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This paper attempts to analysis the credit risk at the angle of industrial and macroeconomic factor using grey incidence analysis method.

Credit asset quality problem is one of the obstacles limiting the further development of commercial banks; the research on credit risk becomes an important part of the implementation of a commercial bank's risk management. Different industries may have different effects on the credit risk of commercial bank. This paper proposes finding out the different incidences between industries and credit risk, as well as macroeconomics. Incidence identification method is established to investigate whether the industry and macroeconomic factor could affect an impaired loan ratio of a bank using the grey incidence analysis method.

The results indicate that the impaired loan ratio differs with diverse industry's influence and the macroeconomics also affect it. From the angle of the industry, the result can also determine the risk deviation scope in the grey risk control process which offers new content and ideas within the grey risk control.

Under the guidance of the principle of “differential treatment, differential control”, this research will help to strengthen the implementation of differentiated credit policy, focus on guiding and promoting the optimization of credit structure, so as to maintain a reasonable size of credit facilities and build a steady currency credit system.

The paper succeeds in finding the top five influent industries compared with others by using one of the newest developed theories: grey systems theory.

The purpose of this paper is to identify any differences between the Islamic and non‐Islamic banks in the UAE on credit risk management.

The study uses survey based methodology for data collection. The sample for the study consists of six commercial banks from UAE with three non‐Islamic and three Islamic banks and with 148 credit risk managers as respondents for the survey. The study aims to investigate factors which distinguish between Islamic and non‐Islamic banks in UAE. This is achieved by fitting a binary logistic regression model.

The study shows that the managers in Islamic banks now do not rely only on personal experiences and simple credit risk analysis. The Islamic banks appear also to be developing and practising the newer and robust techniques, in addition to traditional methods, to manage their credit risk in UAE compared to non‐Islamic banks, which indicates a possibility of further improvement in their credit risk management.

The paper uses questionnaire‐based methodology, which has not been used previously in the UAE financial sector, as well as in studies of credit risk management. Therefore, this research could become the cornerstone of further academic research in other developing countries using this methodology.

The authors provide the reader with a simple introduction to credit derivatives. The article includes a broad overview of the market, estimates of the global market size, and a description of the most widely used products.

Proposes to investigate the current practices of credit risk management by the largest US‐based financial institutions. Owing to the increasing variety in the types of counterparties and the ever‐expanding variety in the forms of obligations, credit risk management has jumped to the forefront of risk management activities carried out by firms in the financial services industry. This study is designed to shed light on the current practices of these firms.

A short questionnaire, containing seven questions, was mailed to each of the top 100 banking firms headquartered in the USA.

It was found that identifying counterparty default risk is the single most‐important purpose served by the credit risk models utilized. Close to half of the responding institutions utilize models that are also capable of dealing with counterparty migration risk. Surprisingly, only a minority of banks currently utilize either a proprietary or a vendor‐marketed model for the management of their credit risk. Interestingly, those that utilize their own in‐house model also utilize a vendor‐marketed model. Not surprisingly, such models are more widely used for the management of non‐traded credit loan portfolios than they are for the management of traded bonds.

The results help one to understand the current practices of these firms. As such, they enable us to make inferences about the perceived importance of the risks. The paper is of particular value to the treasurers intending to better understand the current trends in credit risk management, and to academics intending to carry out research in the field.

A correlation has been shown in the literature between credit constraints and the adoption of agricultural technologies, technical efficiencies and measures for adapting to climate change. The relationship between credit constraints, risk management strategy adoption and income, however, is not well understood. Consequently, the purpose of this study was to investigate how credit constraints affect the income and risk management practices adopted by Northern Nigerian maize farmers.

Cross-sectional data were collected from 300 maize farmers in Northern Nigeria using a multi-stage sampling technique. Descriptive statistics, seemingly unrelated regression and double hurdle regression models were the analysis methods.

The results showed that friends and relatives, banks, “Adashe”, cooperatives and farmer groups were the main sources of credit in the study area. The findings also revealed that the sources of risk in the study area included production risk, economic risk, financial risk, institutional risk, technological risk and human risk. In addition, the risk management strategies used to mitigate observed risks were fertilizer application, insecticides, planting of disease-resistant varieties, use of herbicides, practising mixed cropping, modern planning, use of management tools as well as making bunds and channels. Furthermore, we found that interest rate, farm size, level of education, gender and marital status were significant determinants of statuses of credit constraints while the age of the farmer, gender, household size, primary occupation, access to extension services and income from maize production affected the choice and intensity of adoption of risk management strategies among the farmers.

The study concluded that credit constrained status condition of farmers negatively affected the adoption of some risk management strategies and maize farmers’ income.

The study concluded that credit constrained status condition of farmers negatively affected the adoption of some risk management strategies and maize farmers’ income. It therefore recommends that financial service providers should be engaged to design financial products that are tailored to the needs of smallholder farmers in the study area.

