Credit Risk Management In Banks
Author Rohan Rokade
Credit Risk Management Framework at Banks in India
Bodla, B.S. & Verma Richa (2009) examines the Credit Risk Management Framework of scheduled commercial banks in India. Key findings include:
- Direct lending activities are perceived to pose the highest credit risk, regardless of bank size.
- The Securitization Ordinance Act, 2002, is favoured by most banks for managing credit risk.
- Credit Risk Policy approval is primarily by the Board of Directors, with credit risk management authority typically centralized at the Head Office level.
- Risk rating is highly favoured by banks for credit risk management, alongside credit administration, prudential limits, and loan review.
- Prudential limits suggested by the RBI, such as exposure and borrower limits, are adhered to, with variations based on bank size.
- Risk rating, performed mostly annually, is considered crucial, with MIS design being a significant requirement.
- CRISIL’s models and internally designed models are favoured for credit portfolio evaluation.
- Off-balance sheet exposure is clearly defined by most banks.
- Financial performance, operating efficiency, and management quality are vital for inter-bank exposure evaluation.
- Derivative usage for credit risk management is minimal, and standardized approaches are preferred for capital charge calculation.
Overall, the Credit Risk Management framework aligns with RBI guidelines. While risk rating is paramount, other instruments like credit administration and prudential limits are crucial. However, there’s a need for enhanced understanding and training among risk managers regarding methodologies and instruments. Recommendations include organizing high-quality training programs on risk management by banks and regulatory authorities.
Evaluating the Credit Risk Management Framework of Public
and Private Sector Banks in India
Arora, A. & Kumar, M. (2014) states that Generally, people differentiate between the risk management capabilities of public and private sector banks. But the findings of this study establish that there is no significant difference in the
overall strength of the CRM framework of both public and private sector banks, though on the whole there existed a little difference in the scores of the public sector and the private sector
banks. The study makes an important contribution by providing evidence against the myth that private banks are better than public sector banks in building their CRM framework and upgrading
their risk management capabilities. The results clearly indicate that on an average both public and private sector banks were on par in embracing benchmark CRM practices. As an understanding of the current strengths and weaknesses provide directions for future decision making by managers, the study has policy implications for public and private sector banks.
Bank Credit Risk Management and Migration Analysis
Gavalas,D. & Syriopoulous, T.(2014) investigates the relationship between credit risk management and the macroeconomy, particularly focusing on the impact on financial strength measures such as the Tier 1 capital ratio. By examining data from the internal rating systems of central banks in four advanced European countries, the study explores the connection between credit migration risk and economic indicators, using the Capacity Utilization Index (CUI) as a macroeconomic variable. The study is novel in its empirical estimation of time-homogeneous average matrices for different economic phases (boom and contraction) and comparing the Dynamic Time-dependent Markovian Latent (DTML) method with the Constant Time-dependent Markovian Latent (CTML) method. Results suggest that the time-dependent function tends to overestimate probability of defaults (PDs) during boom phases, posing questions for future research in this area.
Credit risk management in commercial banks
Suresh et al(2010) finds and explains that-
- NPAs (Non-Performing Assets) in private banks show a decreasing trend post-liberalization, particularly from 2001-02 onwards.
- Homogeneity in credit exposure among banks was found to be lacking upon comparing with critical values.
- A positive relationship exists between overall NPAs of private banks and NPAs of individual banks, with significant correlation observed in nine out of fifteen banks.
- Certain occupational portfolios, such as Agriculture (except in rural areas), Transport operations (except in semi-urban areas), and others, exhibit an inverse relationship with NPAs, suggesting that NPAs decrease with increased credit advances to these sectors.
- Some portfolios, like Agriculture in urban and metropolitan regions, and Transport operators in rural and urban areas, make negative contributions to NPAs, indicating a decrease in NPAs with increased credit advances.
- Certain portfolios, including Agriculture in rural areas, Industry in all regions, and others, make positive contributions to NPAs, suggesting an increase in NPAs with increased credit advances.
- Various credit advances, notably towards Agriculture and Industry, have significant contributions to NPAs, highlighting the importance of credit risk management.
