return choice, indicate modest scale economies or in some cases constant returns to scale. In contrast, the utility-maximizing cost function, which takes into account the banks’ risk-expected return choice, yields evidence of large scale economies that increase with the scale of the bank. For example, in 2007, for the smallest banks (with less than $0.8 billion in assets), estimated scale economies is 1.12, which means that a 10% increase in output levels is associated with an 8.8% increase in cost. For the largest banks (with greater than $100 billion in assets), estimated scale economies is 1.34, which means that a 10% increase in output levels is associated with a 7.5% increase in cost.

This evidence of large scale economies at the largest financial institutions suggests that breaking them up into smaller institutions with the goal of reducing the systemic risk they pose would reduce their competitiveness in global financial markets. Using their 2007 estimates, Hughes and Mester (2013a) consider breaking each of the 17 institutions that exceed $100 billion in consolidated assets in half to create 34 banks with total assets equal to those of the 17 larger institutions. Holding product mix constant, that is, assuming the smaller institutions produce the same product mix as the larger ones, their costs are 23% higher. In a similar exercise, Wheelock and Wilson (2012) , who also find large scale economies at banks of all sizes, scale back the four largest US institutions in 2009 to a size of $1 trillion and increase their numbers so that the total assets of the smaller institutions equal those of the larger institutions. They find that the cost of the smaller institutions is approximately 19% higher. These two exercises suggest that breaking up the largest institutions into smaller institutions will limit their global competitiveness and provide incentives to produce their financial services offshore where such limits are not operative.

A related issue in this literature questions whether the estimated scale economies at the largest financial institutions result from cost-of-funds subsidies due to the TBTF doctrine. Davies and Tracey (2014) answer affirmatively; however, Hughes and Mester (2013b) point to flaws in the methods used by Davies and Tracey. Hughes and Mester (2013b) present several pieces of evidence indicating that the large scale economies they find are not driven by a TBTF cost-of-funds subsidy. First, they find large scale economies at small banks in their sample as well as large banks. Second, when they re-estimate their model excluding banks with assets greater than $100 billion, and then calculate scale economies out of sample for the largest banks, their results are unchanged. Finally, they calculate scale economies for the largest bank if they faced the cost-of-funds of smaller banks. Again, their results are unchanged. Hughes and Mester (2013b) conclude that the underlying technology, not TBTF subsidies, account for the scale economies of the largest financial institutions.

10.4 Applications of the Non-Structural Approach

10.4.1 measuring the value of investment opportunities (“charter value”).

The value of a bank’s investment opportunities is often measured by Tobin’s q-ratio; however, in the presence of agency cost the q-ratio captures only the ability of the incumbent managers to exploit these opportunities. Ideally, the value of investment opportunities should be gauged independently of the ability and actions of the current management. Hughes et al. (1997) and Hughes et al. (2003) propose a measure based on fitting a stochastic frontier to the market value of assets as a function of the book value of assets and variables characterizing the market conditions faced by banks. These conditions include a Herfindahl index of market power and the macroeconomic growth rate. The fitted frontier gives the highest potential value of a bank’s assets in the markets in which it operates. Thus, this potential value is conditional on the location of the bank and represents the value the bank would fetch in a competitive auction. Hughes et al. (1997) define this value as the bank’s “charter value”—its value in a competitive auction.

10.4.2 Measuring the Performance of Business and Capital Strategies

Several papers have used the non-structural performance equation to examine the relationship between bank value and bank capital structure. Hughes et al. (1997) regress performance measured by Tobin’s q-ratio and market-value inefficiency on a number of variables characterizing bank production. Calomiris and Nissim (2007) regress the ratio of the market value of equity to its book value on a similar list of variables. De Jonghe and Vander Vennet (2005) apply the market-value frontier of Hughes et al. (1997) to derive a noise-adjusted measure of Tobin’s q, which they use to evaluate how leverage and market power are related to value. All three studies find evidence that banks follow dichotomous strategies for enhancing value as predicted by Marcus (1984) : a lower risk, lower leverage strategy and a higher risk, higher leverage strategy.

10.4.3 Relationship of Ownership Structure to Bank Value

In an influential study, Morck, Shleifer, and Vishny (1988) hypothesized that managerial ownership creates two contrasting incentives: A higher ownership stake, first, better aligns the interests of managers and outside owners and, second, enhances managers’ control over the firm and makes it harder for managers to be ousted when they are not efficient. Measuring performance by Tobin’s q-ratio, these authors provide evidence that the so-called alignment-of-interests effect dominates the entrenchment effect at lower levels of managerial ownership, while the entrenchment effect dominates over a range of higher levels.

Studies that attempt to measure the net effect of the alignment and entrenchment effects on firm valuation cannot identify these effects individually—only their sum in the form of the sign of a regression coefficient or a derivative of a regression equation. Adams and Santos (2006) cleverly isolate the entrenchment effect by considering how the proportion of a bank’s common stock that is controlled but not owned by the bank’s own trust department is statistically related to the bank’s economic performance. The voting rights exercised by management through the trust department enhance management’s control over the bank but do not align their interests with outside shareholders’, since the beneficiaries of the trusts, not the managers, receive the dividends and the capital gains and losses.

Caprio, Laeven, and Levine (2003) study the effect of ownership, shareholder protection laws, and supervisory and regulatory policies on the valuations of banks around the world. The authors construct a database of 244 banks across 44 countries. They measure performance by Tobin’s q-ratio and by the ratio of the market value of equity to the book value of equity. They find evidence that (1) banks in countries with better protection of minority shareholders are more highly valued, (2) bank regulations and supervision have no significant effect on bank value, (3) the degree of cash-flow rights of the largest owner has a significant positive effect on bank value, and (4) an increase in ownership concentration has a larger positive effect on valuation when the legal protection of minority shareholders is weak.

Laeven and Levine (2009) consider a sample of large banks in 48 countries in 2001 and investigate how the cash flow rights of the largest shareholder and various regulatory provisions affect the probability of insolvency. They find that the cash-flow rights of the largest shareholder are positively related to the risk of insolvency. They also find that when there is a shareholder with large cash-flow right, deposit insurance and activity restrictions are associated with increased insolvency risk, but they are uncorrelated with insolvency risk when the bank is widely held.

