What are the possible future research directions for bank’s credit risk assessment research? A systematic review of literature

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  • Published: 11 March 2018
  • Volume 15 , pages 743–759, ( 2018 )

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  • Sandar Win   ORCID: orcid.org/0000-0003-3155-9950 1  

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Banking prudence and efficiency to manage their risks in different business cycle and environment would help to alleviate crises and losses. Hence, the effective assessment of credit risk is an essential component of a comprehensive technique to credit risk assessment and critical to the long-run of not only banking institutions but also the economy as a whole. Therefore, it has received a great interest from scholars across finance and economics to investigate such assessments by banks in different countries using diverse theoretical underpinnings and methodologies. Hence, this paper is developed to review analytical conceptualisations of credit risks assessments that have been developed in the academic literature. By means of a systematic review, it provides a comprehensive analysis that encompasses approaches used in research papers. There has been no prior review on analytical conceptualisations in this area. Moreover, this review is done in a systematic manner, i.e. categorising journal articles into different categories such as purposes, perspectives and methodologies through a transparent and thorough process. Thus, it will be able to provide an objective review. Finally, the paper will outline the evolution of methodologies and theoretical underpinnings in credit risk management research and a landscape for possible future research directions.

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1 Introduction

‘Over the past two decades, the financial world has evolved from [a] return driven to a genuine risk management industry. The term risk management certainly is not confined to what is best denoted with risk control: Measuring risks, setting limits and ensuring adherence to these limits. This is necessarily part of the whole process of risk-return optimisation …. Risk management … also compromises the decision making process of considering risk-return trade-offs and optimising stakeholders’ targets …‘. (Kocken 2006 )

The basic risk factors relevant to financial institutions can be broadly classified into market risk, credit risk, liquidity risk, underwriting risk, and operational risk. Therefore, the definition for ‘risk management’ is broad. Banks are exposed to credit risks more than any other risks mentioned above. Hence, this paper will only focus on Credit Risk Management (CRM) and Credit Risk Assessments (CRA).

Credit risk can simply be defined as the prospective that a bank borrower or counterparty will fail to meet its obligations in accordance with agreed terms and conditions. The failure to manage credit risks properly could result in more than direct accounting loss. It encompasses opportunity costs, transaction costs and expenses associated with non-performing asset over and above the accounting loss. It can affect banks’ portfolio, thereby attracting liquidity risk and in the worst cases, it can have negative effects on both financial industries and economies. Hence, CRM is understood as a process that starts from regulatory level, second, from banks’ strategic levels, then continues to the operational levels. By referring back to Horneff’s ( 2006 ) statement as provided above, this indicates that every level comprises of decision making process, considering risk-return trade-offs and optimising stakeholders’ targets.

In addition, with the repeated banking crises over the years due to poor CRM by banks and other financial institutions, this area has received a lot of attention from academics and many research papers have been published in this area. However, the conceptions of risk by these researchers can differ significantly. The bulk of investment-banking oriented body of literature on risk management usually defines risk in an objective way not differentiating according to the needs of different investors or stakeholders. On the other hand, there are researchers who consider it to be ‘relative’ rather than an absolute concept (Balzer 1994 ). This has caused two main concerns. Firstly, due to such differences, there are inconsistencies in conceptualisations of CRA. This led to an impediment of a precise academic debate in the field, thereby; hindering discovery of possible solutions for CRM. Secondly, the extent of such conceptualisations fails to incorporate the current needs to accommodate the perspectives of a wide range of actors (e.g. decision making at different institutional levels). More importantly, a lack of a review on conceptualisations of CRA provides the fact that there is a scope of development in this field of research.

Therefore, the purpose of this paper is to illustrate, to compare, and to review analytical conceptualisations of CRA along with scope of study, analytical domains and methodologies that have been developed in the academic literature. As my aim is to provide a comprehensive and systematic review, the analysis encompasses published research papers from journals. In summary, this study will contribute to banking literature, especially CRA research. As this is a systematic review conducted according to the guidelines by Tranfield et al. ( 2003 ), the review follows a transparent and thorough process aimed at enhancing scientific rigor and at developing a reliable stock of knowledge.

The remainder of this paper is organised as follows: Section 2 discusses the concept of ‘rationality’ in CRM literature. The research design is outlined in Section 3 , followed by the results of our exploratory study. In section 5 , analysis and evaluation of analytical conceptualisations of CRA will be provided.

2 Rationality assumptions in CRM literature

The term rationality is defined by Bazerman and Messick ( 1998 , p. 478) as.

‘…the decision-making process that is logically expected to deal to the optimal result given an accurate assessment of the decision-makers’ values and risk preferences’.

In other words, decision makers who are rational will arrive at objective and logical judgements. In fact, the costs associated with gathering complete information is high or impossible, making rational decision is implausible. Moreover, rational decisions tend to be made based on unrealistic assumptions (Robbins and Coulter 2011 ):

the problem is clear and unambiguous where decision makers have complete information;

the decision is single, well-defined goal that the decision maker is trying to achieve and there is no conflict over the goal;

the decision maker can identify relevant criteria, lists all the viable alternatives, and is aware of all possible consequences of each alternative;

the decision maker can obtain full information about the criteria and alternatives because it is assumed to that there are no time or cost constraints; and

the rational decision maker always chooses the alternative that will yield the maximum payoff

In CRA, it is not about solving a problem but contemplating whether to take an opportunity for return to realise in the future from investment. These opportunities come with uncertainties and it is impossible for banks to have complete information. Similarly, the full information about the consequences, in this case, borrowers engaging in risky activities cannot be obtained. Herne ( 2011 ) finds some evidence showing that individual choices disappear when individuals have an opportunity to learn and correct their choices to be more in line with the standard utility model depending on the situation where decision making takes place, thereby concluding that different institutional structure affect such differing preferences. Similarly, the studies also find that the standard utility model works well in certain types of competitive markets but not in other institutional environments. These are the results of individuals’ limited cognitive capabilities, information processing capacity, time and cost constraints on decision makers to obtain complete information. In other words, optimal ‘risk perception’ is not attainable. Thus, the term ‘bounded rationality’ is created by Simon ( 1976 , p.82) stating that

‘The human being striving for rationality and restricted within the limits of his knowledge has developed some working procedures that partially overcome these difficulties. These procedures consist in assuming that he can isolate from the rest of the world a closed system containing a limited number of variables and a limited range of consequences’

He further asserts that due to these limitations, individuals construct simplified models of the real world in order to deal with it. He refers to it as picking a course of action that is satisfactory, ‘satisficing’ or ‘good enough’ under circumstances. Applying his views on banks’ CRA context, collaterals, interest rates, for example, are used by banks to simplify complicated issues of deciding whether to approve or reject loan applications. In developed countries, the over reliance on credit rating agencies is also the result of banks’ attempts to simplify complex processes. Similar to Herne ( 2011 ), Simon ( 1976 ) also states that it is impossible for individuals to analyse logically and dispassionately to make the best possible decision as they are constrained within the realm of cultural, organisational or their own values.

Banking is one of the most regulated industries in the world, among various regulatory measures, the regulation of bank capital is crucial due to the important roles it plays in banks’ soundness and risk taking behaviour and its influence on the competitiveness of banks (Zhu 2008 ). Therefore, different types of regulatory frameworks have been introduced for internationally active banks to follow. For instance, at the international level, in 1988, Basel Committee on Banking Supervision (BCBS) formed Basel Accord I. According to this, bank loans of different risk have same weight which allows banks to swap low risk assets with high risk ones. In other words, this Basel Accord allows regulatory arbitrage (Zhu 2008 ). Then, in 2004, Basel II which is a revised version of the former one was released. It allows banks to compute the capital requirements for managing credit risks, standardised approach, Foundation Internal Ratings-Based approach (FIRB) and Internal Ratings-Based approach (IRB). In order to use the latter approaches, it needs approvals from regulatory authorities (regulatory level) and is costly; therefore, banks opt to use the former approach which relies on external rating agencies. In this case, the effects of institutions and environments on credit risk measurements come from two directions, one from external rating agencies and another from the banks themselves. During the times of economic and financial crises, these rating agencies downgrade credit risks including sovereign debts. At the same time, banks become more cautious in lending which creates two directional influences in changing banks’ credit risks perceptions.

In addition, the effects of those institutional constraints cannot be ignored if we take into account of countries that have implemented Basel Accords and those that have not. Even those countries that have implemented the same Basel Accord also tend to have different approaches in their lending practices, for instance UK and Germany (Lane and Quack 2001 ). If the decision makings was rational, we would not have financial crises and banks would not be accused of irresponsible lending. Therefore, the statement which states that rationality exists becomes questionable.

Similar to other decision making research papers, researchers of banking and finance communities are interested in understanding why people make the choices and judgments that they do, for example, the reasons for inflicting higher interest rates on one group of borrowers and lower interest on the another, and why banks refuse to lend to small businesses. Though banks’ CRA process has been discussed in the previous section, the question of whether decision makers are rational, that is what makes to choose one alternative over another still remains unanswered. Many researchers have different opinions on whether to conduct research based on ‘rationality’ assumptions. Hence, an exploratory study of previous literature is conducted to learn about analytical conceptualisations of CRA in banking literature.

3 Research design

Due to the origins of credit risk, I focused primarily on banking academics and literature in order to contribute to the field by systematically reviewing the relevant literature. Three primary sources that I used to collect journal articles are EBSCO/Business Source Complete, PROQUEST and Emerald. This review followed the guidelines proposed by Tranfield et al. ( 2003 ). Prior to conducting the review, a protocol was composed.

Due to the vast amount of literature in this area and based on the theoretical underpinnings, literature gaps are divided into two, one based on the perspectives used by the researchers to study risk perceptions and banks’ lending, i.e. where CRA is viewed as either rationalised or institutionalised; and analytical domains, where different levels of factors affecting lending decisions are researched upon. The summary can be presented as in Fig.  1 .

Graphical presentation of literature gaps

4.1 Perspectives

Research on risk in decision making has been dominated by statistical estimations which are often inadequate to alleviate people’s attitudes toward risks (Renn and Swaton 1984 ). Such methodologies are designed to be objective. However, they lack interpretability of results as they do not take into account of public perceptions and social effects. Since risk is not an “objective” fact in the business environment (Luhmann 1993 ), studying risk perceptions by banks using probability calculus will not allow us to understand the factors influencing banks’ lending behaviour (Lane and Quack 2001 ). In general, this type of methodology fails to include bounded rationality and subjective rationality in various estimations process. Thompson ( 1967 ) supports this fact by stating that uncertainties and risk pose major challenges to rationality which is manifested itself in an individual’s perception. To bridge this gap, many researchers have taken different perspectives such as sociological and psychological to study risk in different areas of research such as in foreign direct investment (Francis et al. 2009 ), information systems (Tsohou et al. 1993 ), organisational communication (Lammers and Barbour 2006 ) and so on. According to Renn and Swaton ( 1984 ), these perspectives of risk in decision making are divided into four categories:

Classical Decision Analysis – focuses on rationality of decision making process and what motivational and cognitive biases are incorporated to optimise our own judgement.

Psychological Decision Theory – emphasises individuals’ processes of information about risk and logical structure in arriving at an overall judgement.

Social-psychological Judgement and Attitude Theory – concentrates on the interaction between social values and personal judgement.

Sociological Theories and Policy Analysis – investigates the social goals, values, or motives that drive persons and social groups to come to final judgement.

4.1.1 Classical decision theory

Classical decision theory assumes that individuals are rational decision makers and optimise their judgements through formal axioms. Grandori ( 1984 ) asserts that classical decision theory incorporates an optimising model. In other words, these theories match the decision processes with a normative model of rational reasoning thereby maximising utility of individuals or groups (Renn and Swaton 1984 ). Oliveira ( 2007 ) used the term ‘normative’ or ‘rational’ decision theories to describe this process. In rational decision making models, a number of possible alternatives from different scenarios are analysed by decision makers before making a final choice which would have the highest probability of outcome in the best expected scenario (Oliveira 2007 ). Therefore, most of the research papers using classical decision or normative theories seek to understand how decision makers solve problems through identifying different alternatives. Banks’ decision making processes have been studied by economists emphasising ‘markets with imperfect information’, ‘bounded rationality of decision-makers’, ‘moral hazard’ and ‘adverse selection’ (Stiglitz and Weiss 1981 ). Some of the economic theories that are used to employ rational decision making models are expected utility theory and game theory.

Economic theory, for example, limits its attention to goods, bonds and money as long as the institutionalisation of saving and investment is confined to the monetary system (Gurley and Shaw 1955 ). Its methodology involves rational decision making models that follow three steps process of (1) analysing the feasibility of the alternative, (2) pondering the desirability of alternative, and (3) choosing the best alternative by combining both desirability and feasibility (Rubinstein 1998 ). Grandori ( 1984 ) states that in the economic theory of competitive decision, the payoff structure is considered as ‘known’ until a system of information, the price system is there to reflect the influence of all the relevant factors. In reality, competitive equilibrium cannot be achieved as said in economic theory at least in banks’ lending because of the use of non-interest item, for instance, collateral is used to offset asymmetry of information existing between the lender and borrower. Moreover, the lenders are unaware of the default probabilities of the borrowers, therefore, are unable to rank and choose the feasible and desirable alternatives. If the lenders were able to rank default probabilities of borrowers using their credit ratings and collaterals, nonetheless, the information is ex-ante and cannot determine the occurrence of moral hazard.