- Additionally, it is emphasized that credit risk management is crucial in the deregulated market, urging banks to adopt competitive Early Warning Systems (EWS) and Basel-II methodology for effective risk management. The adoption of international best practices, particularly Basel-II, is seen as essential for Indian banks to compete effectively in the global banking environment.
- Top of Form
Credit Risk Management of Loan Portfolios by Indian Banks
Nandi, J. K. & Choudhary, N. K.(2011) study the ‘Credit Risk Management Framework’ of scheduled commercial banks operating in India and also to arrive at a model that can help Indian banks manage their credit risk in a better way. The paper mainly adopts discriminant model to compare the performance of a number of
simple credit risk management techniques. This kind of simple and innovative technique can provide a new standard for predicting the defaulters with accuracy. This study also helps in improving
the current predicting power of financial risk factors of banks thereby reducing their NPAs. While risk rating is the most important instrument, other instruments of credit risk
management such as credit administration, prudential limits and loan review are used extensively by the banks. If these instruments are united by simple models of credit risk management, as discussed in this paper, it can help the banks in a big way. But the developed model should be verified and should meet all the prudential norms, otherwise it can give misleading results.
Credit Risk Management Index Score For Indian Banks
Arora, A. & Kumar, M. (2014) explains a novel quantitative measure of the strength of the Customer Relationship Management (CRM) framework in the Indian banking system, along with an assessment of each element within this framework. By benchmarking against comprehensive practices in commercial banks, the study offers an objective measure of CRM quality at a national level. Bank management can use these scores to gauge the extent and depth of CRM practices, identifying strengths and weaknesses within their framework. Two focus areas highlighted are CRM operations and systems at both transaction and portfolio levels. The study’s managerial implications extend to various stakeholders including regulators, policymakers, depositors, and shareholders. Understanding current strengths and weaknesses aids in framing effective CRM strategies for optimal decision-making and shareholder value enhancement. The cross-sectional comparison with other developing economies provides insights for policymakers and regulators. Identification of weaknesses within CRM elements enables appropriate regulatory measures to be taken, contributing to the overall soundness of the banking sector and financial system. The evaluation reflects a fair level of maturity in the Indian banking system’s CRM framework, boosting confidence in the financial markets. In conclusion, the study advocates for a disciplined approach to strengthening CRM frameworks in commercial banks through regular quantitative assessments of each CRM element.
The Impact of Branch Network on Credit Risk Management Practices in Indian banks
Arora, A (2014) Introduces a single quantitative measure to assess the overall strength of the Customer Relationship Management (CRM) framework in the Indian banking system, along with a detailed quantitative evaluation of each element within this framework. By basing the CRM index scores on a comprehensive set of benchmark practices in commercial banks, the study aims to offer an objective and verifiable measure of CRM quality at the national level. These scores can aid bank management in understanding the depth and extent of CRM practices and identifying potential strengths and weaknesses in their CRM framework. Two focal areas for commercial banks in India are highlighted: CRM operations and systems at the transaction level, and CRM operations and systems at the portfolio level, specifically focusing on monitoring practices and risk assessment. Managerial implications of the study are significant, providing valuable insights for bank management, regulators, policymakers, depositors, and shareholders. By evaluating current strengths and weaknesses, bank management can refine their mix of CRM practices, strategies, and techniques to optimize decision-making and enhance shareholder value. Furthermore, the study facilitates cross-sectional comparisons with other developing economies, aiding policymakers in benchmarking and identifying areas for improvement. Identification of weaknesses in each CRM element can inform regulatory measures by the Central Bank, contributing to the overall soundness of the commercial banking sector and strengthening the nation’s financial system. The evaluation results reflect a fair level of maturity in the CRM framework of the Indian banking system, fostering confidence in the Indian financial markets. The study advocates for regular quantitative assessments of each CRM element to follow a disciplined approach towards strengthening CRM frameworks in commercial banks.
Ownership effects on Credit Risk Management Strategic Decisions
Arora, A. (2013) Investigates the impact of ownership on Customer Relationship Management (CRM) strategic decisions in commercial banks, particularly in India. It finds that while most CRM decisions are not significantly influenced by ownership, public sector banks tend to prefer centralized decision-making structures. Despite similarities in certain CRM aspects between public and private sector banks, differences exist in areas such as delegation of credit approving authority and loan pricing considerations.