Hughes et al. (2003) examine US bank holding companies and find evidence of managerial entrenchment among banks with higher levels of insider ownership, more valuable growth opportunities, poorer financial performance, and smaller asset size. When managers are not entrenched, asset acquisitions and sales are associated with reduced market value inefficiency. When managers are entrenched, sales are associated with smaller reductions in inefficiency, while acquisitions are associated with greater inefficiency.

10.4 Conclusions

Great strides have been made in the theory of bank technology in terms of explaining banks’ comparative advantage in producing informationally intensive assets and financial services and in taking, diversifying, and offsetting a variety of risks. Great strides have also been made in explaining sub-par managerial performance in terms of agency theory and in applying these theories to analyze the particular environment of banking. In recent years, the empirical modeling of bank technology and the measurement of bank performance have begun to incorporate these theoretical developments and yield interesting insights that reflect the unique nature and role of banking in modern economies.

This new literature recognizes that the choice of risk influences banks’ production decisions, (including their mix of assets, asset quality, off-balance-sheet hedging activities, capital structure, debt maturity, and resources allocated to risk management), and so, in turn, affects banks’ cost and profitability. Measures of bank performance should take account of this endogeneity. The estimation of structural models that incorporate managerial preferences for expected return and risk have uncovered significant scale economies in banking, a finding that differs from the earlier literature but accords with the consolidation of the banking industry that has been occurring worldwide.

Performance studies based on structural models of managerial utility maximization, as well as those based on non-structural models of bank production, have incorporated variables designed to capture incentive conflicts between managers and outside stakeholders. These studies have shown that factors associated with enhanced market discipline are also associated with improved bank performance and that improved bank performance is not necessarily associated with improved financial stability. The incentive of larger banks to take extra risk to exploit the federal safety net and increase their expected market value may undermine financial stability.

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The authors thank the editors Allen Berger, Phillip Molyneux, and John Wilson for helpful comments. The views expressed here are those of the authors and do not necessarily reflect those of the Federal Reserve Bank of Cleveland or of the Federal Reserve System.

Berlin and Mester (1999) find empirical evidence of an explicit link between banks’ liability structure and their distinctive lending behavior. As discussed in Mester (2007) , relationship lending is associated with lower loan rates, less stringent collateral requirements, a lower likelihood of credit rationing, contractual flexibility, and reduced costs of financial distress for borrowing firms. Banks’ access to core deposits, which are rate inelastic, enable banks to insulate borrowers with whom they have durable relationships from exogenous credit shocks. Mester, Nakamura, and Renault (2007) also find empirical evidence of a synergy between the liability and asset sides of a commercial bank’s balance sheet, showing that information on the cash flows into and out of a borrower’s transactions account can help an intermediary monitor the changing value of collateral that a small-business borrower has posted.

Demirgüç-Kunt, Kane, and Laeven (2007) use a sample of 180 countries to study the external and internal political features that influence the adoption and design of deposit insurance, which, in turn, affects the efficiency of the domestic banking system.

FDIC (2013) summarizes some of the estimates of the subsidy found in the literature.

For expository purposes, in this discussion we are assuming that only the first two moments of the distribution of returns matter for bank production. More generally, however, higher moments, such as skewness and kurtosis, can be expected to influence, for example, calculations of Value at Risk (VaR) and the choice of investment strategies that minimize the probability of financial distress or that exploit the federal safety net. Thus, risk resulting from higher moments likely plays an important role in bank production.

To simplify the discussion, we assume that the smaller bank operates efficiently; therefore point A lies on the frontier rather than beneath it. See Hughes and Mester (2013b) for an analysis of how inefficiency is related to scale economies in banking.

LaPorta, Lopez-de-Silanes, and Shleifer (2002) examine banking systems in 92 countries and find that government ownership is correlated with poorer countries and countries with less developed financial systems, poorer protection of investors’ rights, more government intervention, and poorer performance of institutions. They also find that government ownership is associated with higher cost ratios and wider interest rate margins. Aghion, Alesina, and Trebbi (2007) provide evidence that democracy has a positive impact on productivity growth in more advanced sectors of the economy, possibly by fostering entry and competition.

This framework often guides the choice of outputs and inputs in the bank’s production structure. For example, as discussed in Mester (2008) , the traditional application of efficiency analysis to banking does not allow bank production decisions to affect bank risk, which rules out the possibility that scale—and scope-related improvements in diversification could lower the cost of borrowed funds and induce banks to alter their risk exposure. Also, much of the traditional literature does not account for the bank’s role in producing information about its borrowers in its underwriting decisions when specifying the bank’s outputs and inputs. An exception is Mester (1992) , who directly accounted for banks’ monitoring and screening role by measuring bank output treating loans purchased and loans originated as separate outputs entailing different types of screening, and treating loans held on balance sheet and loans sold as separate outputs entailing different types of monitoring.

See Hughes et al. (2000) for further discussion of this model.

Note that the literature often uses the term “best-practice performance” and sometimes calls it “potential performance.” However, this is somewhat of an abuse of terms since measured best-practice performance does not necessarily represent the best possible practice, but merely the best practice observed among banks in the sample (see Berger and Mester, 1997 , and Mester, 2008 ).

Leibenstein (1966) called such inefficiency, which can result from poor managerial incentives or the failure of the labor market to allocate managers efficiently and to weed out incompetent managers, X-inefficiency . Jensen and Meckling (1976) called such inefficiency agency costs and provided a theoretical model of managerial utility maximization to explain how, when incentives between managers and outside stakeholders are misaligned, managers may trade off the market value of their firm to enjoy more of their own private benefits, such as consuming perquisites, shirking, discriminating prejudicially, and taking too much or too little risk to enhance their control.