Economic theory has been used to study banks’ lending by Stiglitz and Weiss ( 1981 ). Their study has been the most influential in banks’ lending studies (Wette 1983 ; Besankor and Thakor 1987 ; De Meza and Webb 1987 ; Arnold and Rile 2009 ; Su 2010 ). Their main idea is that in a competitive equilibrium, a loan market is characterised by credit rationing. In their model, banks categorise borrowers according to the expected return of projects. It shows that if a bank increases its interest rates charged on borrowers, it will suffer from adverse selection as only risky borrowers are willing to borrow at such high rate and cause moral hazard as they would choose riskier projects. Therefore, interest rate being charged on the borrower is sensitive to banks’ risk ranking of them according to the repayment probabilities. They also examined the role of collaterals but only for risk-averse borrowers. This argument has been further extended by Wette ( 1983 ), however, only for risk-neutral borrowers and focuses on collateral requirement while interest rate is held fixed. Thus, in these types of models of studying banks’ lending behaviour, borrowers’ risk classes are first sorted. These assumptions and results led to conclude that lower quality borrowers could only be attracted at higher interest rates and collateral requirements. In these types of study, different decision makers would arrive at the same conclusion which in reality is not the case, because their experiences, intuitions and the institutional environments that they operate in also have significant influences on how they make judgments.

It is true that classical decision theory and rational decision making models are the most reliable and robust for describing and predicting aggregate-level outcomes that are the result of individual level decisions especially with the case in situations where monetary markets, where information regarding preferences are readily available (Cook et al. 1990 ). North ( 1990 , p.11) also argues that classical theories are compatible with and have made major contributions to market analyses in developed countries but fail to characterise underdeveloped markets.

Other limitations also exist. Firstly, they assume that a clear distinction can be made between high and low risk borrowers. Secondly, almost all the research papers using classical decision theory to study decision making lack empirical testing of the underlying assumptions. Most importantly, the simplifying approach of classical decision theory does not capture the complexities of national and organisational environmental effects on the variations in risk assessments. Thus, classical decision theories with over emphasis on an individual level of analysis should be avoided.

4.1.2 Psychological decision theory

While economic literature on loan officers assumes that they are fully rational people, making decisions on the base of real, although information concerning the quality of applicants and their investment projects are not verifiable, psychological decision theory recognises the role of individuals in arriving judgements. Their personalities and perceptions, roles and organisations including their values and emotions can affect their decision making styles. Psychological decision theory gives emphasis on individual process of reasoning while incorporating the social desirability of perceived consequences and specific motivational factors in processing risk and uncertainties leading to the formation of an overall judgement (Renn and Swaton 1984 ; Mcnamara and Bromiley 1997 ). Thus, embodiment of ‘bounded rationality’ concept into economic organisations has revolutionised economists from a fully rational model of decision making (Rakow 2010 ). Game theory, prospect theory, attribution theory and theory of choice are the most common theoretical assumptions used in psychological decision-making models (Oliveira 2007 ). In addition, researchers have also integrated psychological-based theories to study investors’ behaviour in financial decision making process. In these types of behavioural finance models, traditional assumptions of individual rationality hypothesis are relaxed and agents’ cognitive psychology is examined.

With the introduction of game theory in classical decision making models, psychological aspect of decision making can be seen. For instance, Barboza ( 2009 ) uses game theory approach to study micro lending with no physical collateral but social cost that acts as a quasi-collateral. In that study, the interplay of trust between lender, borrower and consignors is examined. In a regular market setting, using collateral to overcome asymmetry of information would be the dominant strategy and if the borrower is unable to provide such collaterals, the bank would refuse granting the loan. However, in microcredit setting, group-based individual lending contracts where if a person defaults, the other group members would need to pay off the balance owing to the lender, preventing moral hazard by the borrowers. Under this condition, joint liability among borrowers are created, therefore, only those borrowers which the group could trust would get loans, thereby decreasing asymmetry of information. In this study, strategic interaction among uncollateralised borrowers has been introduced into rational decision making model. However, it does not describe the complexity of different levels of political, social and cultural relationships. Another limitation in this study is that though it incorporates psychological thinking, it does not omit the assumptions of rational choice theory. Rational decision making models and economic applications of banks’ lending studies can also be seen using game theory which introduces strategic behaviour into rational decision theories. It focuses on interdependent decision making process (Shubik et al. 2002 ). The underlying assumption is that decision makers take into account of other people’s solutions before choosing an alternative. Jeong and Joh ( 2010 ) study banks’ risk taking behaviour using a game theory framework. They study Korean commercial banks using quarterly data on bank lending compiled by the Bank of Korea from 1993 to 2008. Their results show that big banks tend to take more risks by lending to high risk borrowers as they receive government protections through bail-outs and deposit insurances.

Researchers studying decision making from psychological perspectives are interested in the role of intuitions and emotions in arriving a judgement (Agor 1984 ; Klein 2003 ). Intuition is regarded as “vague feeling of knowing something without knowing exactly how or why” (Hayashi 2001 ; Lipshitz and Shulimovitz 2007 ). Emotion, on the other hand, is defined as the feelings of impending decision might be wrong, or that particular decision is inappropriate (Lipshitz and Shulimovitz 2007 ). The effects of intuition and emotion, in other words, behavioural factors, on banks’ lending decisions are widely studied (Jankowicz and HISRICH 1987 ; Lipshitz and Shulimovitz 2007 ; Bellucci et al. 2010 ; Hensman and Sadler-Smith 2011 ). Jankowicz and Hisrich ( 1987 ) use personal construct theory to explore intuitive factors of banks’ loan officers in small business loan decisions. Their sample includes 20 commercial loan officers from four banks in Tulsa, Oklahom, and Las Cruces, New Mexico. Their results indicate that intuition of loan officers plays more important role in business lending than collateral and other financial aspects of a prospective loan.

Prospect theory, for example, is first introduced by Kahneman and Tversky ( 1979 ), then, it is advanced into cumulative prospect theory by Tversky and Kahneman ( 1992 ). It insists that risk attitude is determined by the outcome’s relation to subjective judgement and not the level of outcome. According to prospect theory, individuals tend to be risk averse in a domain of gains or when the circumstances are in favour of them, and risk seeking in a domain of losses or when they are in the midst of crisis. It has been used by Godlewski ( 2007 ) to study risk-taking behaviour by banks in emerging markets. The author has used accounting data of 894 South-East Asian and South and Latin American banks for the period of 1996–2001 from Bankscope database. The results support prospect theory’s assumptions. Johnson ( 1993 ) has also found similar results using 142 banks’ data from Bank Compustat for the period of 1979–1989. These types of study over emphasise individuals’ cognitive processes. It fails to take into account of the institutional constraints such as regulatory requirements on the banks. When these types of constraints exist, even if the loan officers have all the information they need to validate the credibility of the borrower, loan applications might be rejected as to institutional limitations.

Psychological studies are oriented towards individual decision making and more or less assumed that people are rational when making economic decisions. This approach has been further improved by not only focusing on individual (micro) level but also on how societal (macro) level affects individual choice in social-psychological judgement theory. This is discussed in detail in the next section.

4.1.3 Social-psychological judgement and attitude theory (Sociocognitive)

Social-psychological study of risk perception is interested in the issues of risk communications and also termed as ‘empiricist psychometric’ approach (Taylor-Gooby and Zinn 2006 ). The studies of risk perceptions using social-psychological judgement theory assumes that risk is defined subjectively and influenced by psychological, social, institutional and cultural factors (Solvic 2001 ). In other words, psychological based studies focused only on intuition, personalities, emotions and perceptions, however, in social psychology, it is interested in knowing how social factors influence those psychological aspects and final judgements are arrived. McNamara and Bromiley ( 1997 ) studied influences on risk assessment in commercial lending using behaviour decision theories by recognising organisational and cognitive factors.

Bellucci et al. ( 2010 ) provide a review of literature and examined the theoretical arguments and empirical evidence on how genders of loan officers have effects on banks’ lending practices. They have summarised that male and female loan officers’ exhibit different risk tolerance levels. This can be the results of other factors such as differences in response to incentives (Agarwal and Wang 2008 ; Beck et al. 2009 ) and career concerns (Agarwal and Wang 2008 ).

Risk studies based on psychometric perspective use quantitative measures including questionnaire studies, magnitude estimation, numerical scaling, and attitude surveys (Taylor-Gooby and Zinn 2006 ). Other associated methodologies include Logit Model (Agarwal and Wang 2008 ; Barasinska 2009 ), Probit Model (Ravina 2008 ; Bellucci et al. 2009 ), Tobit Model (Ravina 2008 ) and qualitative methodologies such as interviews, are also used in association with quantitative measures (Buttner and Rosen 1988 ).

4.1.4 Sociological theories and policy analysis

By only depending on the behavioural data alone limits the importance of social context of choice (Cook et al. 1990 ). In other words, rational decision makers in a particular social context will not be able to make rational decisions as collection preferences cannot be obtained due to the constraints imposed from the contextual environment. Sociological perspective gives a distinctive contribution to risk analysis as its emphasis is on the role of shared ideas and normative frameworks which are formed by cultural and social factors (Taylor-Gooby and Zinn 2006 ). Douglas and Wildvasky ( 1982 ) have studied risk from sociocultural perspective. They have found a wide range of cultural bases for risk perception and the process of dealing with it. Thus, sociological perspective gives a significant contribution to classical risk studies whose assumptions are that individuals are rational actors.

However, sociological theories have not been incorporated extensively in studying banks’ lending behaviour, except for Lane and Quack ( 2002 ) who applied sociological institutionalist approach to understand how banks construct and manage risk in SME lending. The authors analysed banks financing in Britain and Germany and found different approach towards risk assessments despite banks are within EU regulations and internationalisation. This is because banks are deeply embedded in their own institutional framework.

Moreover, Lane and Quack ( 2002 ) investigate countries in which economic sanctions do not exist, therefore, with no barriers to internationalisation. By looking at this study, differences in banks’ lending practices can be seen across two different countries. If the banks are considered to be rational, no difference will be seen. Hence, banks’ operations and activities are affected by the institutional environment where they operate in (Hernández-Cánovas and Koëter-Kant 2010 ). Therefore, there requires the need to take into account of the context. By referring back to the theoretical studies of perception of risks, sociological theory would be the only one that addresses power, institutional constraints, social values and pressure groups on risk perception (Otway and Vonwinterfeldt 1982 ).

Thus, in order to understand banks’ risk assessment procedures and policies, it is necessary to consider the institutional environment in which the banks are embedded in. This includes regulative effects of state policy, legislation and intermediary organisations on banks’ lending behaviour which have been highlighted by some of the comparative studies of economic organisation in different societies (Lane and Quack 2002 ; Klein 2003 ; Whitley 2003 ) and other normative and cognitive effects as suggested by new institutional theory (Dimaggio and Powell 1983 ; Scott and Meyer 1994 ).

4.2 Analytical domains

Previous studies’ analytical domains are divided into three different levels of practice in sociology, micro, meso and macro levels.

4.2.1 Micro level

The studies in which individual interactions between and within organisations, thus having direct effects on decision making processes will be classified under micro level studies. For instance, Deyoung et al. ( 1999 ) study the effects of age, number of branches and size of the bank on banks’ lending using US commercial bank data and find that there are negative relationships between age and size of the banks on lending to small businesses. They have also found that banks with higher concentration of banks’ branches in urban market have positive effect on small business lending. Similar results are also found by Berger et al. ( 2001 ) and Zhong and Ying ( 2009 ) stating that large banks are less likely to engage in small business lending and this is also true for distressed and foreign owned banks in Argentina and China respectively.

Panagopoulos and Spiliotis ( 1998 ) and Degryse and Van Cayseele ( 2000 ) study the customer relationships and their effects on pledging collaterals and interest rates. The former uses bank level data set from Greek banks whereas the latter from Belgian banks. However, they have got the same results suggesting that the longer the customers have relationships with a bank, the lower the interest rates and probability of pledging collaterals. Sapienza ( 2004 ) and Micco and Panizz ( 2006 ) study the impact of bank ownership on banks’ lending. They have found that government-owned banks charge lower interest rates than private banks. Similarly, higher risk takings can be found in shareholder owned banks as they attempt to increase shareholders’ wealth (Seabright et al. 2002 ). These studies have used data from European transition countries. There is also another study of the relationships between internal credit ratings which is derived from Basel Accord II and interest premiums (Machauer and Weber 1998 ). This study focuses on German banks and finds that loan interest premiums are related to borrower credit ratings and show no relation to collaterals.

In summary, these micro level studies focus on the organisational factors such as customers, collaterals, bank size, ownership, age and number of branches and their effects on banks’ lending behaviour.

4.2.2 Meso level

Meso level studies are broader than micro level studies in the sense that they provide more focus on industrial effects on banks’ lending practices. One of the most studied meso level factors and its effects on banks’ lending is competition. There are significance number of studies stating that competition not only decreases cost of borrowing but also increases banks to have longer relationships with borrowers (Petersen and Rajan 1995 ; Ruckes 2004 ; Hauswald and Marquez 2006 ; Zhong and Ying 2009 ), thereby creating less incentives for banks to acquire information. Liu et al. ( 2012 ) study competition and risk taking in regard to South East Asian banking. They have found that concentration of banks lead to reduce risk taking. The major flaw of the study is that they have studied only four countries, namely, Indonesia, Malaysia, Philippines and Vietnam, which are listed under top six economies according to GDP data from IMF database. They have generalised the findings based on these four countries and concluded that competition decreases banks’ risk taking behaviour. Collateral laws and creditor protection rights are also found to have effects on banks’ lending, for instance, Haselmann and Wachtel ( 2006 ) study 423 banks in 20 transition countries in Europe and found that banks in good legal environment is associated with banks acceptance of different types of assets as collaterals and these banks are more willing to lend to information opaque borrowers.

Ely and Robinson ( 2001 ) also study the improved in credit scoring models in banking industry and its effects on banking industry using US banking data. They have discovered that technological change in credit scoring increases large banks’ share of small business lending and decreases average loan size to small businesses. The impacts of capital regulations on banks’ lending are also studied quite extensively by many researchers (Ben Naceur and Kandil 2009 ; Shrieves and Dahl 1995 ; Honda 2004 ; Yilmaz 2009 ). They have found that regulatory practices, capital regulation and bank penalties have significant effects on banks’ lending.

In summary, meso level studies focus on the relationships between competitions, collateral laws, and technological developments in banking sector, capital regulations and banks’ lending behaviour.