The study contributes empirical evidence to the ongoing debate on the influence of bank ownership on CRM decisions. It also provides a detailed examination of CRM strategies in both public and private sector banks within a developing economy context, a previously unexplored area. Understanding the mix of CRM approaches in the Indian banking sector can aid bank management in enhancing overall risk management effectiveness. Moreover, the study identifies areas of weakness that banks can focus on to strengthen their CRM practices. However, limitations associated with questionnaire survey methods, such as response validity and understanding, may affect the reliability of the findings. In conclusion, this research sheds light on the relationship between bank ownership and CRM strategies, offering valuable insights for both academic and practical purposes within the banking industry.
Managing Credit Risk in Foreign Exchange Derivatives
NG KAH HWA & JESSICA LIM(1994)explains the approach to the management of credit risk. In this financial environment, a major concern of banks, banks regulators and other financial institutions is counter-party credit risks. By this is meant the risk which one party to the contract faces if a counter-party defaults on or before the maturity of the contract. A derivative instrument is a contract whose value is derived from the price of the underlying financial asset. For example, if the underlying financial asset is a foreign exchange (forex) instrument, then the derivative is known as a forex derivative, for example a currency swap. Derivative contracts, which are traded outside of exchanges, are known as Over-The-Counter (OTC) contracts. Many of these forex derivatives are traded over the counter, e.g. CME. LIFFE or SIMEX, as opposed to trading on the exchanges. Unlike exchange-traded contracts, these OTC products incur credit risk arising from the potential default of the counter-party, as there are no margin requirements for the latter. In exchange-traded contracts, the exchange is the counter-party. Generally, the failure of the exchange to complete the contract is less likely, as there are financial and regulatory safeguards.
The Impact Of Credit Risk On Bank Profitability In Nigeria
Onyeiwu et al(2020) investigate the impact of credit risk management on bank profitability in Nigeria. The paucity of studies of local inclination on credit risk management vis-a-vis the
dangerous effect on credit risk on bank capital spurred the researcher to embark on an immediate investigation to seek empirical answers. This research reinforces the role of adequate regulatory and economic capital in ensuring the long-term sustainability of Nigeria’s top banks. The influx of new banks in the industry may necessitate tight regulatory beam-light to ensure their risk exposure is moderate in favour of creditors, shareholders, and depositors. There is a commendable success on the IFRS adoption in the banking industry, with a corresponding decrease in non-performing loans across the top banks in Nigeria. However, there are notable worries on the in-built flexibility possessed by banks’ top management to build a bank-specific ECL system in deciding the percentage set aside for loan loss provisions and reporting procedures when there is an excess or a shortage. The overall call is for increased scrutiny by the regulators on banks’ balance sheet and off-balance sheet activities to obtain the true health of banks in the banking system.
Conclusion
Credit Risk Management Framework:
Direct lending activities are perceived to pose the highest credit risk.
The Securitization Ordinance Act, 2002, is favored for managing credit risk.
Credit Risk Policy approval is primarily by the Board of Directors, with centralized management authority at the Head Office level.
Risk rating, alongside credit administration, prudential limits, and loan review, is highly favored for credit risk management.
Prudential limits suggested by the RBI are adhered to, with variations based on bank size.
CRISIL’s models and internally designed models are favored for credit portfolio evaluation.
Off-balance sheet exposure is clearly defined by most banks.
Financial performance, operating efficiency, and management quality are vital for inter-bank exposure evaluation.
Derivative usage for credit risk management is minimal, with standardized approaches preferred for capital charge calculation.
Overall, the Credit Risk Management framework aligns with RBI guidelines, with risk rating being paramount.
Comparison of Public and Private Sector Banks’ CRM Frameworks:
There is no significant difference in the overall strength of the CRM framework between public and private sector banks.
Both sectors are on par in embracing benchmark CRM practices.
Understanding current strengths and weaknesses aids in future decision-making by managers, with policy implications for both sectors.
Relationship Between Credit Risk Management and the Macroeconomy:
Investigates the impact of credit risk management on financial strength measures such as the Tier 1 capital ratio.
Finds a connection between credit migration risk and economic indicators, with implications for future research.
Management of NPAs and Credit Risk in the Banking Sector:
NPAs in private banks show a decreasing trend post-liberalization.