Note that the estimated profit (or return) function resembles a multi-factor model where the factors are the explanatory variables in the profit function. The regression coefficients can be interpreted as marginal returns to the explanatory variables, and the standard error of the predicted return, a function of the variance-covariance matrix of the estimated marginal returns, resembles the variance of a portfolio return. Hughes (1999) and Hughes, Mester, and Moon (2001) report that the regression of ln (market value of equity) on ln(E (π i / k i )) and ln (σ i ) for 190 publicly traded bank holding companies has an R-squared of 0.96, which implies that the production-based measures of expected return and risk explain a large part of a bank’s market value. For a regression of the market value of equity on E (π i / k i ) and σ i , Hughes and Mester (2013b) report R-squareds of 0.99, 0.94, and 0.97 for samples of data from 2003, 2007, and 2010, respectively. These values of R-squared are significantly higher than those obtained by regressing the market value on the accounting net income before and after taxes.

Demsetz and Strahan (1997) demonstrate that a larger scale of operations leads to better diversification of banking risk—in particular, bank-specific risk estimated from a multifactor asset pricing model. To isolate this diversification effect, they regress bank-specific risk on asset size and find a small, negative association. When they control for the many ways banks take risk, the relationship between risk and asset size becomes much more negative and statistically significant. They note that isolating the scale-related diversification effect requires controlling for differences in business strategies that influence risk exposure. Finding the effect of scale-related diversification on scale economies requires a similar approach to controling for endogenous risk-taking.

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A Systems View Across Time and Space

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  • Published: 04 March 2022

Enhancing financial performance of the banks: the role of customer response and operations management

  • Osama Mohamed Ahmed Enad   ORCID: orcid.org/0000-0002-9259-9967 1 &
  • Salah Murtada Abdelrahman Gerinda 1  

Journal of Innovation and Entrepreneurship volume  11 , Article number:  28 ( 2022 ) Cite this article

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Metrics details

The current study investigates the relations between the following variables customer response, operations management, and financial performance. The questionnaires were distributed among the board of upper management, middle management, and first-line management in Al-Tadamon Islamic bank in Sudan. Then, the feedbacks were analyzed using SPSS, and the response rate was 77%. The outcomes displayed that, the customer response effect positively operations management and financial performance. Similarly, operations management influences financial performance, but operations management does not mediate the relations between customer response and financial performance.


Customer response is probable to be the main factor affecting the performance of a business, mainly in the stage of “sense and respond” (Jayachandran, 2004 ).

In the current article, the main purpose is to enhance financial performance through customer response and operations management. The study focuses on the impact of customer response on operations management, besides the impact of customer response on financial performance, and the influence of operations management on financial performance. (Jayachandran et al., 2004 ) argues that the customer response refers to the point to which a bank's response to customer needs is speedy. The logic of capability-building is used for understanding that banks can improve the higher order competence of customer response speed to capture market changes quickly, reliability, and improving consumer service. Customer response improves visibility of downstream demand and upstream industrial schedule. Alternatively, customer response speed can to enhance bank’s performance as the bank can enjoy the benefit of rapid response over competitors thanks to additional coordinated and associated responses from banks in its supply chain. In addition, customer integration has an important part in strengthening customer responsiveness: i.e., through customer integration, banks added more customer response speed to respond and enhanced their performance in quickly changing business environment (Chiang et al., 2015 ).

Generating adequate data on effective responses of customers to influence them in dealing with a bank’s branches seems to be crucial for the reason that customer subjectivity of branches influence their customer decisions (Vazifehdust & Khalili, 2017 ) On the other hand, the financial performance of the bank is defined as how well the bank achieves its financial objectives. The financial goals have transmission-accounting variables to gauge the performance of business such, as return on an asset. The return on asset is reasoned as the central metric for evaluating profitability, adding to income on equity, and operating profit margin (Hilal, 2017 ). The previous studies discussed in the literature review have reflected that financial performance is a critical factor for the growth and stability in the banks, and then the banks looking for increasing their financial performance through several factors the current study assumes financial performance influenced by customer response and operations management.

Literature review

  • Financial performance

Performance term has been derived from term ‘performed’ which means ‘to do’, ‘to carry out’ or ‘to render’. Numerous economists consider establishments and organizations, such as an engine in determining economic, social and, political progress. Continuous performance of the organizations is useful in the development and growth of the state. Organizational performance is one of the most significant factors in the management research and debatable the important indicator of organizational performance (Melwani, 2019 ). The financial performance of influence subdivision companies the central objective was to ascertain if any changes happen in financial performance among the different energy manufacturers, he was found that the firms using fossil fuel to produce electricity were performing better (Rai & Prakash, 2019 ). The performance of banks has been of countless interest in academic research. According to (Nyathira 2012 ) bank's performance is an obviously a multidimensional concept including four components: financial and market performance, human resource performance, organizational efficiency, and customer concentrated performance.

To assess the structural performance, one has to study the countryside of the banks and the causes for which its performance is being assessed to properly select the applied measurement or component when determining the performance of those banks (Mugo et al. 2019 ). Using economic ratios, investors can determine the performance of a bank. This is reliable with the statement that the comparison in the form of ratios products statistics that are more objective, for the reason that the performance dimensions can be compared with other banks' or with the prior period. The banks' performance can be seen through a wide range of variables or indicators. Variable or indicator as the source of valuation is the economic reports of the bank concerned. If the performance of the banks growth its value will be higher. According to the Indonesia Organization of Accountants, the banks' performance can be measured by evaluating financial statements. Financial position and performance information in the past often used as a basis for forecasting the financial position and forthcoming performance and other matters that directly attracted the attention of users such as the payment of dividends, wages, the price movement of safeties and the banks' capability to meet its promises as they fall due. Performance is a significant purpose to be accomplished by any banks' everywhere, for the reason that the performance is a reflection of the banks capability to manage and allocate resources (Sintha, 2017 ).

Developing customer value is important to increase financial performance; also Salespeople have an important part in creating customer value through their encounters and strategic relational interactions with clientele (Schwepker & Schultz, 2015 ). In any kind of commercial bank, profitability is a significant factor. Banking firms similarly measure their commercial events undertaken to be familiar with their profitability performance. CAMEL (Capital Adequacy, Asset Quality, Management, Earning and Liquidity) the analysis is used by the banks to analyses economic performance. Banks adopt CAMEL model analysis to evaluate several types of risks and managing them efficiently. Financial ratios have been long practiced by academics to assess the bank’s financial performance. Banks use CAMELS ratings to investigate their financial health and performance (Ali & Dhiman, 2019 ). In today’s marketing era, organizations that successfully achieve their customers enjoy advanced retention stages and better profitability due to improved clients’ loyalty. This is why it is essential to save clients satisfied. Consumer satisfaction is supposed to be tightly linked with understanding customer behavior. Particularly, customer satisfaction is an important component in the formation of customer needs for future buy. In addition, satisfied customers will probably recommend and talk to others about their good capabilities.