4.2.3 Macro level

Macro level studies are the broadest of all as it takes into account of all the factors that not only affect banking industry as such but the economy as a whole. These studies include macroeconomic uncertainties, socio-cultural environment, and so on. For instance, Baum et al. ( 2002 ) and Ruckes ( 2004 ) study of macroeconomic uncertainties such as uncertainty in future economic conditions, inflation, and volatility of interest rates on banks’ lending and found that banks become collectively more conservative in lending when there are a lot of pressures of macroeconomic uncertainties using bank level data from US. Similar results are found in Italian (Gambacorta and Mistrulli 2003 ) and.

Chilean banks (Micco and Panizz 2006 ). On the other hand, Maznevski et al. ( 2001 ) have taken a different perspective by studying banks’ lending behaviour from social-cultural environmental perspective. They have used comparative data on cultural orientations from Canada, Mexico, Netherlands, Taiwan and USA integrating behavioural finance approach to understand how the differences in social cultural environment can have an effect on banks’ lending practices. Their results indicate that loans are best rated when hierarchical information about the borrowers is given and worst when collective information is given.

It can be concluded that all of these papers study banks’ lending by either isolating analytical domains or considering decision making as being rational or at least within bounded rational by using quantitative methodologies. In other words, many of the research papers in this area usually isolate the factors by studying only one directional approach rather than the interconnectedness and reflective actions on influences. In addition, none of these studies undertake research on how banks respond to institutional environment and how they interact with each other in order to attain efficiency while achieving legitimacy. Different levels of studies provide different factors affecting banks’ lending behaviour. In reality, not only banks’ lending but also their other activities operate by interacting with the elements from both task and institutional environments.

Moreover, it is unrealistic to study risk perceptions only at an individual level and also, it is inappropriate to assume that individuals are rational. The studies with rationality assumption are weak in the sense it will not give complete picture of the phenomenon in how banks’ lending practices are shaped if the events or state of affairs that materialises them are excluded (Elster 1990 ). In order to choose one of the risks in decision making studies for this research, there is the need to understand the type of environments that banks operate in. In a country, banking sector receives more policy attention than any other sectors. This is because they play a dominant role in the financial system by leveraging their balance sheet structure to allocate financial resources for businesses. This high leverage implies substantial degree of exposure of capital to liquidity, credit and other risks, which can lead to possible bank runs and failures. If these happen, there can be disruptive consequences for the economy. As a result, quantitative (capital adequacy requirements for risk diversification) and qualitative (protection rules for stakeholders) prudential regulations are imposed on banks (Rocha et al. 1999 ), therefore, banks become highly institutionalised (Soon and Cummings 1997 ). In any organisations, in this case, banks operating in the industry mean they have claimed memberships to related institutions in this industry. Banks as members need to follow rules and norms in the environment along with the industry to become legitimate for their existence and survival. Thus, the type of study which integrates ‘sociological theories and policy analysis’ is more suitable for this research. To this date, sociological theories have yet to be widely applied in banking research, except for Lane and Quack ( 2002 ) and Riaz ( 2009 ). The former studies banks’ lending behaviour in the UK and Germany while the latter applied sociological approach to study the global financial crisis. As the research using sociological approach is limited, there is no prior framework or model to be followed. Therefore, the following chapter will provide the process by which sociological theories or approaches can be applied in banking studies.

5 Conclusions

In summary, the literature studying banks’ lending behaviour used statistical probability models based on bank level data which are only realised in the future and has ignored the fact that these future results are formed by the banks’ perceptions and risk attitudes towards businesses during their lending decisions. In other words, these financial studies focus on market-based judgements of financial risks and the ex-post calibration of different factors and bank lending. In contrast, bank lending decisions are strategic decision processes (ex-ante) and made depending on their perceptions of borrower’s credibility and repayment ability.

Secondly, these studies are limited in the sense that they only identified the significances of the relationships between different factors and banks’ lending, and failed to explore other factors constraining banks from externalising and internalising risks. By identifying the significances of the relationships, these studies isolate the factors in macro, meso and micro analyses and fail in one important respect, that is, how these factors influence one another, in other words, they fail to provide theoretical links in which these factors interact. More importantly, these analyses are based on the countries where transparency exists and large amount of data can be gathered through different sources.

Thirdly, most of these studies have ‘rationality’ assumptions in studying decision making approach. This causes limitations as it usually simplifies complexities of relationships between political and social relationships. Individual level decision making is very complex, hence, require an expanded set of concepts about how different institutional arrangements affect and are affected by individual decision making (Cook et al. 1990 ). Rationality is more concerned with micro level than macro level studies. Miller ( 1990 , p. 343) also makes distinctions between economics and sociology by stating that

“Economics is about how individuals make choices, and sociology is about how individuals have no choices to make. The gap between economics and sociology has certainly shrunk dramatically as economists have learned to accept the possibility that individual choices in coordination games are rationally constrained by social conventions and norms. However, individuals in social settings constrained by social norms still have important choices to make”

He suggests that there is still a gap in studying banks’ lending behaviour in two main streams, economic and sociology. Much of the research in banking is dominated by economists who integrate their rationality models into them. Despite sociological approach being recognised to improve banking studies, none of the sociologists have taken the steps to integrate their disciplinary assumptions and theories into this area. It is needed as banks are similar to individuals living in a community or a society, where they have to adapt to the environments that they live in and follow the requirements that their societies expected them to. These gaps in literature give a scope for interdisciplinary approach to study CRA.

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Win, S. What are the possible future research directions for bank’s credit risk assessment research? A systematic review of literature. Int Econ Econ Policy 15 , 743–759 (2018). https://doi.org/10.1007/s10368-018-0412-z

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The effect of credit risk management and bank-specific factors on the financial performance of the South Asian commercial banks

Asian Journal of Accounting Research

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Article publication date: 14 October 2021

Issue publication date: 27 May 2022

Among all of the world's continents, Asia is the most important continent and contributes 60% of world growth but facing the serving issue of high nonperforming loans (NPLs). Therefore, the current study aims to capture the effect of credit risk management and bank-specific factors on South Asian commercial banks' financial performance (FP). The credit risk measures used in this study were NPLs and capital adequacy ratio (CAR), while cost-efficiency ratio (CER), average lending rate (ALR) and liquidity ratio (LR) were used as bank-specific factors. On the other hand, return on equity (ROE) and return on the asset (ROA) were taken as a measure of FP.

Design/methodology/approach

Secondary data were collected from 19 commercial banks (10 commercial banks from Pakistan and 9 commercial banks from India) in the country for a period of 10 years from 2009 to 2018. The generalized method of moment (GMM) is used for the coefficient estimation to overcome the effects of some endogenous variables.

The results indicated that NPLs, CER and LR have significantly negatively related to FP (ROA and ROE), while CAR and ALR have significantly positively related to the FP of the Asian commercial banks.

Practical implications

The current study result recommends that policymakers of Asian countries should create a strong financial environment by implementing that monetary policy that stimulates interest rates in this way that automatically helps to lower down the high ratio of NPLs (tied monitoring system). Liquidity position should be well maintained so that even in a high competition environment, the commercial is able to survive in that environment.

Originality/value

The present paper contributes to the prevailing literature that this is a comparison study between developed and developing countries of Asia that is a unique comparison because the study targets only one region and then on the basis of income, the results of this study are compared. Moreover, the contribution of the study is to include some accounting-based measures and market-based measures of the FP of commercial banks at a time.

  • South Asian countries

Credit risk

Bank-specific factors.

  • Generalized method of moment

Siddique, A. , Khan, M.A. and Khan, Z. (2022), "The effect of credit risk management and bank-specific factors on the financial performance of the South Asian commercial banks", Asian Journal of Accounting Research , Vol. 7 No. 2, pp. 182-194. https://doi.org/10.1108/AJAR-08-2020-0071

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Copyright © 2021, Asima Siddique, Muhammad Asif Khan and Zeeshan Khan

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Introduction

Around the globe, depository institutions perform a crucial job in bringing financial stability and economic growth by mobilizing monetary resources across multiple regions ( Accornero et al. , 2018 ). The commercial plays an intermediary role by collecting the excessive amount from savers and issuing loans to the borrowers. In return, banks can earn a high interest rate ( Khan et al. , 2020 ; Ghosh, 2015 ). Banks tried to increase their financial performance (FP) by issuing loans while playing their intermediary role; banks have a high chance of facing credit risk. Accornero et al. (2018) found that the country's banking industry mostly collapses due to high credit risk. Sometimes, it leads to the failures of the whole financial system. Credit risk is expected to be arises when a borrower cannot meet their obligation about future cash flows. Commercial banks' FP is affected by two factors: one is external and the other is internal. Bank-specific factors are internal and able to control factors of the commercial banks. Ofori-Abebrese et al. (2016) pointed out that adverse selection and moral hazards were created due to mismanagement of internal factors. The abovementioned financial problems are turmoil period in the banking/financial sector.

Among the entire continent of the world, Asia is the most crucial continent and contributing 60% of world growth but facing the serving issue of high nonperforming loans (NPLs). It is well known that a high ratio of NPLs weakens the economy or country's financial position. The growth level in South Asia was the highest in 2015, and the ratio is 9.3%, which is the highest among all continents. According to the Asian Development Bank (2019), the NPLs in the south are approximately $518bn, which is relatively high compared to previous years. The soaring of NPLs in South Asian countries enforces a massive burden on commercial banks' financial position (mainly banks' lending process effected). The massive increase in NPL is observed after the global financial crisis (2007–2008). According to Masood and Ashraf (2012) , the credit risk high ratio of NPLs is the main reason for most of the financial crisis because NPLs alarmingly high during the Asian currency crisis in 1997 and subprime crises in 2007, and some loans are declared bad debts. The alarmingly high ratio of NPL resulted in an increasing depression in the financial market, unemployment and a slowdown of the intermediary process of banks (see Figure 1 ).

The World Bank statistics of different regions show that NPLs exist in almost all regions. Still, the ratio of NPLs is relatively high in the South Asian area compared to other regions. Therefore, the study is conducted in South Asia. Two proxies of credit risk are used in this study: NPLs and capital adequacy ratio (CAR). Moreover, the study also incorporates bank-specific factors to increase FP.

Various studies ( Louzis et al. , 2012 ; Ofori-Abebrese et al. , 2016 ; Hassan et al. , 2019 ) are conducted to address the issue, but literature shows that the results of these studies are inconclusive and also ignore the most important region of South Asia. Therefore, the study objective is to investigate that credit risk and banks specific factors affect FP of commercial banks in Asia or not? We have selected two from South Asia, Pakistan and India, as sample countries. In 2019, the NPLs were 13% and 10% in Pakistan and India, respectively. This ratio is relatively high as compared to the other countries of the world. Due to these reasons, we have mainly selected India and Pakistan from South Asian countries ( Siddique et al. , 2020 ). The present study uses secondary panel data set of 19 commercial banks from 2009 to 2018.

Two serious threats may exist: The first is autocorrelation and the second is endogeneity. If the data do not meet these CLRM assumptions, then the regression results are not best linear unbiased prediction (BLUE) ( Sekaran, 2006 ; Kusietal, 2017 ). And in this situation, apply pooled regression is applied, and then the results were biased because the coefficient results cannot give accurate meaning. After all, pool regression ignores year and cross section-wise variation. Therefore, in this study, an instrumental regression can be used that handle all these issues. Generalized method of moments (GMM) is used to analyze the data to overcome endogeneity. Our study is unique by addressing the autocorrelation and endogeneity issue at a time. Our study results show that credit risk measure NPLs decrease the FP due to having negative relation, while CAR has a positive relation with South Asian banks’ FP. The remainder of the research study is organized as follows: Section 2 consists of a detailed literature review; Section 3 consists of data and methodology. Sections 4 contains information about finding and suggestions. Finally, Section 5 discusses the conclusion.

Literature review

The Literature Review has mainly divided into two crucial sections; First part consists of the literature review related to credit risk and FP. The other part is related to the literature review of bank-specific variables and FP. In the hypothesis development, we have used commercial banks' profitability that represents the FP of commercial banks.

Credit risk and financial performance

While operating in the banking industry, three categories of risks that the bank has to face include environmental, financial and operational risks. Banks generate their incomes by issuing a massive amount of credit to borrowers. Still, this activity involves a significant amount of credit risk. When borrowers of the banking sector default cannot meet their debt obligation on time, it is called credit risk ( Accornero et al. , 2018 ). When there is a large amount of loan defaulter, then it adversely affects the profitability of the banking sector. Berger and DeYoung (1997) pointed out that the absence of effective credit risk management would lead to the incidence of banking turmoil and even the financial crisis. Siddique et al. (2020) explain that NPLs are related to information asymmetric theory, principal agency theory and credit default theory. When asymmetric information unequal distribution of information of high NPLs is spread, there is a chance that banks or financial declared bankrupt. According to Pickson and Opare (2016), the principal agency must separate corporate ownership from managerial interest. Because each management has its interest, they want more prestige, pay increment and want the stock options for management. Effective management of credit risk or nonperformance exposure in the banking sectors increases profitability. It enhances the development of banking sectors by adequate allotment of working capital in the economy ( Ghosh, 2015 ).

There is a growing literature ( Louzis et al. , 2012 ) on credit risk and its empirical relationship with the monetary benefits of the banking sector. Ekinci and Poyra (2019) investigate the relationship between credit risk and profitability of deposit banks in Turkey. The data sample used 26 commercial banks from 2005 to 2017. All data of this study are secondary and collected from annual reports of commercial Turkey banks. The proxies of profitability were taken as return on equity (ROE) and return on the asset (ROA), while NPLs of commercial banks were used as a proxy to measure credit risk. The research paper reveals that credit risk and ROA are negatively correlated as well as the relation between credit risk and ROE is also significantly negative relation. Therefore, the study suggests that the Turkey government tightly monitors and controls the alarmingly soaring ratio of NPLs. Upper management introduced some new measures to trim the credit risk.

There is a negative and significant relationship between NPLs and commercial banks' FP.