Certain portfolios exhibit inverse or positive relationships with NPAs, highlighting the importance of credit risk management.
Credit risk management is crucial in the deregulated market, with the adoption of international best practices seen as essential for effective risk management.
Model for Credit Risk Management:
A discriminant model is used to compare the performance of credit risk management techniques, aiming to predict defaulters accurately and reduce NPAs.
Risk rating is emphasized as the most important instrument, alongside credit administration, prudential limits, and loan review.
Quantitative Assessment of CRM Framework:
Provides a quantitative measure of the strength of the CRM framework in the Indian banking system.
Allows bank management to gauge CRM practices, identify strengths and weaknesses, and make informed decisions.
Recommendations include regular assessments and cross-sectional comparisons with other economies.
Impact of Ownership on CRM Strategic Decisions:
While CRM decisions are generally not significantly influenced by ownership, public sector banks tend to prefer centralized decision-making structures.
Provides empirical evidence on CRM strategies in public and private sector banks, contributing to the ongoing debate on bank ownership’s influence on CRM decisions.
Management of Credit Risk in Foreign Exchange Derivatives:
Highlights the approach to managing credit risk in Over-The-Counter (OTC) contracts, emphasizing the importance of managing counter-party credit risks.
Impact of Credit Risk Management on Bank Profitability in Nigeria:
Reinforces the role of regulatory and economic capital in ensuring the long-term sustainability of banks.
Emphasizes the importance of scrutiny by regulators on banks’ balance sheet and off-balance sheet activities to obtain the true health of banks in the banking system.
These texts collectively provide a comprehensive overview of various aspects of credit risk management in the banking sector, including frameworks, strategies, and their implications on bank performance and stability.
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ARORA, A. The Impact of Branch Network on Credit Risk Management Practices in Indian Banking Sector. IUP Journal of Financial Risk Management, [s. l.], v. 11, n. 4, p. 31–44, 2014. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=543726f8-9fe7-3c2e-9a56-2eae8f0d0c18. Acesso em: 24 fev. 2024.
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BODLA, B. S.; VERMA, R. Credit Risk Management Framework at Banks in India. ICFAI Journal of Bank Management, [s. l.], v. 8, n. 1, p. 47–72, 2009. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=e9609259-b173-382d-976b-7fd6918772d7. Acesso em: 24 fev. 2024.
GAVALAS, D.; SYRIOPOULOS, T. Bank Credit Risk Management and Migration Analysis; Conditioning Transition Matrices on the Stage of the Business Cycle. International Advances in Economic Research, [s. l.], v. 20, n. 2, p. 151–166, 2014. DOI 10.1007/s11294-014-9459-y. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=f15fcab4-34e0-3947-8baf-b6cd25294d96. Acesso em: 24 fev. 2024.
NANDI, J. K.; CHOUDHARY, N. K. Credit Risk Management of Loan Portfolios by Indian Banks: Some Empirical Evidence. IUP Journal of Bank Management, [s. l.], v. 10, n. 2, p. 32–42, 2011. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=ba9b8597-ca5f-3a87-aa3d-af9337a165ae. Acesso em: 24 fev. 2024.
NG KAH HWA; JESSICA LIM. Managing Credit Risk in Foreign Exchange Derivatives. Singapore Management Review, [s. l.], v. 16, n. 1, p. 33, 1994. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=3d16064f-ece3-3c16-839e-ce00c531e8a1. Acesso em: 24 fev. 2024.
ONYEIWU, C.; AJAYI, G.; OBUMNEKE, M. B. The Impact of Credit Risk on Bank Profitability in Nigeria. Journal of Banking & Financial Economics, [s. l.], v. 1, n. 13, p. 5–22, 2020. DOI 10.7172/2353-6845.jbfe.2020.1.1. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=8feec6b1-e3d7-32dc-a8b1-3e0c51640e71. Acesso em: 24 fev. 2024.
SURESH, N.; KUMAR, S. A.; GOWDA, D. M. Credit Risk Management in Commercial Banks. CURIE Journal, [s. l.], v. 2, n. 4, p. 72–83, 2010. Disponível em: https://research.ebsco.com/linkprocessor/plink?id=e6ed70f6-4cfb-3ffa-bc31-e2b887c0860c. Acesso em: 24 fev. 2024.