The presence of returns in a bank is predictable to get the care of savers and creditors in assessing a management performance of a bank and can forecast bank incomes in the future. Earning is also an element in the financial declarations which are very worried, for the reason that the bank incomes are probable to be a reference for the banks in offering the performance in a bank as a whole in accomplishing business objectives. One way that management does when preparing financial statements that impact the level of return is earnings management which expectation can raise the value of the bank itself (Prihastomo & Khafid, 2018 ).

Financial influence is the amount to which a company entity uses debt capital to finance investment chances offered to the corporate (Gatsi et al. 2013 ) opine that using debt capital efficiently to create revenues on investment indicates the effectiveness of business governance. The application of debt capital by an entity will raise the earnings on equity capital in long term that the income made from its usage is greater than the cost financing the project (Afolabi et al. 2019 ).

The capability to demonstrate the influence of marketing activities on bank financial performance is essential for assessing, justifying, and enhancing the spending of an organization’s marketing resources. This presents itself as a formidable mission when one considers both the variety and possible effect of marketing activity. Marketing administrators face growing pressure to demonstrate the influence of their activities on bank financial performance (Dotson & Allenby, 2010 ). According to (Trivedi, 2015 ) banks must select amongst the revenue streams that enhance stability. The study outcomes find a positive effect of diversification of both non-interest and total income on profitability but a negative influence on stability. In the context of the European banking business, researchers reflect the positive relationship between risk and product diversification which is strong in small banks. With the modern deregulation in the Indian economy, trade banks have arrived into fee-based events alike investment banking, commercial banking, assurance agency, security brokerage, and other nontraditional activities (Malhotra & Sarabhai, 2019 ).

Banks can increase high revenues in the market through valuable knowledge that improves the ratio of benefit to customers (Halim et al. 2016 ) beside the banks those can decrease at low cost these can improve their financial performance (Muhammad & Cavus, 2017 ) Financial success generally dependent on the effectiveness of salesperson (Wong & Tan, 2018 ) Excellent performance not only to the success of bank but also to the good of society by being good business citizens (Yahya & Ha, 2014 ) The main factor may measure performance are profitability and market share various scholars have use measure performance with Profits, growth, and sales (Batra & Dhir, 2019 ). Moreover, banks performance have concentrated on three factors, bank strategy, bank structure or internal environment and, external environment (Pedaste et al. 2015 ) other scholars measure financial performance by rising sales, profit, and financial security (Han et al. 2017 ). Performance measures deferent from stockholder perspective include employees, customers, shareholders, suppliers and, the community Ahmad (Abidin et al. 2017 ). Also, we may use Productivity; it’s the ratio between efficiency and is measured by banks for the same decision-making unit in two different periods (Akbarian, 2020 ). Effective performance measurement should be concentrated on financial and non-financial performance (Ismail et al. 2010 ).

  • Customer response

A Study from marketing literature has classified five key customer response to stock-out including (1) Buy an item at another branch (store switch); (2) Delay buying (purchase future at the same place); (3) Substitute-same brand (for a dissimilar size or type); (4) Substitute different brand (brand switch); (5) Do not buy the item (lost sale). Other than identifying the consumer behaviors following a stock-out (Zhang, 2016 ). In addition, it’s related to Customer sensing, Customer sensing is the continuance of market sensing. (Day, 1994 ) proposes that the market sensing capability is an establishment’s aptitude to be aware of changes in its marketplace and to create perfect responses in their marketing events (Aqmala & Ardyan, 2019 ).

To formulate an effective strategy, Customer Satisfaction, customer response, and Innovation Customer satisfaction has been recognized as a significant part of business strategy and a vital factor of bank long-term profitability and market value in the marketing researches. Satisfied customers and customer responses are an asset of the bank and can bring more profit, more sales, and increase market share to the bank. customer responses lead to customer satisfaction, customer satisfaction defined as a general evaluation of the offer’s performance comparing to the customer’s expectations (Liu, 2019 ) Numerous methods such as implementing lean practices have been found effective in satisfying the customer request and at a similar period preserving or even improving the productivity of the commercial trade. The efficiency of the supply chain must be measured by its responsiveness to customers, (Anand & Grover, 2015 ) which displays his effort that one has to judge and balance upon being client-responsive and being volume concentrated. He concluded that a bank might find an effective customer responsiveness being more critical in increasing the market (such as clean technology markets) condition compared to a mature market. This is in track with the contingency method which proposes a fit between customer responsiveness and the market context (Jermsittiparsert et al. 2019 ).

Good relations with the customers, providing suitable services will make customers select Al-Tadamon Bank on the other Banks (Vahdati & Hadi, 2016 ). Efficient and effective relations with customers will benefit all parties in the long term. (Widana & Wiryono, 2015 ) ender influences have been largely discussed in consumer responses to socially relevant marketing activities in general (Moosmayer, & Fuljahn, 2010 ) In addition to generating direct profits, extended warranties are used as a means to retain customers (Albaum & Wiley, 2010 ) Price competition has become the main means for enterprises to gain a market share, and the competition among enterprises is quite fierce (He & Deng, 2020 ). Understanding what customers value and seeking to deliver that is one cornerstone of effective marketing programs Stephanie (Wen et al. 2016 ), Customers regard esthetical manners as a vital consideration during their purchase decision to enhance trust (Abd Rahim et al., 2011 ). Besides, brand personality may be linked to increasing levels of trust and loyalty (Kim & Zhao, 2014 ) Operation management department plays a significant role in the service sector (Demir, 2019 ).