There is a positive and significant relationship between capital adequacy ratio and commercial banks' FP.

Bank-specific variables and financial performance

Bank-specific variables or internal factors are the product of business activity. Diversifiable risk is associated with these factors ( Louzis et al. , 2012 ) and can be reduced by efficient management. This risk is controllable compared to an external factor, which cannot be diversified because this risk is market risk ( Ghosh, 2015 ; Rachman et al. , 2018 ). If a firm can manage its internal factor effectively, then the firm can be high profitability, while, on the other hand, these factors are mismanaged. It would adversely affect the firm's balance sheet and income statement ( Ofori-Abebrese et al. , 2016 ). Different authors ( Akhtar et al. , 2011 ; Louzis et al. , 2012 ; Chimkono et al. , 2016 ; Hamza, 2017 ) discuss different bank-specific variables and firm performance in their studies. The bank-specific variables used in this study are cost-efficiency ratio (CER), average lending rate (ALR) and liquidity ratio (LR). Aspal et al. (2019) used two types of factors (macro and bank-specific factors) and inspected their connection with the FP of the commercial bank in India. Gross domestic product (GDP) and inflation are used as proxies of macroeconomic factors.

In contrast, a bank-specific variables’ proxy includes capital adequacy ratio, asset quality, management efficiency, liquidity and earnings quality. Data of 20 private banks have been used from 2008 to 2014. The panel data pointed out that one macroeconomic factor is significant (GDP), and another factor (Inflation) is insignificant. All bank's specific factors (earning quality, asset quality, management efficiency and liquidity) significantly affect the FP except the CAR (insignificant). Hasanov et al. (2018) conducted their study to explore the nature of the interrelation between bank-specific (BS) and macroeconomic determinants with the banking performance of Azerbaijan (oil-dependent economy). The study used the GMM to analyze the panel data set. The results show that bank loans, size, capital and some macro factors (inflation, oil prices) were positive and significantly interconnection with the FP of banks; on the other hand, liquidity risk, deposits and exchange rates are significantly affected negatively bonded with the FP.

There is a negative and significant relationship between the CER and commercial banks' FP.

There is a positive and significant relationship between the ALR and commercial banks' FP.

Francis et al. (2015) define liquidity in their study and, according to the liquidity of an asset, determined by how quickly this asset can be converted or transferred into cash. Liquidity is used to fulfill the short-term liabilities rather than the long term ( Siddique et al. , 2020 ; Raphael, 2013 ). Adebayo et al. (2011) mentioned in their study that when banks are unable to pay the required amount to their customers, it is considered bank failure. Sometimes liquidity risk affects the whole financial system of a country. Different studies are conducted on the issue of liquidity and performance, but different studies show different results. FP and liquidity, on the other hand, a chunk of studies ( Francis et al. , 2015 ; Hamza, 2017 ) revealed significant negative tie-up between liquidity and FP, while some other studies pointed out that there is no significant relationship between liquidity and FP. Therefore, the studies show a contradictory result, so the current study takes the bank-specific measures (LR, ALR study and CER) and checks its interconnection with commercial banks' FP.

There is a positive and significant relationship between the LR and commercial banks' FP.

Data and methodology

Our current study has one problem variable, financial performance (FP), while regressors variables are credit risk and bank-specific variables. Our model is consistent with Chimkono et al. (2016) , where ROA and ROE will be used as a measure of FP, while credit risk will be measured by NPL ratio, CAR and three specific variables: CER, LR and ALR.

Various studies ( Hamza, 2017 ; Belas, 2018 ) emphasize some macro and micro variables that need to be controlled when measuring FP because these factors are the influential factors. Three control variables: size of the bank, age of the banks and Inflation are used in this study and shown as yes in the tables. We have chosen these three control and most relevant variables because these variables represent both micro and economic situations. Data have been collected from two South Asian countries Pakistan and India. The nature of data is panel data and the number of banks from Pakistan (10 commercial banks) and India (9 commercial banks) is 19. The data have been collected from bank financial statements throughout 2009 to 2018, so the data of this study are a panel in nature. The final number of observations is 190 (19*10 = 190) for the analysis of this study (see Table 1 ).

Operational definition

The probability of lenders being the default, high credit risk higher FP of banks ( Louzis et al. , 2012 ).

Bank-specific factors are those which are under the control of the management of commercial banks ( Chimkono et al. , 2016 ).

Nonperforming loans

A loan becomes nonperforming when the duration of the loan has been passed, and after that duration, banks 90 days are passed unable to receive the principal amount of loan and interest payment ( Hamza, 2017 ).

Methodology

The current study investigates the interrelationship between credit risk, bank-specific factors and FP. Panel data set is used in our study, and two serious threats usually faced when using panel data set: (1) autocorrelation and (2) endogeneity. For this purpose, a GMM can be used. GMM model has many advantages on simple ordinary least square regression. And when in any study GMM model applies, it allows by adding the fixed effect model; this model can be able to tackle the problem of heterogeneity, and it also removes the problem of endogeneity by introducing some instrumental variables.

Model specification

The regression model is as follows:.

γ 0  = intercept; γ 1 - γ 8  = estimated coefficient of independent variables and control variables.

ε it represents error terms for those variables that are omitted or added intentionally/unintentionally.

According to Lassoued (2018) , panel data regression has two significant problems: autocorrelation and endogeneity, and this problem is existed due to the fixed effect. Therefore, our study checked the basic two assumptions of ordinary least squares.

Testing for autocorrelation

The fifth assumption of CLRM is that data should be free from autocorrelation. Sekaran (2006) pointed out the relationship between two different error terms should be zero; it means that there is no autocorrelation between error terms. There are different tests for testing autocorrelation, but the Wooldridge test is used in the present paper to test the autocorrelation.

Table 2 shows that the p -value of the Wooldridge test result is zero, so it means that all p -values are less than 0.05. It means that reject the null hypothesis. And the null hypothesis is that our data have no autocorrelation, but the results show that our data have autocorrelation problems.

Testing for endogeneity

The seventh assumption of CLRM is that data have no issue of endogeneity. Sekaran (2006) found that the relationship between the error term and explanatory or independent variable should be zero. If this relationship is not zero, then the problem of endogeneity exists. Brooks (2014) pointed out that Hausman test results probabilities can be used to test the endogeneity, and the null hypothesis of this test is that errors are uncorrelated. He also pointed out that if the probabilities are more than 0.10, then accept the null hypothesis. It means that there is no problem of endogeneity, and if the values are less than 0.1, then our data have the problem of endogeneity. Appendix 1 shows that some values of the Hausman test are less than 0.10, so it means that data have the problem of endogeneity. Our panel data results prove that our data have the problem of autocorrelation and endogeneity. Some CLRM model assumptions are not met, so ordinary least square regression results are not BLUE. And GMM model can be applied to any study because this model can be able to tackle the problem of autocorrelation, and it also removes the problem of endogeneity by introducing some instrumental variables.

Findings and discussion

The present research paper provides empirical evidence on the interconnection between credit risk and bank-specific/internal factors on FP commercial banks. To analyze the data set, first, the study applies the descriptive analysis to identify the big picture of the data, then the correlation section and at the end, regression results are discussed. Table 3 presents the descriptive statistics of the all variables used in the study: credit risk indicator which are the ratio of NPL, CAR; indicators of bank-specific factors (CER, ALR, LR); some control variables SIZE, AGE, INF and the measure of FP: ROA, ROE. The mean value of ROA and ROE is 0.986 and 7.964 with a standard deviation of 1.905 and 39.175, respectively, which shows that ROE has much higher variation than ROA. The standard deviation of NPL is 9.659, which is double that of CAR, whose standard deviation is 4.183 among all bank-specific factors (see Table 4 ).

Factor (CER, ALR, LR) LR has high dispersion (14.177) because there is a remarkable difference between minimum 25.027 and maximum value (107.179) of LR. ROA has 0.986 with a range between 10.408 and −6.234 with a standard deviation of 1.905, and it shows that there is a low level of dispersion in developed countries. The dispersion of ROE 39.175 is highest among all other variables, which means that some outliers exist in the ROE variable.

Correlation analysis is used to check the linear relationship between the two explanatory variables ( Brooks, 2014 ). If the sample size of any approaches to 100, greater than 100 and the correlation coefficient is 0.20, then the correlation is significant at 5% ( Lassoued, 2018 ). Most of the variables in the current study are significant at 5%.NPLs, and CER loans are negatively correlated with almost all independent variables, which supports the literature point that NPLs and CER are negatively associated with FP and bank-specific factors. The negative correlation of NPLs with ROE is loan −0.378, and this correlation is high as compared to other countries. At the same time, all bank-specific factors, CER, ALR and LR are mostly positively correlated with most of the other, almost all dependent and independent variables, while AGE and INF are mostly negatively correlated with the other variables of the study.

Regression results and discussion

Tables 5 and 6 have shown the regression results of pooled regression and GMM models. Tables include all independent, control variable coefficients, t -statistics, standard error and probability values. Additionally, tables have the values of R 2 , adjusted R 2 and Durbin Watson statistics. The adjusted R 2 under pooled regression are 0.250 and 0.231 in both models (ROA and ROE). While adjusted R 2 under the GMM are 0.358 and 0.249 in both models ROA and ROE.

It means the GMM more and better explains our model than pooled regression. Moreover, we also apply a Hausman test on both models. The p -value of both models is less than 0.05, so our data have the problem of endogeneity null hypothesis. To eliminate the endogeneity issue, the GMM coefficient was measured.

NPL has a significant and negative measure of FP: ROA and ROE. In contrast, CAR has significant and positive with all proxies of FP: ROE and ROA, which supports H1 and H2 of the paper. Our finding is consistent with Masood and Ashraf (2012) who conducted their study on credit risk and FP and found a significant negative relationship between NPL and FP, so NPLs hinder banks' profitability. Therefore, NPLs affect the whole financial system of a country especially in developing countries. The findings of CAR matched with Accornero et al. ’s (2018) study and pointed out that CAR has a significantly positive link with FP. CER has a significant negative relationship with ROA and ROE, which is consistent with the study of Francis et al. (2015) who pointed out a significant negative relationship between CER and ROE. Therefore, banks need to adapt strategies to control these costs and tried to increase their profitability. ALR had a significant and positive relationship with both measures of FP. ALR is significant at 1% with ROA and 10% significant with ROE. The result is supported by the study of Chimkono et al. (2016) who found a positive relationship between the ALR and FP of commercial banks.

LR has a significantly negative relationship with ROA and ROE. This finding is consistent with Siddique et al. (2020) who pointed out a significant negative relationship between LR and ROE; the more liquidity is maintained, the lesser the profitability level. In short, most of the independent variables are significant at 5% and 1%, and control variables are also significant in both models size of the bank and inflation except AGE. This result is matched with Ghenimi et al. ’s (2017) findings that prove that total assets or investment increment are directly proportional to the FP. Both variables of credit risk NPL and CAR are significant with the FP of commercial banks in both models. Banks try to reduce bank-specific factors risk, and by doing so, ultimately the amount of bad debt decreased, and another benefit is that it also reduces the amount of loan loss provision.

The current study empirically investigates the causal interrelation between credit risk, bank-specific factors and FP of commercial banks in two South Asian countries (Pakistan and India). The study's finding suggests that managers in South Asian countries should be focused on increasing capital adequacy to enhance the monetary gain (FP) while for the contraction of NPLs by implementing modern techniques and strategies for credit risk (NPLs) management. One indicator of the bank-specific variable (ALR) has a significant and positive interrelation with the FP of commercial banks. In contrast, CER and LR have a significant and positive relationship with the FP of commercial banks of South Asia. Control variables of the study (size of the bank and inflation) are also significant in both models except AGE. There are several policy implications that commercial banks of South Asian countries should be followed. NPLs are soaring due to the following reasons: less supervision and monitoring of customers, the problem of the market and lack of customer knowledge related to loans. Bank management should be efficient in judging that their customers have viable means of repayment or not. Moreover, banks can offer expert opinion to the professional loan take on feasible techniques of efficiently endow the borrowing to secure the required return on total firms investment is acquired. Liquidity position should be well maintained so that even in a high competition environment, the commercial can survive in that environment.

The scope of the study is only limited to commercial banks, but this model can also be applied to Islamic banks. And future researchers can also apply this model to a comparison-based study of commercial and Islamic banks. Data of this study have been collected only from 19 banks; future research can also increase the number of banks and increase the number of years to conduct their study. And if the number of banks and the number of the year increased, the results are a more reliable and accurate representation of the population. The data of this study have been taken only from two countries of South Asia, but this study can be extended by adding more countries in Asia. When we add the number of countries, the results are a better and accurate representation of developing and developed countries of Asia. This model can also be applied to some other continents because the macro environment and bank-specific factors are pretty different from continent to continent Appendix A1 .

research papers on credit management

NPLs-continent wise

Summary of explanatory variables and dependent variables

Results for autocorrelation for South Asia countries

Descriptive statistics

Correlation figures

ROA model (pooled regression and fixed effect GMM result)

Extra tables and figures in the Google drop box and available at: https://www.dropbox.com/sh/dro0gkowf3t542r/AAC3QQ5lKQTpLdke7UNxRUEea?dl=0

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Effect of Credit Risk Management on Financial Performance Of Nepalese Commercial Banks

The main purpose of this study is to investigate the effect of credit risk on the financial performance of commercial banks in Nepal. The panel data of seventeen commercial banks with 85 observations for the period of 2015 to 2020 have been analyzed. The regression model revealed that non – performing loan (NPLR) has negative and statistically significant impact on financial performance (ROA).Capital adequacy ratio (CAR) and bank size (BS) have negative and statistically no significant impact on financial performance (ROA). Credit to deposit (CDR) has positive but no significant relationship with the financial performance (ROA) and the study concluded that the management quality ratio (MQR) has positive and significant relationship with the financial performance (ROA) of the commercial banks in Nepal. The study recommends that, it is fundamental for Nepalese commercial banks to practice scientific credit risk management, improve their efficacy in credit analysis and loan management to secure as much as possible their assets, and minimize the high incidence of non-performing loans and their negative effects on financial performance.