This paper incorporates the role of constraints in influencing farmers’ decisions to uptake credits and subsequently their adoption behaviours on risk management strategies. The researcher approached the topic with a state-of-the-art method which allows for obtaining more reliable results and hence more specific contributions to research and practice.

This study aims to determine the effect of bank ownership on the credit risk of Indonesian Islamic local banks (ILBs).

This study uses the system generalized method of moments (GMM) estimation technique with a sample of 155 Islamic local banks in Indonesia from 2012 to 2019.

The results show that commissioner board (D.COW) ownership has a negative effect on credit risk. This indicates that an increase in the number of shares of Islamic local banks owned by the commissioner board reduces credit risk. On the other hand, government ownership (D.GOW), the Sharia supervisory board (D.SOW) and the director board (D.DOW) do not affect credit risk.

The government, Sharia supervisory board and director board need opportunities to easily own more Islamic local bank shares. Therefore, the provisions regarding the share ownership rights of the government, Sharia supervisory board and director board need to be improved to increase their role in reducing credit risk.

Previous researchers have not studied the effect of government ownership, the commissioner board, the Sharia supervisory board and the ownership of directors on credit risk at the ILB in Indonesia.

With the help of financial engineering – and equipped with the modern technique of risk management – securitisation was supposed to identify and evaluate risks and parcel them out to informed parties who could bear them. In hindsight, we can see that this somewhat simplistic thesis – espoused by market participants as well as the academic promoters of modern techniques of risk management – seemed to promise a great deal more than it could ultimately deliver. At this juncture, however, the danger of regulatory over-reaction – which might be throwing the baby (financial innovation) out with the bath-water (overlooking/under-pricing of risk) – is very real and (in my view) calls for policy measures of this sort should be resisted firmly not only by market participants but also by regulators. This is not to say that regulation should be seen as immune from responsibility in the unfolding of the current credit crisis (quite the opposite would more likely be closer to the truth). As we shall see below (Section “Financial Crisis and Credit Ratings Debacle in SF”), the best risk-management practices – and related tools available before the crisis – provided enough ammunition to caution against the uncertainty surrounding risk assessment for some categories of SF products. However, the increasing complexity embedded in an increasing number of deals did provide genuine new challenges even to best risk-management practices.

The purpose of this research is to examine the connections between liquidity risk, credit risk, and bank profitability in India.

In order to examine the interlinkage between liquidity risk, credit risk, and profitability of banks in India, the researcher has gathered data from all commercial banks in India from 2004–2005 to 2020–2021. The data sources included in this study encompass the International Country Risk Guide, World Development Indicators and Reserve Bank of India (RBI). Seemingly Unrelated Regression (SUR) has been utilised for the study.

Findings of this research identified that liquidity risk is inversely proportional to credit risk. Return on assets (ROA) and return on equity (ROE) are both impacted negatively by liquidity risk. ROA is impacted positively by credit risk, while ROE is impacted negatively by it. The profitability of banks is harmed by the interaction between liquidity risk and credit risk. It also shows that law and order, are beneficial to bank earnings and risk management. The capital risk-adjusted ratio has a negative relationship with bank profitability, indicating the need for better capital allocation.

The originality of this work lies in its unique contributions, It emphasises explicitly the Indian context, thereby providing insights tailored to this particular setting. It employs the SUR methodology, a statistical approach allowing for a more comprehensive data analysis. Additionally, it identifies and explores interaction effects, which can shed light on the complex relationships between variables.

Introduction: Commercial banks play a vital role in the global economy, facilitating economic growth and providing essential financial services. As key intermediaries between savers and borrowers, these institutions operate in a dynamic and complex environment characterised by various risk factors that can significantly impact their profitability and overall stability. Understanding the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability is crucial for effective risk management strategies and the development of appropriate regulatory frameworks.

Purpose: Commercial banks play a critical role in the global economy by facilitating economic growth and providing financial services. This study examines the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability in commercial banking.

Methodology: The sample consists of licenced scheduled commercial banks on the Bombay Stock Exchange (BSE) from 2015 to 2022. Using the Smart PLS-SEM 3.0 path analysis technique, the study evaluates the combined influence of these risk factors on profitability and provides evidence-based recommendations for risk management strategies.

Findings: The findings can assist banks in enhancing their risk management practices, and regulators in developing appropriate regulatory frameworks. By understanding the key risk factors and their impact on profitability, banks and regulators can mitigate risks, enhance transparency, and promote stability within the banking sector.

Significance/value: The value of this study lies in its focus on the interconnectedness of risk factors, profitability, and the potential implications for decision-making, risk management strategies, regulatory frameworks, and the overall stability of the commercial banking sector.