An appraisal of the literature shows that there is little agreement among researchers on how to measure financial performance. The current study measures financial performance through different indicators include Share of the market, Volume of the sale, Profitability (Majid Elahi, Khaledi & Karimi, profitability, market share, sales operating costs, cash flow, and profit (Ross, 2002 ).

Researchers depend on different items for measuring customer response (Roschk & Hosseinpour, 2020 ) measured customer responses by fives dimensions which are Mood (Activation, Valence, and Control); Evaluations (Product evaluations, Environmental quality, and Shopping satisfaction); Memories (Recall, and Time elusiveness); Intentions (Purchase, and Intention to recommend); Behaviors (Expenditures, and Lingering) .

  • Operations management

Operations Management is a central part of any bank. It’s very important for success in banks. It is a part of management that is a focus on the production of services at the bank (Manikas et al. 2019 ). Operations management practices are meant to develop the effectiveness of production (Battistoni et al., 2013 ). (Dao et al., 2020 ) measured operations management by three dimensions detailed in as following: just in time practices (daily schedule adherence–equipment layout–(JIT) delivery by the supplier–Kanban–setup time reduction); quality management practices (cleanliness and organization–process control–supplier quality management–customer focus–maintenance); infrastructure practices (committed leadership–multi-functional training–employee involvement–information and feedback).


The research conceptual framework.

Few studies had further examined the relationship between customer response and financial performance. This study revealed the effect of the customer response and operation management as determinants on the financial performance.

The integrative model presented in Fig.  1 consists of the following:

figure 1

Source: prepared by researcher, (2020)

Research conceptual framework.

Independent variable was customer response (Roschk & Hosseinpour, 2020 ) measured customer responses by fives dimensions which were Mood, Evaluations, Memories, Intentions,Behaviors. Mediating variable is about operation management which included items that were very important in the current study.

Dependent variable was the financial performance measured by many dimensions, namely, Share of the market, Profitability (Majid, Khaledi & Karimi, sales operating costs, cash flow, and profit (Ross, 2002 ).

In the current study, four main hypotheses were developed to examine the relationships between Customer Responses and Financial Performance; customer responses and operations management; operations management and financial performance; and mediates of operations management between customer responses and financial performance.

Customer response affects financial performance positively

Customer response affects operations management positively

Operations management affects financial performance positively

Operations management mediates the relationship between customer response and financial performance

Research questions:

What is the relationship between customer response and financial performance?

What is the connection between customer response and operatoions management?

What is the link between operations management and financial performance?

Does the operations management mediate the relationship between customer response and financial performance?

Research design

This section is designed to discuss in detail the data collection procedure, sampling technique, questionnaire design and development, administration of questionnaire as well as the data analysis techniques.

Sampling procedure the target population for the current study is the Sudanese Islamic banks. The number of all Sudanese banks was 38 banks according to the central bank of Sudan.

Development of questionnaire according to there are five steps in developing a questionnaire. These steps include: planning what to measure, developing the questionnaire, question—wording, questionnaire layout, pre-testing, correcting problems, and their implementations. These steps are:

Planning what to measure the questions of the study were divided as follows: (1) questions include demographic information and bank information this section includes respondent’s information about gender, age, education, experience years. Besides information about the banks, such as type of activities, job title, number of employees (2) items about the customer response. (3) Items about operational management include significant items of the current study. (4) Items about financial performance include important aspects for the current study. These sections of the study are developed based on past literature.

Formatting of the questionnaire most of the respondents were familiar with Arabic language, since it is a common language in Sudan. Therefore, the questionnaire was translated from English languish to Arabic languish.

Question—wording this step examines whether the phrases are obviously clear to all respondents. Thus it is necessary to use simple terminologies to avoid unclear meaning. It is important to avoid double-barreled and confusing phrases. Besides the phrasing and length of phrases, it is also designed to solicit ideas and answers from target respondents. Simple statements were framed so that the questionnaire could be easily understood. In the process, the questionnaire was reviewed by Academic staff in different universities in Sudan.

Sequence and layout decisions the questionnaire was started with easy phrases flow from general to specific phrases. The difficult phrases were avoided at the beginning. Besides, the attractive layout of the questionnaire was considered for clarity of the aspects presented.

Pre-testing and correcting problems Pilot test was ensured that the phrases were meet the researcher’s prospects with no ambiguities, and clearing the double-barreled phrases. The aim of the pilot test is to remove confusion and checking the reliability of the variables.

Administrative of the field works

According to a report of the central bank of Sudan 2019 ( https://cbos.gov.sd/ar ) the banking system of Sudan consists of 38 banks, namely; Animals Resources Bank, Industrial development Bank, Omdurman National Bank, Financial Investment Bank, Al-Tadamon Islamic Bank, Byblos Bank Africa, National Workers Bank, Faisal Islamic Bank of Sudan, Agricultural Bank of Sudan, Sahel and Sahara Bank for Investment and Trade, Sudanese Egyptian Bank, Country bank, Ivory Bank, Country bank, Commercial Real Estate Bank, Al Baraka Bank of Sudan, The Sudanese French Bank, The Saudi Sudanese Bank, Bright Blue Nile Bank, The Nile Bank, Commercial farm bank, Al-Jazira Sudanese Bank of Jordan, The banking branch of Qatar National Islamic Bank, United Money Bank, Export Development Bank, National Bank of Sudan, Peace Bank, Family Bank, The Savings and Social Development Bank, Bank of Khartoum, The Sudanese Islamic Bank, National Bank of Abu Dhabi, Arab Sudanese Bank, National Bank of Egypt (Khartoum), Qatar Islamic Bank, Abu Dhabi Islamic Bank, Gulf bank, Katelem Agricultural Bank. (The central bank of Sudan, 2019) with different activities and different sizes. The current study focuses on the Islamic banks, namely (Al-Tadamon Islamic Bank, The Sudanese Islamic Bank, Qatar Islamic Bank, Abu Dhabi Islamic Bank, and Faisal Islamic Bank) the 73 questionnaires were drawn exactly from the middle and top management in Al-Tadamon Islamic Bank and the study used probability sampling technique exactly random sampling.