Evaluation of Effects of Credit-Risk on Return on Assets of Commercial Banks in Nepal

Introduction: The major cause of bank distress in Nepal is associated with poor credit management which results to decline in credit standing of the banks. The study adopts judgmental sampling techniques. Objective: To analyze and evaluate the impact of credit-risk ratio on return on assets of commercial banks in Nepal. Research design: Descriptive and exploratory research designs were used. Methods and materials: Review of various articles and collection of secondary data through the websites of Nepal Rastra Bank. Results and conclusion: It is found that there is inverse relationship between credit risk ratio and return on assets ratio. The findings provide sufficient evidence that credit risk management indicators impact significantly on commercial bank performance in Nepal. Article type: Research Paper

Application of Machine Learning Techniques for Credit Risk Management: A Survey

Portfolio credit risk management applications, exploration of financial market credit scoring and risk management and prediction using deep learning and bionic algorithm.

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Methodical approaches for reducing the credit risk

Banking is inevitably associated with risks. No matter what efforts the bank makes to minimize risks, they will always exist – the only question is to what extent. Lending operations are among the most profitable types of banking, but they are associated with a high level of risk. The instability of the economic situation in the country, the imperfection of the legal framework in this area necessitate a detailed study of the problems of minimizing credit risks. It should be noted that the choice of methods of credit risk management in the bank is quite relevant today. Credit risk management is the most important task of any bank, and choosing the right method of credit risk management will increase the stability, reliability and competitiveness of the banking system, which will positively affect the overall economic condition of the country. Credit risk is the oldest in the system of banking risks and occupies a prominent place. It is necessary to work out an effective system of using the tools recognized by the world banking community to minimize risks, given the possibility of their transfer from the bank to investors. The starting point in the development of the latest risk management tools of the bank should be the creation of a regulatory framework that will regulate this process. It is necessary to improve the existing methodological framework and develop a new methodological framework for credit risk management of the bank, concentrating the advantages of existing assessment methods, create a single method of assessing the borrower's creditworthiness, not to mention a certain algorithm for banks to form credit procedures. It is necessary to adopt the experience of foreign banks in credit risk management. The experience of foreign banks in developed countries, based on a detailed study of all credit procedures, multifactor analysis of the creditworthiness of potential borrowers.

Enterprise Credit Risk Management Using Multicriteria Decision-Making

The purpose of this study is to reduce the rate of multicriteria decision-making (MCDA) errors in credit risk management and to weaken the influence of different attitudes of enterprise managers on the final decision when facing credit risk. First, several solutions that are suitable for present enterprise credit risk management are proposed according to the research of enterprise risk management in the world. Moreover, the criteria and matrix are established according to the general practice of the expert method. A decision-making method of enterprise credit risk management with trapezoidal fuzzy number as the criteria of credit risk management is proposed based on the prospect theory; then, the weight is calculated based on G1 weight calculation, G2 weight calculation method, and the method of maximizing deviation; finally, the prospect values of the alternatives calculated by each method are adopted to sort and compare the proposed solutions. Considering the difference of risk degree of managers in the face of credit risk management, the ranking results of enterprise credit risk management solutions based on three weight calculation methods are compared. The results show that as long as the quantitative value of the risk attitude of the enterprise credit risk manager meets a certain range, the final choice of credit risk management scheme ranking is consistent. This exploration provides a new research direction for enterprise credit risk management, which has reference significance.

The Impacts of New Financial Instrument Accounting Standards on Chinese Commercial Banks

On March 31, 2017, the Ministry of Finance revised and issued three new financial instrument accounting standards including Accounting Standards for Enterprises No.22- Recognition and Measurement of Financial Instruments. The banks of China’s A and H stocks have implemented the new standards since January 1, 2018. From January 1, 2021, the scope of implementation of the standards covers all non-listed commercial banks. The new financial instrument standards have undergone great changes in the classification and impairment treatment of financial assets, which is bound to have a profound impact on Chinese commercial banks. This article analyzes the impacts of new standards on Chinese commercial banks from the aspects of financial asset classification and measurement, impairment, credit risk management, profit and earnings management. Finally, the paper puts forward several suggestions and measures on the system and model construction, credit policy and post-loan risk management and talent training, in order to facilitate banks smooth the transition to the new standards.

Data Driven Design to Credit Risk Management Using Digital Footprint Intelligence

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Impact of risk management strategies on the credit risk faced by commercial banks of Balochistan

  • Zia Ur Rehman 1 ,
  • Noor Muhammad 1 ,
  • Bilal Sarwar 1 &
  • Muhammad Asif Raz 1  

Financial Innovation volume  5 , Article number:  44 ( 2019 ) Cite this article

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This study aims to identify risk management strategies undertaken by the commercial banks of Balochistan, Pakistan, to mitigate or eliminate credit risk. The findings of the study are significant as commercial banks will understand the effectiveness of various risk management strategies and may apply them for minimizing credit risk. This explanatory study analyses the opinions of the employees of selected commercial banks about which strategies are useful for mitigating credit risk. Quantitative data was collected from 250 employees of commercial banks to perform multiple regression analyses, which were used for the analysis. The results identified four areas of impact on credit risk management (CRM): corporate governance exerts the greatest impact, followed by diversification, which plays a significant role, hedging and, finally, the bank’s Capital Adequacy Ratio. This study highlights these four risk management strategies, which are critical for commercial banks to resolve their credit risk.

Introduction

Credit risk causes economic downturn as banks fail due to default risk from clients, which has had a negative impact on the economic development of many nations around the world (Reinhart & Rogoff, 2008 ). By definition, credit risk describes the risk of default by a borrower who fails to repay the money borrowed. The term hedging signals the protection of a business’s investments by limiting its level of risk, for example, by purchasing an insurance policy. Diversification is the allocation of financial resources in variety of different investments and has also long been understood to minimize such risk. The capital adequacy ratio is a measure of a bank’s capital maintained to absorb its outlying risks. Since there is a lot of competition among banks to attract customers, therefore, it has triggered several innovations in banking services (Aruwa & Musa, 2014 ). Regulators also require banks to improve internal governance practices in order to ensure transparency and ethical standards to keep the customers satisfied with their products and services. Ambiguity in banks’ terms and conditions will make it difficult for customers to select financial products appropriate for their needs, whereas clear terms and conditions allow customers to be more satisfied with the bank’s performance (Ho & Yusoff, 2009 ). Customers expect the financial institutions to have strong policies that can safeguard their interests and protect them. Therefore, poor understanding of effective credit risk and the acceptable risk management strategies by bank managers poses a threat to the commercial banks advancement and customers’ interest.

One critical success factor for financial institutions lies in their realization of the importance of credit risk and devising solid strategies – such as hedging, diversification and managing their capital adequacy ratio – to avoid shortcomings that could lead to operational catastrophe. Credit risks faced by banks have fundamental impact on the performance because, even few large customers default on loans would cause huge problems for it. The objective of the Credit Risk Management (CRM) process is to maximize the cost-adjusted rate of return of a particular bank by maintaining exposure to credit risk acceptable to its shareholders. Banks have to navigate the credit risk associated with the overall portfolio as well as external risks that may be due to macroeconomic factors in the economy. Banks must also compare the credit risk relationships with other risks. Another specific case of credit risk applies to the method of trying to settle banking transactions. Until and unless both parties settle their payments in a timely manner, bank suffers from opportunity loss. Corporate governance may also have large effect on the risk management strategies used by the bank for reducing credit risks. Research suggests that it is imperative that banks engage in prior planning in order to avoid future problems (Andrews, 1980 ).

Majority of commercial banks provide several services that could help them mitigate or manage risk. For example, hedging has been used to reduce the level of risk involved in transactions by keeping specific conditions that would allow different parties to exchange goods or services at a flexible date and time (Harrison & Pliska, 1981 ). The significance of effective risk management strategies have been highlighted by many researchers and practitioners over time to assist banks and other financial institutions. CRM became an obvious necessity for commercial banks, especially after the 2008 global financial crisis, in which it was primarily subprime mortgages that caused a liquidity crisis (Al-Tamimi, 2008 ). According to Al-Tamimi ( 2008 ), ensuring the efficient practice of risk management may not be expensive but the implementation should be done in a timely manner in order to ensure smooth banking operations.

A financial institution, just like a constituent part of any other major economic sector, aims to meet incurred expenses, increase the return on invested capital and maximize the wealth of its shareholders. In their pursuance of these objectives, the financial system has to offer effective risk management strategies to financial institutions like banks against credit risk (Hakim & Neaime, 2005 ).

Problem statement

In 2008, across the world, the credit crisis began as a result of mass issuing of sub-prime mortgages to individuals in the United States leading to defaults, which caused outwardly-rippling problems for financial institutions all across the world. Sub-prime mortgages and other loans with less restrictions can generate remarkable losses including corporate failure and bankruptcy for financial institution (Brown & Moles, 2014 ). These credit decisions have a pivotal role in firms’ profitability. The decision to over-extend credit to high-risk customers may increase short-term profitability for individual banks, though in aggregate, this lending behavior was seen to become a major challenge to the risk management structures of the economy as a whole. Therefore, managing risk is the most important element of a bank’s operations. This phenomenon is equally applicable to banks across the globe, including banks in Pakistan.

Due to unstable and volatile nature of the political and financial environment in Pakistan, banks are affected by many types of risk, including risks to foreign exchange rates, liquidity, operations, credit and interest rates. Pakistan’s financial institutions are generally risk-averse, especially towards car financing and mortgage loans in which chances of huge losses are higher (Shafiq & Nasr, 2010 ). Balochistan is the least developed part with largest geographical area in Pakistan. There are limited opportunities for small businesses and majority of businesses are run in informal form with poor documentation. Majority of commercial banks face problems like loan documents verification and loan processing. Therefore, the adoption of proper risk management strategies can help understand and mitigate the credit risk faced by commercial banks of Balochistan.

Research objective

This study aims to identify the different risk management strategies that can influence the management of credit risk by commercial banks. We expect to determine if these strategies contribute both to the reduction of credit risk as well as the efficient performance in fulfilling customer needs.

Significance of the study

This study aims to provide a basis for guidance for the commercial banks of Balochistan to adopt long-term performance-improving risk management strategies (Campbell, 2007 ). The model for the study shows the impact of risk management strategies, including hedging, diversification, the capital adequacy ratio and corporate governance. The research will also examine the impact of each risk management strategy individually in order to understand the importance of each strategy. To the best of authors’ knowledge, there is no study on credit risk management on Balochistan using the described parameters. The findings of this study are intended to contribute positively to society by demonstrating that the banks of Balochistan can develop effective strategies to improve their CRM. Additionally, policy makers can identify and generate appropriate policies to govern bank behavior in order to minimize risk.

Literature review

Credit risk is considered as the chance of loss that will occur when the loan or any other line of credit by a particular debtor is not repaid (Campbell, 2007 ). Since 2008, financial experts around the world have researched and analyzed the primary factors underpinning the credit crisis to identify problematic behavior and effective solutions that can help financial institutions avoid catastrophe in the future. Long ago, the Basel Committee on Banking Supervision Footnote 1 (1999) has also identified credit risk as potential threat to banking sector and developed certain banking regulations that must be maintained by the banks around the world. Owojori, Akintoye, and Adidu ( 2011 ) stated that there are legislative inadequacies in financial system especially in banking system that are effective as well as lack of uniform credit information sharing amongst banks. Thus, it urges to the fact that banks need to emphasize on better risk management strategies which may protect them in the long run.

Abiola and Olausi ( 2014 ) emphasized on the establishment of a separate credit unit at banks with professional staff for credit/loan officers and field officers. It is important as they perform variety of functions from project appraisals through credit disbursement, loan monitoring to loans collection. Therefore, a comprehensive human resource policy related their selection, training, placement, job evaluation, discipline, and remuneration need to be in placed to avoid any inefficiencies related to loan management and credit defaults.

Ho and Yusoff ( 2009 ) focused on researching Malaysian financial institutions and their management of credit risk. The study involved a sample of 15 foreign and domestic financial institutions from which the data was collected through questionnaires. The findings demonstrated that the diversification of loan services leads to risk improvement, though it requires training employees and the commitment of employees to ensure that the financial institution will meet the requirements for best practice lending.

Brown and Wang ( 2002 ) conducted study about the challenges faced by Australian financial institutions due to credit risk over the period January 1986 to August 1993. The Australian financial institutions were not able to provide a wide variety of alternatives to their clients that led to higher risks as there was a lack of diversification in their services. The research suggested that corporate governance practices allow firms to adopt appropriate rules, policies, and procedures to ensure that the rights of all the stakeholders are fulfilled. Hedging Footnote 2 is used by financial institutions to minimize the risk associated with the transactions conducted with the bank customers as it allows the bank to minimize the risk by offering flexible offers that allows customer to make their decisions effectively (Dupire, 1992 ).

The work of Karoui and Huang ( 1997 ) indicates that the super hedging strategy Footnote 3 could be implemented to achieve a surplus downside market risk as it possesses a duality of both the super hedging and open hedging approaches. The prices of options can increase due to the volatility of the asset prices. If the prices of the financial instrument are fluctuating, then the price of the options contract might also be influenced as the buyers or sellers will be deriving their profit from the price of the financial security (Hobson, 1998 ).

Several factors are associated with the pricing of securities as these factors support the financial decisions that must be made by the investors. The loans that the bank provides to the borrower are highly dependent on the conditions of the market. Decision-making for mitigation and management of credit risk is very important for banks (Li, Kou, & Peng, 2016 ). A highly volatile security market will influence the prices and interest rates of the securities being exchanged in such a market. Financial markets are affected by the macroeconomic variables that influence the prices of the securities being exchanged. Hedging allows firms and their managers to incorporate policies that will maximize the value of the company as clients have a wide array of alternatives that allow them to make their decisions in an effective manner. The derivatives such as options, futures, forwards and swaps that are used by firms increase their financial stability by allowing the customers to have sufficient information that improves their decision making in different circumstances. This enables managers to adopt practices that will benefit their organizations. Hedging allows businesses to support a higher debt load due to its flexible nature and ability to minimize risk, which increases the value of the company as it can actually meet the needs of more customers with a comparatively lower level of risk (Graham & Rogers, 2002 ). Similarly, Levitt ( 2004 ) explained that hedging enables firms to extend its activities because the risk inherent to providing funds is reduced in such transactions, allowing more flexibility to all involved parties.

Banks are able to maintain a particular level of reserved cash for the sake of managing the day to day operations that is decided based on the allocated capital adequacy ratio. This enables the bank to maintain a balance of cash that is sufficient to meet the needs of the customers. Managers can use the bank’s available cash flow to meet short-term cash requirement needs, which are based on the concept of capital adequacy ratio. This gives certainty to some funds that banks must maintain in order to address unforeseen circumstances. The selective hedging concept has been used by firms for the sake of making investments that are based on a certain part of their portfolio that pose the most threat and not the entire portfolio of the financial instruments (Stulz, 1996 ). The emphasis is on utilizing hedging at the right time for the specific customer that a company believes should be entering into a contract with flexible terms and conditions. It is a viable option for banks to use hedging to avoid customers’ dissatisfaction for those who do not meet the firm’s loan eligibility criteria. Zhang, Kou & Peng, ( 2019 ) proposed a consensus model that considers the cost and degree of consensus in the group decision making process. With a certain degree of consensus the generalized soft cost consensus model was developed by defining the generalized aggregation operator and consensus level function. The cost is properly reviewed from the perspective of the individual experts and the moderator. Economic significance of the two soft consensus cost models is also assessed. The usability of the model for the real-world context is checked by applying it to a loan consensus scenario that is based on online data from a lending platform. Group decision making is critical for changing the opinions of everyone to arrive at a synchronized strategy for minimizing the risks of the bank with the help of hedging (Zhang, Kou, & Peng, 2019 ).

Kou, Chao, Peng, Alsaadi & Herrera-Viedma, ( 2019 ) identified that financial systemic risk is a major issue in financial systems and economics. Machine learning methods are employed by researchers that are trying to respond to systemic risks with the help of financial market data. Machine learning methods are used for understanding the outbreak and contagion of the systemic risk for improving the current regulations of the financial market and industry. The paper studies the research and methodologies on measurement of financial systemic risk with the help of big data analysis, sentiment analysis and network analysis. Machine learning methods are used along with systematic financial risk management for controlling the overall risks faced by the banks that are related to hedging of the financial instruments of the bank (Kou, Chao, Peng, Alsaadi, & Herrera-Viedma, 2019 ).

Provision of financial assistance to customers that require the funds for business activity can prove profitable for the bank (Datta, Rajagopalan, & Rasheed, 1991 ). If the principle and interest of the loan is repaid in a timely manner that would help the banks ensure smooth flow of their operations, and the economic activities in the society are improved as the standard of living of people also improves with such financial assistance that is provided by commercial banks (Keats, 1990 ). As banks enter into such contracts with several customers, the level of the its incurred risk increases; management likewise becomes more complex with a more diverse group of customers (Kargi, 2011 ). Non-Performing Loans (NPL) represent the credit that a bank believes is causing a loss, and includes loan defaults, which are typically categorized by their expectation of recovery as “standard,” “doubtful” or “lost” (Kolapo, Ayeni, & Oke, 2012 ). The lost category focusing on the inability of the bank to recover particular products restricts a bank from reaching the set targets thus causing a bank to fail in attaining the objectives of profitability that have been set. The incurrence of a large amount of high-risk debt is often difficult for banks to manage unless the managers have undertaken appropriate strategies for mitigating the risk in addition to enhancing their financial performance. The existence of NPLs prompted central global banks to enter into the 1988 Basel Accord, also known as Basel I (later superseded in 2004 by Basel II), which maintained that banks must maintain a particular amount of capital in order to meet their operational needs (Van Greuning & Brajovic Bratanovic, 2009 ). This on-hand capital requirement, also called the capital adequacy ratio, is beneficial as it allows banks to more easily manage potential, sudden financial losses (Keats, 1990 ).

Kithinji ( 2010 ) provides specific evidence that the management of credit risk does not influence the profitability of banks in Kenya. In fact, the Kargi ( 2011 ) study on Nigerian banks from 2004 to 2008 revealed a healthy relationship between appropriate CRM (Credit Risk Management) and bank performance. Poudel ( 2012 ) emphasized the significant role played by CRM in the improvement of financial performance of banks in Nepal between 2001 and 2011. Strict requirements of maintaining higher capital that is around 14.3% of the cash balance as reserve in the banks of Nepal was found to have resulted in better bank performance by producing more profit.

Heffernan ( 1996 ) stated that CRM is crucial for predicting proper bank financial performance. A bank’s inability to recoup its outstanding loans reduces its ability to engage in other profitable transactions A loss both of principle as well as interest (including time value) means also a loss in opportunities to expand and pursue other profitable operations (Berríos, 2013 ).

Banks that avoid risk management face several challenges, including their own survival in the current highly competitive financial environment. To compete successfully with other commercial financial institutions, banks rely on a diversification of products and financial services to improve portfolio performance, including attracting more customers. Diversified services allow customers to select the most appropriate financial assistance in light of their individual needs. Along with diversification of the financial services, banks need to manage the credit risk involved where funds are given as loans for various needs of the customers such as car loans, house loans, starting a new business or expanding ongoing business (Kou, Ergu, Lin, & Chen, 2016). It is also important to have effective behavior monitoring models to ensure that bank employees are careful in minimizing the operational risks by providing maximum information to the customers about the financial instruments and the restrictions imposed by the bank for the sake of protecting the interests of the financial institution. Chao, Kou, Peng & Alsaadi, ( 2019 ) conducted a study to understand a new form of money laundering that is trade based which is using the signboard of international trade. It appears along with the capital movement that is mostly concerned with the rise in the collapse of the overall financial market. It is difficult to prevent money laundering since it has a plausible sort of trade characterization. The aim of the paper is to develop monitoring methods that have accurate recognition along with classified form of supervision of the trade based money laundering with the help of multi class knowledge driven classification algorithms that are linked with the micro and macro prudential regulations. Based on an empirical study from China the application is reviewed and the effectiveness is assessed in order to improve the efficiency of the management in the financial markets (Chao, Kou, Peng, & Alsaadi, 2019).

Selecting the most eligible customers for a loan is also essential to managing credit risk: a bank can screen through a list of customers to identify the ones who have a higher probability of repayment within the specified time duration, according to the terms and conditions of the contract. Hentschel and Kothari ( 1995 ) emphasized that using different derivatives is significant for the leverage of the financial institution. A vast majority of companies surveyed were using derivatives to reduce their risk (Kou, Peng, & Wang, 2014 ). Dolde, ( 1993 ) highlighted that several banks are vulnerable to various risks, therefore, banks have undertaken specific precautionary measures like training their employees, developing better credit policies and reviewing the credit rating of the customers applying for the loans (Dolde, 1993 ).

Diversification is adopted by corporations for increasing the returns of the shareholders and minimizing risk. Decision-making criteria is improved by using classifiers that have some algorithms for resolving problems (Kou, Lu, Peng, & Shi, 2012 ). Rumelt ( 1974 ) revealed that only around 14% of firms on the Fortune 500 list were working as single business organizations in 1974, whereas 86% of the businesses operated in diversified product markets. This shows a considerable inclination of the business sector to emphasize diversification instead of single trade. Much research has been conducted focusing on the activities of companies during recent times; most have found a rise in the prevalence of diversified firms (Datta et al., 1991 ).

Research hypotheses

The first hypothesis considers assessing the role of hedging in reducing a bank’s credit. Based on a model presented by Felix ( 2008 ), which showed risk management strategies of hedging, capital adequacy ratio and diversification may be used to explain credit risk that a bank faces. Thus our first hypothesis is as follows:

H 1 : hedging will minimize credit risk faced by the commercial banks of Balochistan

The second risk management strategy is diversification, which requires banks to provide a wide range of financial services with flexible terms to customers and to provide credit to a wide range of customers instead of few in order to reduce risk (Fredrick, 2013 ). The concept of diversification can be used by banks as they create a wide customer pool for providing loans, instead of providing large amount of loans to few customers, which inherently increases risk (Hobson,  1998 ). Therefore,

H 2: diversification will minimize credit risk of the commercial banks of Balochistan

The third hypothesis considers management strategy that requires banks to maintain a particular amount of the capital (Ho & Yusoff, 2009 ). The capital adequacy ratio is critical for banks to be in a better position to manage unexpected risks and thus capital maintained in a bank has a consequence at overall credit risk therefore the it may be hypothesized as following:

H 3 : capital adequacy ratio will minimize credit risk of commercial banks of Balochistan

The fourth hypothesis considers the role played by corporate governance in minimizing credit risk. Corporate governance assumes that the organization or corporation should adopt all practices that ensure accountability to the stakeholders (Shafiq & Nasr, 2010 ). Therefore,

H 4 : corporate governance will minimize credit risk of the commercial banks of Balochistan

Methodology.

This study adopts an explanatory research design, which was aimed to collect authentic, credible and unbiased data. The data were collected from the employees of commercial banks located in the province of Balochistan, Pakistan. All ethical considerations were made during the research process. The questionnaire developed for the collection of information was prepared to effectively incorporate all potential factors that include, diversification, hedging, capital adequacy ratio, corporate governance and credit risk. The purpose of this research was clearly explained in the questionnaire as it was being shared with the respondents.

The participants were informed about the research objective and ensured that the information provided would be kept confidential. This step was designed to remove bias and ensure that the participants were able to share their views without having any reservations. This process is important for authentic results and reliable information (Levitt, 2004 ).

The sample size for this study comprised of 250 employees from commercial banks in Balochistan. There are large scale commercial banks that operate in Pakistan with several branches of these banks working in the entire country. Commercial banks approached for this study included Habib Bank Limited, Standard Chartered Bank, United Bank Limited, Summit Bank, Faisal Bank, Askari Bank and Bank Al-Habib.

The questionnaire was adopted from a global survey previously conducted by the World Bank. This study analyzed the work that has been done on managing credit risk in several countries in different parts of the world. Our questionnaire used the framework of this valuable research tool, adopting changes specific to address the localized context of Balochistan.

The information collected from the participants was analyzed to identify trends and practices in the banks operating in Balochistan to understand the practices of these commercial banks for managing credit risk. Following is the theoretical framework of the study.

figure a

The relationships between risk management strategies such as diversification, hedging, the capital adequacy ratio and corporate governance with credit risk itself were determined in the paper.

Results & findings

The questionnaire was tested to check the reliability through Cronbach’s alpha (Table 1 ), which shows internal consistency of the instrument; the information revealed that the data are 80% reliable, considering the total of 31 questions asked. The information is essential as this shows that the results and findings of the study are reliable and they can be generalized to the population (Hungerford, 2005 ).

The correlation table shows the relationship between the different variables in the research study. The dependent variable, credit risk, was reviewed against the independent variables: corporate governance, hedging, diversification and capital adequacy ratio. The correlation is essential for further analysis as there should be some relation between the different variables. Each variable is used for the correlation analysis so it highlights the correlation among all the variables with each other. This is useful for assessing the correlation among the independent variables and to ensure that it is not too high leading to a problem of multicollinearity.

Table  2 shows the results of the correlation test between the independent variables and the dependent variable. Before running regression analysis, basic assumptions were also checked. Data normality was checked through skewness and kurtosis and for all variables; these values were in range ± 2. Linearity was checked through correlation analysis and all variables were shown to have a significant relationship with each other. Homogeneity was checked through scatter plot, showing that the variance across all variables was the same. No autocorrelation was found as the value for the Durbin Watson test was 2, showing no correlation among residuals (Antonakis, Bendahan, Jacquart, & Lalive, 2014 ). The value for the variance inflation factor (VIF) was VIF < 5, which shows no relationship among the four independent variables. The regression test was used to determine the influence of each of the variable on credit risk. The results can be seen in Table 3 .

Credit risk can be influenced by different factors but, there is around 36% influence of the four variables that are independent. The variation of 36% can be explained by the independent variables that are hedging, diversification, capital adequacy ratio and corporate governance on credit risk. These factors account for this much change that can be observed in the credit risk faced by the commercial banks. The adjusted r 2 was further analyzed because it is a better measure for a focused analysis on a bank’s performance.

Table  4 shows the results of the assessment of the data for the overall model goodness of fit; the overall model is highly significant at p  < 0.05. The analysis of the variance across the small samples of the data reveals that the overall information is consistent.

The standardized coefficients in Table 5  show the rate of change that is caused by each of the variables in the credit risk of the commercial banks. This is critical information as the variable that is having a higher coefficient value will be having more influence on the level of credit risk so it should be emphasized more by the commercial banks for the sake of achieving better performance. The regression analysis highlights that the four independent variables have an impact on credit risk.

The results reveal that corporate governance had the most impact on credit risk (with a 0.288 standardized beta value). In other words, this CRM strategy appears to be the most beneficial for commercial banks to undertake. Next is diversification (0.263 beta), followed by hedging (0.250 beta) and, finally, the capital adequacy ratio (0.040 beta). The results are significant in is showing that these variables have an impact on credit risk. The constant value was calculated at 1.765 and the error term in the equation is 0.237.

Recommendations

The banks in Balochistan would benefit from adopting sound strategies to improve control over credit risk. CRM strategies such as diversification, hedging, corporate governance and the capital adequacy ratio have all been cited in extant research as being crucial for the success in this regard; in fact, many problems arising from credit risk can be resolved by implementing some combination of these strategies. The research findings can likewise help the government of Balochistan to ensure that commercial banks take appropriate risk management measures to help keep them from failures, such as falling into bankruptcy (Greuning & Bratanovic, 2009 ). Society depends on the smooth operation of the banking sector, so individual (and aggregate) bank performance can help contribute to the development and improved welfare of the economy. Therefore, effective inspection should be employed by the banks to check and safeguard bank resources. Effective trainings and refresher courses should be giving to bank employees in the areas of risk asset management, risk control and credit utilization in order to ensure proper usage and performance.