Reliability analysis

Reliability is a measurement of the degree of consistency between multiple measurements of variables (Hair, 2010 ) for testing reliability, this study has used Cronbach's alpha as a diagnostic measure, which assesses the consistency of the entire scale, since being the most widely used measure (Sharma, 2000 ). According to (Hair, 2010 ), the lowest limit for Cronbach's alpha is 0.70, although it may decrease to 0.60 in exploratory research. While (Roberts, 1980 ) considered Cronbach's alpha values greater than 0.60 are to be taken as reliable. The results of the reliability analysis summarized in Table 1 confirm that all scales display a satisfactory level of reliability (Cronbach's alpha exceed the minimum value of (0.676) as a conclusion, the measures which were used have an acceptable levels of reliability (Tables 2 , 3 , 4 , 5 , 6 , 7 ).

Hypothesis testing in Table 7 shows the result from hierarchical regression between Customer response and financial performance ( β  = 0. 59; F change = 5.091), hence H1 (Customer response and financial management) were accepted (Table 7 ).

Hypothesis testing in Table 8 shows the result from hierarchical regression between Customer response and operations management ( β  = 0.562; F change = 0.341), hence H2 (Customer response and operational management) were accepted.

Multiple regressions: operational management and financial management the study exams the link between operational management and financial management the findings show in Table 9 that operational management influenced financial management ( β  = 000; F change = 36.731).

Table 10 testing H4 (operations management mediates the relationship between customer response and financial performance). The findings presented in Table 10 reflect that, the operational management partially mediates the relationship between customer responses and financial performance. To test these hypotheses, this study was applied a three-step hierarchical regression recommended by (Baron & Kenny, 1986 ). First step, the independent variable must affect the dependent variable significantly (ß1 must be significant). Second step, the independent variable should affect the mediating variable (ß2 must be significant). Third step, mediating variable must influence the dependent variable significantly (ß3 must be significant). On the other hand, to establish whether mediator is fully or partial mediating the relationship between the independent variable and dependent variable, the impact of independent variable on dependent variable controlling for mediating variable should be zero or ß4 is not significant in fully mediator, while partial mediator exists once ß4 is significant but reduced. To establish that the mediator ( M ) is fully mediates the relationship between the initial variable ( X ) and outcome variable ( Z ), the impact of X on Z controlling for M should be zero or β 4 is not significant, whereas partially, mediator exists when β 4 is significant. As shown in Fig.  2 .

figure 2

Source: Baron and Kenny ( 1986 )

Mediating structure.

The summary of results

This study aims to examine the relationship of variables; customer response and financial performance; customer response and operations management; operations management and financial performance; and mediating effects of operations management between customer response and financial performance.

The results of the study show that customer responses have a positive relationship with financial performance; (hypothesis one supported) also the result reflects that customer responses connected positively with operations management (hypothesis 2 supported), besides the positive correlation between operations management and financial performance (hypothesis 3 supported), the last result for the mediating effect and the outcome shows that operations management partially mediate the relation between customer response and financial performance (hypothesis 4 partially supported).

The study aims to better understanding the relations between variables; Customer response, and financial performance, customer response and operations management, besides the relation of the operations management and financial performance. First, our result indicates the positive relationship between customer response and financial performance that means good customer response leads to high financial performance. The finding consistent with the conclusions of (Schwepker & Schultz, 2015 ) also consistent of (Paulo & Pereira, 2006 ) findings. Besides the agreed with (Hwang et al. 2012 ) their result indicated that crowding directly affected approach-avoidance responses and performance, Also consistent with (Jones et al., 2010 ) and their result Affective commitment was a significant and positive predictor of all three customer responses dimensions, Also the result similar to (Brunner et al., 2019 ), and their outcome customer responses and brand response enhancing performance, agreed with (Shin& Larson, 2020 ) and their result customer response has an influence on performance and perceived trustworthiness of the firm, besides the similarity with (Wang & Beise-Zee, 2013 ) their outcome reflects that, service responses positive effects on customer evaluations of service performance.

The result also similar to (Roschk & Hosseinpour, 2020 ) their result indicates to influence of customer response variables: Mood (Activation, Valence & Control); Evaluations (Product evaluations, Environmental quality, and Shopping satisfaction); Memories (Recall, and Time elusiveness); Intentions (Purchase, and Intention to recommend); Behaviors (Expenditures, and Lingering) on performance. In addition (Leaniz et al. 2018) reflected that customer perception of green practices positively affect the green images of companies, which also positively affects customer behavioral, and performance.

Second, our results show the positive relationship between customer response and operational management, there are no studies connect directly between customer response and operational management (et al., 2004) argued that a firm’s customer response speed is increasingly critical for sustained success (Chianga et al., 2015 ).

Third, our analyses identify a surprising finding, where operational management has a positive relationship with financial performance. There is a few researchers associate indirectly between operational management and financial performance, this finding is consistent with the conclusions of (Perdikaki et al., 2015 ) Also Omar (Masood & Javaria, 2019 ) study shown a positive association between Implementation management and financial performance of the Takaful Industry. In addition, (et al., 2016) found that sales is positively related to higher operational, and profit (Rangarajana et al., 2018 ) similarly (Dao et al. 2020 ) revealed the positive effect of operations management variables (Just in time practices, quality management practices, and infrastructure practices) on bank performance. Fourth, the mediation effect the operational management was partially mediated the customer response and financial performance. The current study introduced new relations between various variables besides the little of previous studies in this field.


The current study is an attempt to explain the importance of customer response among the bank's administrator’s concepts. Alongside this, the study investigated the correlation between variables; customer responses and financial performance, customer responses, and operations management, operations management, and financial performance, besides the mediating effect of operations management on the relations between customer response and financial performance. The sample size of the study was 73 questionnaires delivered hand by hand to managers in the top and middle management. Questionnaire items were shown as following; customer responses included three items, operations managements included five items, and financial performance included six items. The attention of customer response affected positively on financial performance and operations management. Operations management related to financial performance positively. Focusing on the outcomes of study financial performance affected by customer response and operations management then banks administrations should be careful about customer response and operations management.

The results provided empirical support for the theoretical framework, reflected the fact that the study had adequately addressed the questions of the study. The study also highlighted the implication, limitations, and suggestions for future research.