Several banks have failed in the past as they were not able to control their credit risk. Recommendations for banks stemming from this study include the diversification of their products and services, which is critical as it allows the bank to provide customers with many products and services. After diversification, an emphasis on employing corporate governance policies is most important, according to the findings. Hedging and the capital adequacy ratio are also important strategies that can be examined and optimized by banks. Hedging is useful because entering into flexible contracts helps reduce risk. The banks in Balochistan will be able to realize the importance of the capital adequacy ratio as that will allow them to achieve a proper balance between the amounts of capital that should be maintained to manage the needs of the investors. It is recommended that further research on the topic should be conducted so that effective strategies for management of other risks can be identified for banks. The success and further progress of these banks depend on the smooth implementation of risk management strategies and activities, which have been shown to have a very significant positive impact on the ability of the banks of Balochistan to control credit risk.

Availability of data and materials

The data of the research paper will be available upon request.

This is a place in Switzerland where the Basel Committee on Banking Supervision (BCBS) comprising of 45 members from 28 Jurisdictions, consisting of Central Banks and authorities have the responsibility of banking regulation.

Hedging are flexible contracts that allow customers to agree to buy a particular product in future date using spot rates. It allows customers and banks to manage the transaction by locking contracts at desired price.

Super hedging strategy allows the users to hedge their positions with a trading plan based on self-financing. A low price is paid for the portfolio that would ensure that it’s worth to be equal or higher at a future date.

Acknowledgements

We are grateful to all the reviewers who have shared their valuable comments and suggestions for the research paper. The Editorial Board of Financial Innovation has been extremely kind in their editorial efforts.

There was no funding required for the completion of the research paper.

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Zia Ur Rehman, Noor Muhammad, Bilal Sarwar & Muhammad Asif Raz

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NM is the corresponding author and he has also given the idea for the paper. NM has reviewed the theoretical framework and empirical analysis of the research paper. ZR has written the manuscript and collected the data for the paper. BS has reviewed the methodology of the paper and reviewed literature. MAR has given conception advice and edited the paper. All authors have read the paper and approved the final manuscript.

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Rehman, Z.U., Muhammad, N., Sarwar, B. et al. Impact of risk management strategies on the credit risk faced by commercial banks of Balochistan. Financ Innov 5 , 44 (2019). https://doi.org/10.1186/s40854-019-0159-8

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Foreign Currency Liquidity Risk Management at Japanese Major Banks: Efforts and Enhancement

May 22, 2024 Financial System and Bank Examination Department, Bank of Japan Strategy Development and Management Bureau, Financial Services Agency

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Securing stable foreign currency liquidity is one of the most important issues for Japanese major banks, as it is the basis of the expansion of their overseas businesses. The March 2023 banking turmoil in the United States and Switzerland shed new light on the importance of managing liquidity risk. Against this background, major banks have been enhancing their risk management through foreign currency liquidity stress testing based on more conservative and appropriate stress scenarios, early warning frameworks, and prompt and accurate liquidity data management. The Financial Services Agency and the Bank of Japan have supported these efforts through initiatives including joint surveys. As a result, major banks' resilience to foreign currency liquidity risk has steadily improved. However, there remains room for further enhancement. Going forward, banks are expected to continue their efforts to further enhance their risk management in line with changes in the risk profiles of their overseas businesses and the external environment.

The Bank of Japan Review Series is published by the Bank to explain recent economic and financial topics for a wide range of readers. This report, 2024-E-3, is a translation of the Japanese original, 2024-J-7, published in May 2024.

If you have any comments or questions, please contact Financial System and Bank Examination Department (E-mail : [email protected]).

McKinsey Global Private Markets Review 2024: Private markets in a slower era

At a glance, macroeconomic challenges continued.

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McKinsey Global Private Markets Review 2024: Private markets: A slower era

If 2022 was a tale of two halves, with robust fundraising and deal activity in the first six months followed by a slowdown in the second half, then 2023 might be considered a tale of one whole. Macroeconomic headwinds persisted throughout the year, with rising financing costs, and an uncertain growth outlook taking a toll on private markets. Full-year fundraising continued to decline from 2021’s lofty peak, weighed down by the “denominator effect” that persisted in part due to a less active deal market. Managers largely held onto assets to avoid selling in a lower-multiple environment, fueling an activity-dampening cycle in which distribution-starved limited partners (LPs) reined in new commitments.

About the authors

This article is a summary of a larger report, available as a PDF, that is a collaborative effort by Fredrik Dahlqvist , Alastair Green , Paul Maia, Alexandra Nee , David Quigley , Aditya Sanghvi , Connor Mangan, John Spivey, Rahel Schneider, and Brian Vickery , representing views from McKinsey’s Private Equity & Principal Investors Practice.

Performance in most private asset classes remained below historical averages for a second consecutive year. Decade-long tailwinds from low and falling interest rates and consistently expanding multiples seem to be things of the past. As private market managers look to boost performance in this new era of investing, a deeper focus on revenue growth and margin expansion will be needed now more than ever.

A daytime view of grassy sand dunes

Perspectives on a slower era in private markets

Global fundraising contracted.

Fundraising fell 22 percent across private market asset classes globally to just over $1 trillion, as of year-end reported data—the lowest total since 2017. Fundraising in North America, a rare bright spot in 2022, declined in line with global totals, while in Europe, fundraising proved most resilient, falling just 3 percent. In Asia, fundraising fell precipitously and now sits 72 percent below the region’s 2018 peak.

Despite difficult fundraising conditions, headwinds did not affect all strategies or managers equally. Private equity (PE) buyout strategies posted their best fundraising year ever, and larger managers and vehicles also fared well, continuing the prior year’s trend toward greater fundraising concentration.

The numerator effect persisted

Despite a marked recovery in the denominator—the 1,000 largest US retirement funds grew 7 percent in the year ending September 2023, after falling 14 percent the prior year, for example 1 “U.S. retirement plans recover half of 2022 losses amid no-show recession,” Pensions and Investments , February 12, 2024. —many LPs remain overexposed to private markets relative to their target allocations. LPs started 2023 overweight: according to analysis from CEM Benchmarking, average allocations across PE, infrastructure, and real estate were at or above target allocations as of the beginning of the year. And the numerator grew throughout the year, as a lack of exits and rebounding valuations drove net asset values (NAVs) higher. While not all LPs strictly follow asset allocation targets, our analysis in partnership with global private markets firm StepStone Group suggests that an overallocation of just one percentage point can reduce planned commitments by as much as 10 to 12 percent per year for five years or more.

Despite these headwinds, recent surveys indicate that LPs remain broadly committed to private markets. In fact, the majority plan to maintain or increase allocations over the medium to long term.

Investors fled to known names and larger funds

Fundraising concentration reached its highest level in over a decade, as investors continued to shift new commitments in favor of the largest fund managers. The 25 most successful fundraisers collected 41 percent of aggregate commitments to closed-end funds (with the top five managers accounting for nearly half that total). Closed-end fundraising totals may understate the extent of concentration in the industry overall, as the largest managers also tend to be more successful in raising non-institutional capital.

While the largest funds grew even larger—the largest vehicles on record were raised in buyout, real estate, infrastructure, and private debt in 2023—smaller and newer funds struggled. Fewer than 1,700 funds of less than $1 billion were closed during the year, half as many as closed in 2022 and the fewest of any year since 2012. New manager formation also fell to the lowest level since 2012, with just 651 new firms launched in 2023.

Whether recent fundraising concentration and a spate of M&A activity signals the beginning of oft-rumored consolidation in the private markets remains uncertain, as a similar pattern developed in each of the last two fundraising downturns before giving way to renewed entrepreneurialism among general partners (GPs) and commitment diversification among LPs. Compared with how things played out in the last two downturns, perhaps this movie really is different, or perhaps we’re watching a trilogy reusing a familiar plotline.

Dry powder inventory spiked (again)

Private markets assets under management totaled $13.1 trillion as of June 30, 2023, and have grown nearly 20 percent per annum since 2018. Dry powder reserves—the amount of capital committed but not yet deployed—increased to $3.7 trillion, marking the ninth consecutive year of growth. Dry powder inventory—the amount of capital available to GPs expressed as a multiple of annual deployment—increased for the second consecutive year in PE, as new commitments continued to outpace deal activity. Inventory sat at 1.6 years in 2023, up markedly from the 0.9 years recorded at the end of 2021 but still within the historical range. NAV grew as well, largely driven by the reluctance of managers to exit positions and crystallize returns in a depressed multiple environment.

Private equity strategies diverged

Buyout and venture capital, the two largest PE sub-asset classes, charted wildly different courses over the past 18 months. Buyout notched its highest fundraising year ever in 2023, and its performance improved, with funds posting a (still paltry) 5 percent net internal rate of return through September 30. And although buyout deal volumes declined by 19 percent, 2023 was still the third-most-active year on record. In contrast, venture capital (VC) fundraising declined by nearly 60 percent, equaling its lowest total since 2015, and deal volume fell by 36 percent to the lowest level since 2019. VC funds returned –3 percent through September, posting negative returns for seven consecutive quarters. VC was the fastest-growing—as well as the highest-performing—PE strategy by a significant margin from 2010 to 2022, but investors appear to be reevaluating their approach in the current environment.

Private equity entry multiples contracted

PE buyout entry multiples declined by roughly one turn from 11.9 to 11.0 times EBITDA, slightly outpacing the decline in public market multiples (down from 12.1 to 11.3 times EBITDA), through the first nine months of 2023. For nearly a decade leading up to 2022, managers consistently sold assets into a higher-multiple environment than that in which they had bought those assets, providing a substantial performance tailwind for the industry. Nowhere has this been truer than in technology. After experiencing more than eight turns of multiple expansion from 2009 to 2021 (the most of any sector), technology multiples have declined by nearly three turns in the past two years, 50 percent more than in any other sector. Overall, roughly two-thirds of the total return for buyout deals that were entered in 2010 or later and exited in 2021 or before can be attributed to market multiple expansion and leverage. Now, with falling multiples and higher financing costs, revenue growth and margin expansion are taking center stage for GPs.

Real estate receded

Demand uncertainty, slowing rent growth, and elevated financing costs drove cap rates higher and made price discovery challenging, all of which weighed on deal volume, fundraising, and investment performance. Global closed-end fundraising declined 34 percent year over year, and funds returned −4 percent in the first nine months of the year, losing money for the first time since the 2007–08 global financial crisis. Capital shifted away from core and core-plus strategies as investors sought liquidity via redemptions in open-end vehicles, from which net outflows reached their highest level in at least two decades. Opportunistic strategies benefited from this shift, with investors focusing on capital appreciation over income generation in a market where alternative sources of yield have grown more attractive. Rising interest rates widened bid–ask spreads and impaired deal volume across food groups, including in what were formerly hot sectors: multifamily and industrial.

Private debt pays dividends

Debt again proved to be the most resilient private asset class against a turbulent market backdrop. Fundraising declined just 13 percent, largely driven by lower commitments to direct lending strategies, for which a slower PE deal environment has made capital deployment challenging. The asset class also posted the highest returns among all private asset classes through September 30. Many private debt securities are tied to floating rates, which enhance returns in a rising-rate environment. Thus far, managers appear to have successfully navigated the rising incidence of default and distress exhibited across the broader leveraged-lending market. Although direct lending deal volume declined from 2022, private lenders financed an all-time high 59 percent of leveraged buyout transactions last year and are now expanding into additional strategies to drive the next era of growth.

Infrastructure took a detour

After several years of robust growth and strong performance, infrastructure and natural resources fundraising declined by 53 percent to the lowest total since 2013. Supply-side timing is partially to blame: five of the seven largest infrastructure managers closed a flagship vehicle in 2021 or 2022, and none of those five held a final close last year. As in real estate, investors shied away from core and core-plus investments in a higher-yield environment. Yet there are reasons to believe infrastructure’s growth will bounce back. Limited partners (LPs) surveyed by McKinsey remain bullish on their deployment to the asset class, and at least a dozen vehicles targeting more than $10 billion were actively fundraising as of the end of 2023. Multiple recent acquisitions of large infrastructure GPs by global multi-asset-class managers also indicate marketwide conviction in the asset class’s potential.

Private markets still have work to do on diversity

Private markets firms are slowly improving their representation of females (up two percentage points over the prior year) and ethnic and racial minorities (up one percentage point). On some diversity metrics, including entry-level representation of women, private markets now compare favorably with corporate America. Yet broad-based parity remains elusive and too slow in the making. Ethnic, racial, and gender imbalances are particularly stark across more influential investing roles and senior positions. In fact, McKinsey’s research  reveals that at the current pace, it would take several decades for private markets firms to reach gender parity at senior levels. Increasing representation across all levels will require managers to take fresh approaches to hiring, retention, and promotion.

Artificial intelligence generating excitement

The transformative potential of generative AI was perhaps 2023’s hottest topic (beyond Taylor Swift). Private markets players are excited about the potential for the technology to optimize their approach to thesis generation, deal sourcing, investment due diligence, and portfolio performance, among other areas. While the technology is still nascent and few GPs can boast scaled implementations, pilot programs are already in flight across the industry, particularly within portfolio companies. Adoption seems nearly certain to accelerate throughout 2024.

Private markets in a slower era

If private markets investors entered 2023 hoping for a return to the heady days of 2021, they likely left the year disappointed. Many of the headwinds that emerged in the latter half of 2022 persisted throughout the year, pressuring fundraising, dealmaking, and performance. Inflation moderated somewhat over the course of the year but remained stubbornly elevated by recent historical standards. Interest rates started high and rose higher, increasing the cost of financing. A reinvigorated public equity market recovered most of 2022’s losses but did little to resolve the valuation uncertainty private market investors have faced for the past 18 months.