Managerial implications

The outcomes of the current study will motivate top management in the business organization to build strong relations with the variables of the study (Customer response and financial performance, customer response and operational management, besides the relation of the operational management and financial performance) the current study reflected that the attention to customer response increase market share, enhancing profitability, and increase sales. In addition, financial performance can be increased through effective operational management. Thus, the current study encouraged Sudanese Islamic Banks managers to focus on customer response and operational management, because they are important factors for improving financial performance. This study also contributes to managerial practices in all sizes of the banks, as shown in the following: for the big size of the banks; attention to customer response provide an external environment and support them with new competitive advantage besides the analytical tools needed for strategic decision support, then expand their activities, achieve their financial objectives, improve their competitive position, and enhancing their economic and non-economic performance. For the medium size of the banks; increasing financial performance through attention to customer response and operational management reinforce them for facing their threats, help them seizing their opportunities, then expanding their activities. Finally, for the small size of the banks; attention to customer response makes them reducing weak points, providing strengthens points, and foster them for facing the external environment.

Limitations of the study

The study focused the on sector of the banks specifically Islamic banks in Sudan. Therefore, it is unacceptable to generalize the results of different businesses and different countries. The study not covered all services sectors in the business organization just concentrated on the services at the banks then it’s not covered the organization which produced tangible products. In addition, our theoretical framework was limited framework has to considered a summary of the most commonly studied variables, further studies that can increase variables such as non-financial performance and marketing performance besides moderating variables can be entered and simultaneously increase the elements of the variables. The sample size was limited because of the difficulties of distribution questionnaires.

Suggestions for future studies

Depending on the above limitations of the study, the current study introduced a number of suggestions for further studies. Future researches can repeat this study with increasing sample size and different contexts, such as different sectors or dissimilar states. In addition, the model or framework of the study was simple and limited, further researches can enter several variables, such as moderating variables or increase the aspects of the current variables.

Availability of data and materials

The data available in Saudi electronic library, about the present article data it will be available in the journal web site after publication.


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First, great thanks are humbly extended to Allah almighty who give me strength and endurance to complete this study. Second, I express my thanks and appreciation to all my family, specially father, mother, Brothers and sisters. Finally, but not least I’m thankful to all, colleagues and friends who help me to complete my study at the university a memorable and valuable experience to all of them.

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Enad, O.M.A., Gerinda, S.M.A. Enhancing financial performance of the banks: the role of customer response and operations management. J Innov Entrep 11 , 28 (2022). https://doi.org/10.1186/s13731-022-00211-w

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Financial Performance Analysis of Private Sector Banks in India: An EAGLE Model Approach

Profile image of Jay Sathavara

2021, International Journal of Commerce and Management Studies

Healthy economy is depend upon financial service sector of a nation. Sheduled commercial banks occupy an important place in this sector by lending funds and creating saving habits of people. The aim of this study to evaluate financial performance of selected private sector banks of india by using EAGLE model. Private sector banks such as Axis Bank, HDFC Bank, ICICI Bank, Indusind Bank and Kotak Mahindra Bank was selected on the basis of market capitalisation. To achive this objective financial data of selected sample was retrived from bank's annual reports for the period from 2009-10 to 2018-19. Ranking the banks with the help of EAGLE model and ANOVA test was used to measure variance amongs the financial variables of a banks. The finding of this study shows that HDFC bank secured first rank in terms of earning, assets, liquidy and equity parameters where as kotak mahindra bank also secured first rank in terms of earning, growth and equity. Indusind bank also secured first rank in term of growth. ICICI bank earned last rank in terms of earing, assets and growth overall HDFC bank secured first rank followed by Kotak mahindra bank, Indusind Bank, Axis bank and ICICI Bank. All the selected private sector banks has been maintained the capital adequacy ratio as per RBI norms. The tabulated values of all the variables are less than significant value 0.05 at 95% confidence level so null hypothesis of variables of this study are rejected, that means there are statistically significant difference in all the selected samples.

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Impact of the quality of credit risk management practices on financial performance of commercial banks in Tanzania

  • Published: 02 March 2024
  • Volume 4 , article number  38 , ( 2024 )

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  • Grace Isidor Temba   ORCID: orcid.org/0000-0002-2281-0448 1 ,
  • Pendo Shukrani Kasoga   ORCID: orcid.org/0000-0001-6634-3020 1 &
  • Chirongo Moses Keregero 1  

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Commercial banks’ roles in economic development make it paramount for their sustainable financial performance, hence a need for effective credit risk management as credits are the main source of revenue creation, yet are the main threat to the bank’s asset quality and, if not effectively managed, will jeopardize performance. The study investigated the influence of the quality of credit risk management practices on the financial performance of commercial banks in Tanzania. Balanced panel data of fifteen commercial banks with 255 observations from 2003 to 2019 have been used for the analysis. Results revealed that risk assessment and approval, the quality of credit processes and controls, adequacy of the recovery process, and risk supervision & monitoring positively influence banks’ performance through their capital adequacy, efficient use of equity and asset quality, respectively. Further, banks’ earning ability and liquidity are negatively affected by risk assessment and approval as well as risk supervision and monitoring. The study recommends that credit risk management practices be central to bank operations due to their positive effect on financial performance. However, caution should be taken and strike a balance on mix and concertation in the facilitation of all studied variables, as credit risk assessment & approval and credit risk monitoring and supervision negatively affect banks’ liquidity.

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Authors acknowledge the public relations / legal officers of TPB Bank Plc, DCB Commercial Bank Plc, Diamond Trust Bank (Tanzania) Ltd and Akiba Commercial Bank Plc, who made efforts to provide hard-bound books of annual reports for a few years which were missing in their banks’ websites.

The authors did not receive support from any organization for the submitted work. Further, all authors certify that they have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript.

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Department of Accounting and Finance, The University of Dodoma, Dodoma, Tanzania

Grace Isidor Temba, Pendo Shukrani Kasoga & Chirongo Moses Keregero

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GIT conceptualized the introduction, reviewed the literature, developed study hypotheses, collected and analyzed data, discussed findings, drew the conclusion, and was a major contributor to writing the manuscript. PSK sharpened the conceptualized introduction, hypotheses, findings discussion and conclusion. CMK worked on the grammar issues and manuscript editing.