Within private markets, the denominator effect remained in play, despite the public market recovery, as the numerator continued to expand. An activity-dampening cycle emerged: higher cost of capital and lower multiples limited the ability or willingness of general partners (GPs) to exit positions; fewer exits, coupled with continuing capital calls, pushed LP allocations higher, thereby limiting their ability or willingness to make new commitments. These conditions weighed on managers’ ability to fundraise. Based on data reported as of year-end 2023, private markets fundraising fell 22 percent from the prior year to just over $1 trillion, the largest such drop since 2009 (Exhibit 1).

The impact of the fundraising environment was not felt equally among GPs. Continuing a trend that emerged in 2022, and consistent with prior downturns in fundraising, LPs favored larger vehicles and the scaled GPs that typically manage them. Smaller and newer managers struggled, and the number of sub–$1 billion vehicles and new firm launches each declined to its lowest level in more than a decade.

Despite the decline in fundraising, private markets assets under management (AUM) continued to grow, increasing 12 percent to $13.1 trillion as of June 30, 2023. 2023 fundraising was still the sixth-highest annual haul on record, pushing dry powder higher, while the slowdown in deal making limited distributions.

Investment performance across private market asset classes fell short of historical averages. Private equity (PE) got back in the black but generated the lowest annual performance in the past 15 years, excluding 2022. Closed-end real estate produced negative returns for the first time since 2009, as capitalization (cap) rates expanded across sectors and rent growth dissipated in formerly hot sectors, including multifamily and industrial. The performance of infrastructure funds was less than half of its long-term average and even further below the double-digit returns generated in 2021 and 2022. Private debt was the standout performer (if there was one), outperforming all other private asset classes and illustrating the asset class’s countercyclical appeal.

Private equity down but not out

Higher financing costs, lower multiples, and an uncertain macroeconomic environment created a challenging backdrop for private equity managers in 2023. Fundraising declined for the second year in a row, falling 15 percent to $649 billion, as LPs grappled with the denominator effect and a slowdown in distributions. Managers were on the fundraising trail longer to raise this capital: funds that closed in 2023 were open for a record-high average of 20.1 months, notably longer than 18.7 months in 2022 and 14.1 months in 2018. VC and growth equity strategies led the decline, dropping to their lowest level of cumulative capital raised since 2015. Fundraising in Asia fell for the fourth year of the last five, with the greatest decline in China.

Despite the difficult fundraising context, a subset of strategies and managers prevailed. Buyout managers collectively had their best fundraising year on record, raising more than $400 billion. Fundraising in Europe surged by more than 50 percent, resulting in the region’s biggest haul ever. The largest managers raised an outsized share of the total for a second consecutive year, making 2023 the most concentrated fundraising year of the last decade (Exhibit 2).

Despite the drop in aggregate fundraising, PE assets under management increased 8 percent to $8.2 trillion. Only a small part of this growth was performance driven: PE funds produced a net IRR of just 2.5 percent through September 30, 2023. Buyouts and growth equity generated positive returns, while VC lost money. PE performance, dating back to the beginning of 2022, remains negative, highlighting the difficulty of generating attractive investment returns in a higher interest rate and lower multiple environment. As PE managers devise value creation strategies to improve performance, their focus includes ensuring operating efficiency and profitability of their portfolio companies.

Deal activity volume and count fell sharply, by 21 percent and 24 percent, respectively, which continued the slower pace set in the second half of 2022. Sponsors largely opted to hold assets longer rather than lock in underwhelming returns. While higher financing costs and valuation mismatches weighed on overall deal activity, certain types of M&A gained share. Add-on deals, for example, accounted for a record 46 percent of total buyout deal volume last year.

Real estate recedes

For real estate, 2023 was a year of transition, characterized by a litany of new and familiar challenges. Pandemic-driven demand issues continued, while elevated financing costs, expanding cap rates, and valuation uncertainty weighed on commercial real estate deal volumes, fundraising, and investment performance.

Managers faced one of the toughest fundraising environments in many years. Global closed-end fundraising declined 34 percent to $125 billion. While fundraising challenges were widespread, they were not ubiquitous across strategies. Dollars continued to shift to large, multi-asset class platforms, with the top five managers accounting for 37 percent of aggregate closed-end real estate fundraising. In April, the largest real estate fund ever raised closed on a record $30 billion.

Capital shifted away from core and core-plus strategies as investors sought liquidity through redemptions in open-end vehicles and reduced gross contributions to the lowest level since 2009. Opportunistic strategies benefited from this shift, as investors turned their attention toward capital appreciation over income generation in a market where alternative sources of yield have grown more attractive.

In the United States, for instance, open-end funds, as represented by the National Council of Real Estate Investment Fiduciaries Fund Index—Open-End Equity (NFI-OE), recorded $13 billion in net outflows in 2023, reversing the trend of positive net inflows throughout the 2010s. The negative flows mainly reflected $9 billion in core outflows, with core-plus funds accounting for the remaining outflows, which reversed a 20-year run of net inflows.

As a result, the NAV in US open-end funds fell roughly 16 percent year over year. Meanwhile, global assets under management in closed-end funds reached a new peak of $1.7 trillion as of June 2023, growing 14 percent between June 2022 and June 2023.

Real estate underperformed historical averages in 2023, as previously high-performing multifamily and industrial sectors joined office in producing negative returns caused by slowing demand growth and cap rate expansion. Closed-end funds generated a pooled net IRR of −3.5 percent in the first nine months of 2023, losing money for the first time since the global financial crisis. The lone bright spot among major sectors was hospitality, which—thanks to a rush of postpandemic travel—returned 10.3 percent in 2023. 2 Based on NCREIFs NPI index. Hotels represent 1 percent of total properties in the index. As a whole, the average pooled lifetime net IRRs for closed-end real estate funds from 2011–20 vintages remained around historical levels (9.8 percent).

Global deal volume declined 47 percent in 2023 to reach a ten-year low of $650 billion, driven by widening bid–ask spreads amid valuation uncertainty and higher costs of financing (Exhibit 3). 3 CBRE, Real Capital Analytics Deal flow in the office sector remained depressed, partly as a result of continued uncertainty in the demand for space in a hybrid working world.

During a turbulent year for private markets, private debt was a relative bright spot, topping private markets asset classes in terms of fundraising growth, AUM growth, and performance.

Fundraising for private debt declined just 13 percent year over year, nearly ten percentage points less than the private markets overall. Despite the decline in fundraising, AUM surged 27 percent to $1.7 trillion. And private debt posted the highest investment returns of any private asset class through the first three quarters of 2023.

Private debt’s risk/return characteristics are well suited to the current environment. With interest rates at their highest in more than a decade, current yields in the asset class have grown more attractive on both an absolute and relative basis, particularly if higher rates sustain and put downward pressure on equity returns (Exhibit 4). The built-in security derived from debt’s privileged position in the capital structure, moreover, appeals to investors that are wary of market volatility and valuation uncertainty.

Direct lending continued to be the largest strategy in 2023, with fundraising for the mostly-senior-debt strategy accounting for almost half of the asset class’s total haul (despite declining from the previous year). Separately, mezzanine debt fundraising hit a new high, thanks to the closings of three of the largest funds ever raised in the strategy.

Over the longer term, growth in private debt has largely been driven by institutional investors rotating out of traditional fixed income in favor of private alternatives. Despite this growth in commitments, LPs remain underweight in this asset class relative to their targets. In fact, the allocation gap has only grown wider in recent years, a sharp contrast to other private asset classes, for which LPs’ current allocations exceed their targets on average. According to data from CEM Benchmarking, the private debt allocation gap now stands at 1.4 percent, which means that, in aggregate, investors must commit hundreds of billions in net new capital to the asset class just to reach current targets.

Private debt was not completely immune to the macroeconomic conditions last year, however. Fundraising declined for the second consecutive year and now sits 23 percent below 2021’s peak. Furthermore, though private lenders took share in 2023 from other capital sources, overall deal volumes also declined for the second year in a row. The drop was largely driven by a less active PE deal environment: private debt is predominantly used to finance PE-backed companies, though managers are increasingly diversifying their origination capabilities to include a broad new range of companies and asset types.

Infrastructure and natural resources take a detour

For infrastructure and natural resources fundraising, 2023 was an exceptionally challenging year. Aggregate capital raised declined 53 percent year over year to $82 billion, the lowest annual total since 2013. The size of the drop is particularly surprising in light of infrastructure’s recent momentum. The asset class had set fundraising records in four of the previous five years, and infrastructure is often considered an attractive investment in uncertain markets.

While there is little doubt that the broader fundraising headwinds discussed elsewhere in this report affected infrastructure and natural resources fundraising last year, dynamics specific to the asset class were at play as well. One issue was supply-side timing: nine of the ten largest infrastructure GPs did not close a flagship fund in 2023. Second was the migration of investor dollars away from core and core-plus investments, which have historically accounted for the bulk of infrastructure fundraising, in a higher rate environment.

The asset class had some notable bright spots last year. Fundraising for higher-returning opportunistic strategies more than doubled the prior year’s total (Exhibit 5). AUM grew 18 percent, reaching a new high of $1.5 trillion. Infrastructure funds returned a net IRR of 3.4 percent in 2023; this was below historical averages but still the second-best return among private asset classes. And as was the case in other asset classes, investors concentrated commitments in larger funds and managers in 2023, including in the largest infrastructure fund ever raised.

The outlook for the asset class, moreover, remains positive. Funds targeting a record amount of capital were in the market at year-end, providing a robust foundation for fundraising in 2024 and 2025. A recent spate of infrastructure GP acquisitions signal multi-asset managers’ long-term conviction in the asset class, despite short-term headwinds. Global megatrends like decarbonization and digitization, as well as revolutions in energy and mobility, have spurred new infrastructure investment opportunities around the world, particularly for value-oriented investors that are willing to take on more risk.

Private markets make measured progress in DEI

Diversity, equity, and inclusion (DEI) has become an important part of the fundraising, talent, and investing landscape for private market participants. Encouragingly, incremental progress has been made in recent years, including more diverse talent being brought to entry-level positions, investing roles, and investment committees. The scope of DEI metrics provided to institutional investors during fundraising has also increased in recent years: more than half of PE firms now provide data across investing teams, portfolio company boards, and portfolio company management (versus investment team data only). 4 “ The state of diversity in global private markets: 2023 ,” McKinsey, August 22, 2023.

In 2023, McKinsey surveyed 66 global private markets firms that collectively employ more than 60,000 people for the second annual State of diversity in global private markets report. 5 “ The state of diversity in global private markets: 2023 ,” McKinsey, August 22, 2023. The research offers insight into the representation of women and ethnic and racial minorities in private investing as of year-end 2022. In this chapter, we discuss where the numbers stand and how firms can bring a more diverse set of perspectives to the table.

The statistics indicate signs of modest advancement. Overall representation of women in private markets increased two percentage points to 35 percent, and ethnic and racial minorities increased one percentage point to 30 percent (Exhibit 6). Entry-level positions have nearly reached gender parity, with female representation at 48 percent. The share of women holding C-suite roles globally increased 3 percentage points, while the share of people from ethnic and racial minorities in investment committees increased 9 percentage points. There is growing evidence that external hiring is gradually helping close the diversity gap, especially at senior levels. For example, 33 percent of external hires at the managing director level were ethnic or racial minorities, higher than their existing representation level (19 percent).

Yet, the scope of the challenge remains substantial. Women and minorities continue to be underrepresented in senior positions and investing roles. They also experience uneven rates of progress due to lower promotion and higher attrition rates, particularly at smaller firms. Firms are also navigating an increasingly polarized workplace today, with additional scrutiny and a growing number of lawsuits against corporate diversity and inclusion programs, particularly in the US, which threatens to impact the industry’s pace of progress.

Fredrik Dahlqvist is a senior partner in McKinsey’s Stockholm office; Alastair Green  is a senior partner in the Washington, DC, office, where Paul Maia and Alexandra Nee  are partners; David Quigley  is a senior partner in the New York office, where Connor Mangan is an associate partner and Aditya Sanghvi  is a senior partner; Rahel Schneider is an associate partner in the Bay Area office; John Spivey is a partner in the Charlotte office; and Brian Vickery  is a partner in the Boston office.

The authors wish to thank Jonathan Christy, Louis Dufau, Vaibhav Gujral, Graham Healy-Day, Laura Johnson, Ryan Luby, Tripp Norton, Alastair Rami, Henri Torbey, and Alex Wolkomir for their contributions

The authors would also like to thank CEM Benchmarking and the StepStone Group for their partnership in this year's report.

This article was edited by Arshiya Khullar, an editor in the Gurugram office.

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Child Tax Benefits and Labor Supply: Evidence from California

research papers on credit management

In the United States today, some of the largest social welfare programs focused on children – including the Earned Income Tax Credit (EITC) and Child Tax Credit (CTC) – require that parents earn income from work. While intended to encourage recipients to work, tax credit work requirements may also harm the lowest-income families. In this paper, the authors study whether eliminating child tax credit work requirements affects parents’ decision to work.

The authors study this question in the context of California’s Young Child Tax Credit (YCTC), a refundable state tax credit for low-income parents with children younger than six. When the YCTC was enacted in 2019 it was available to any taxpayer with income over $1. Then, beginning in 2022, California eliminated the work requirement altogether.   Using federal administrative tax data, the authors compare the labor force participation of mothers with children who just barely qualify for the YCTC to those with children just above the age cutoff, before and after the work requirement was eliminated. They find the following:

  • Eliminating the YCTC work requirement did not cause a significant number of California mothers to exit the labor force. The authors estimate that working mothers’ labor force participation fell by no more than 0.4 percentage points with the elimination of the work requirement.

The results of the study suggest that eliminating the work requirement from the federal CTC would cause fewer exits from the labor force than prior studies suggest. The results also provide new evidence for states considering adopting or reforming their own child tax benefits, as a central issue in designing such policies is whether to condition benefits on work.

More on this topic

research papers on credit management

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research papers on credit management

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The macroeconomics of the greek depression.

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