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Correspondence to Grace Isidor Temba .

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Financial/Non-Financial Interests: All authors have no relevant financial or non-financial interests to disclose. Affiliations: All authors certify that they have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript. Editorial Board Members and Editors: All authors certify that they make no part in the editorial part and/or Editors in which this manuscript will be processed/edited/published. Employment: This research work has not been conducted for any financial gain to any organization. The work is purely for academic requirements. Nevertheless, none of the authors is employed by any institution whose data were used for this research work.

Ethical approval

This research work was approved by the Vice Chancellor of the University of Dodoma through the Directorate of Research, Publication and Consultancy ([email protected]) of the University of Dodoma—Tanzania as it is part of the requirement for the attainment of PhD studies by the corresponding Author pursued at the University of Dodoma. This research used published secondary data of Institutions (commercial banks), Audited and Published under the Tanzania Central Bank—Bank of Tanzania requirements. No part of the collected and utilized information was obtained from human participants, nor did the research involve human participants.

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Temba, G.I., Kasoga, P.S. & Keregero, C.M. Impact of the quality of credit risk management practices on financial performance of commercial banks in Tanzania. SN Bus Econ 4 , 38 (2024). https://doi.org/10.1007/s43546-024-00636-3

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DOI : https://doi.org/10.1007/s43546-024-00636-3

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    In section 2, we explain the literature review detailed about the accounting and financial performance of banking sector. Section 3 applies the research problem, objectives and detailed methodology. Section 4 concludes the insights and result for all financial ratios has been applied to measure the performance of banks.

  11. A Review of the Research on Financial Performance and Its ...

    The analysis of the entire sample of articles enabled us to identify the following aspects: 36 articles were written by foreign authors and 9 by Romanian authors; 25 articles presented analyses of samples comprising less than 120 companies, and 15 contain empirical research on samples comprising between 121 and 500 companies; five articles had samples of 1000 and 5025 companies, respectively ...

  12. Cooperative financial institutions: A review of the literature

    Cooperative financial institutions. Literature review. 1. Introduction. Cooperative financial institutions comprise a variety of member-owned financial intermediaries variously referred to as credit unions/caisse populaires, savings and credit cooperatives, cooperative banks and Shinkin Banks. Credit unions/caisse populaires have a strong ...

  13. A Survey Of Literature Review On Bank Preformance

    Nina Siniţîn, 2021. " A Survey Of Literature Review On Bank Preformance ," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1 (1), pages 235-241, July. Downloadable! This study analyses existing literature review studies on banking sector performance. Specially, this research aim is to identify topics of ...

  14. Empirical studies on the performance of banks: A systemic literature

    term financial performance of banks and Z-score measures the long-term performance of banks. Therefore, we are of the view that the performance of banks h as to be measured considering the risk

  15. Enhancing financial performance of the banks: the role of customer

    The current study investigates the relations between the following variables customer response, operations management, and financial performance. The questionnaires were distributed among the board of upper management, middle management, and first-line management in Al-Tadamon Islamic bank in Sudan. Then, the feedbacks were analyzed using SPSS, and the response rate was 77%. The outcomes ...

  16. PDF Financial Performance Analysis of Commercial Banks

    REVIEW OF LITERATURE 16-30 2.1 Theoritical Review 16 ... 2.1.3 Financial performance analysis of bank 20 2.1.4 Techniques of financial analysis 21 2.1.5 Types of ratio analysis 21 2.2 Review of Books 26 2.3 Review of journal and articles 27 ...

  17. PDF A Study on Financial Performance Analysis of Selected Public ...

    available for use as academic literature by other students and researchers on a global and local scale. Policymakers will have information to aid them in developing policies affecting the banking industry. Additionally, the general public will be educated about the numerous aspects that contribute to the analysis of banks' financial performance.

  18. PDF Financial Performance Analysis of Commercial Banks in Nepal

    FINANCIAL PERFORMANCE ANALYSIS OF COMMERCIAL BANKS IN NEPAL ... CHAPTER II: REVIEW OF LITERATURE 9-29 ... 19 2.1.9 User of Financial Analysis 20 2.2 Review of Previous Related Study 21 2.3 Research Gap 29 CHAPTER III: METHODOLOGY 30-35 3.1 Research Design 30 ...

  19. Review of Literature

    Abstract. The literature on bank performance is indeed voluminous. Here we try to give some studies on performance of banks in India which employ both traditional and DEA methods. Again for the studies pertaining to the window DEA-based banking efficiency analysis, we review only the major studies outside the country as window-DEA-based banking ...


    Priyangajha (2018) "Analyzing Financial Performance (2011-18) of Public Sector Banks (PNB) and Private Sector Banks (ICICI) in India". ICTACT Journal of Management StudiesAugust 2018 vol.04, Issue ...

  21. Financial Performance Analysis of Private Sector Banks in India: An

    The sector banks from 2012-2014 with CAMEL model with the financial crisis of US banks in 2008-09 and failure of large t test, rank test and anova test as a statastical tools and 1 Page International Journal of Commerce and Management Studies (IJCAMS) Peer Reviewed, Indexed Journal, ISSN 2456-3684 Vol.6, No.3, 2021, www.ijcams.com indicated ...

  22. Performance analysis of non-banking finance companies using ...

    2.1 Relevant literature review of NBFCs. While there is no lack of literature for DEA in banking, the same cannot be said about the NBFC's. ... Shankarii, S. & Muthukumar, J. (2017). A comparative study of financial performance analysis on non banking financial companies. International Journal of Scientific Research, 6(7), 291-293.


    The main purpose of this study is to study the financial performance of ICICI bank using camel analysis. This study is analytical in nature. Secondary Data is collected from annual reports, books ...

  24. Impact of the quality of credit risk management practices on financial

    The study investigated the influence of the quality of credit risk management practices on the financial performance of commercial banks in Tanzania. Balanced panel data of fifteen commercial banks with 255 observations from 2003 to 2019 have been used for the analysis. ... Literature review and hypothesis development are presented in the next ...