Credit Risk Issues Research Articles

Double Literacy, Double Protection?: Minimising Gen Z's Risky Digital Credit Behaviour In Surabaya Through Financial Literacy And Digital Financial Literacy

This study aims to investigate the credit risk issues that Generation Z is facing In Surabaya, particularly digital credit and loans. This study utilises a closed-ended questionnaire to explore Generation Z’s knowledge and awareness of subjective financial literacy, digital financial literacy, and risky credit behaviour, so that the results can reveal the influence of subjective financial literacy and digital financial literacy on risky credit behaviour controlled by gender and financial condition of Generation Z in Surabaya. To the best of the researcher’s knowledge, there are no studies that specifically highlight the influence of subjective financial literacy and digital financial literacy on risky credit behaviour. Based on the results of the multiple linear regression approach, researchers found that subjective financial literacy and digital financial literacy have a significant positive effect on risky credit behaviour, which means that the higher the subjective financial literacy and digital financial literacy, the riskier credit behaviour is minimized, gender has no significant effect on risky credit behaviour, financial condition has a significant negative effect on risky credit behaviour.

A Study on Credit Risk of Small and Medium-sized Logistics Enterprises Based on System Dynamics

The rapid development of small and medium-sized logistics enterprises has also revealed potential credit risk issues. Based on this, this paper constructs a system dynamics model to simulate the key factors affecting the credit risk of small and medium-sized logistics enterprises. Firstly, the paper analyzes the factors affecting the credit risk of small and medium-sized logistics enterprises from multiple aspects such as industry characteristics and sources of risk, and constructs an index system for these factors. Secondly, the paper uses the system dynamics method to build a mechanism model of credit risk for small and medium-sized logistics enterprises, and deeply analyzes the factors affecting the mechanism of these enterprises. Finally, through simulation analysis of examples, the paper identifies key risk factors and proposes effective control measures to improve the overall credit risk situation of small and medium-sized logistics enterprises.

Understanding Credit Risk in Internet Consumer Finance: An Empirical Analysis with a Focus on the Young Generation

In recent years, internet finance has garnered increasing attention from the public. Online lending, emerging within the framework of Internet finance as a pivotal component, has witnessed substantial growth. While online credit, within the realm of Internet finance, presents numerous advantages over traditional lending, it concurrently exposes a plethora of credit risk issues. This study aims to facilitate the effective utilization of online credit tools by the young generation within the context of Internet finance. Additionally, it seeks to ensure the overall stability of the Internet finance environment and mitigate risks for the youth. Given the significance of understanding credit risk management for college students in the age of internet finance, this paper adopts the logistic model to evaluate credit risk in internet consumer finance and provides pertinent recommendations from the perspective of the young generation.

The Effect of Risk Management on the Financial Performances Among Hospitality and Tourism Companies in Malaysia

Purpose: This study explores the effect of risk management on the financial performance of Malaysian hospitality and tourism companies. Theoretical framework: The agency theory and extreme value theory (EVT) were applying in this study. Design/Methodology/Approach: The study population is the public listed companies in Bursa Malaysia. The unit of analysis of this study is the Travel, Leisure & Hospitality Companies listed in Bursa Malaysia. With the purposive sampling method, 29 companies were selected which are suitable for the objective of this study. The secondary data used in this study were derived from the audited financial statements and annual. Findings: The findings indicates that there is insignificant and negative relationship between the risk management and financial performances of Hospitality and tourism Industry in Malaysia and the significantly positive relationship between company size and financial performances of Hospitality and tourism Industry in Malaysia. Research, Practical & Social implications: This study will be beneficial for future researcher and entrepreneurs to have access to this study in order to gain a better understanding of how to take pre-actions before starting a business in order to ensure their success. Policy implications include ensuring that prudential guidelines and other regulations governing the company's operations regarding loan facilities are reviewed periodically to address evolving credit risk issues. Originality/Value: The study provides valuable insight on the effect of risk management on the financial performances among hospitality and tourism companies in Malaysia.

Empirical Test of Credit Risk Assessment of Microfinance Companies Based on BP Neural Network

In recent years, the chaos of internet finance has occurred frequently, especially P2P, with high risks. As a kind of financial innovation, small loan companies are challenging to avoid alone, and the issue of credit risk is also highly valued. This study selects the loan records of a small loan company (a daily loan record from September 1, 2016 to July 1, 2021 has seven indicators, each of which has 21299 data). It uses MATLAB programming to test the correctness of risk indicator selection and the accuracy of BP neural network classification and identification results. This study obtains the corresponding risk value. According to the corresponding risk value, the newly applied loans are classified, that is, rated, to verify the effectiveness and applicability of this method. Therefore, BP neural network has strong applicability, generalization ability, and portability and is an effective method for small loan companies to guide credit risk assessment.

Credit Risk Prediction Model for Listed Companies Based on CNN-LSTM and Attention Mechanism

The financial market has been developing rapidly in recent years, and the issue of credit risk concerning listed companies has become increasingly prominent. Therefore, predicting the credit risk of listed companies is an urgent concern for banks, regulators and investors. The commonly used models are the Z-score, Logit (logistic regression model), the kernel-based virtual machine (KVM) and neural network models. However, the results achieved could be more satisfactory. This paper proposes a credit-risk-prediction model for listed companies based on a CNN-LSTM and an attention mechanism, Our approach is based on the benefits of the long short-term memory network (LSTM) model for long-term time-series prediction combined with a convolutional neural network (CNN) model. Furthermore, the advantages of being integrated into a CNN-LSTM model include reducing the complexity of the data, improving the calculation speed and training speed of the model and solving the possible lack of historical data in the long-term sequence prediction of the LSTM model, resulting in prediction accuracy. To reduce problems, we introduced an attention mechanism to assign weights independently and optimize the model. The results show that our model has distinct advantages compared with other CNNs, LSTMs, CNN-LSTMs and other models. The research on the credit-risk prediction of the listing formula has significant meaning.

CAMEL Rating System and Financial Performance of Islamic Banks in Kenya

Kenyan Islamic banks are facing a myriad of credit risk issues adversely affecting their financial performance. Importantly. CAMEL rating system has been identified as an effective approach when making credit risk management decisions. However, most of the research associating financial performance of Islamic banks has ignored issues arising in emerging market such as Kenya, a knowledge gaps this research locked. Quantitative approach was utilised while adopting correlational research design. The research had its target population as being the three (3) Islamic banks which had been operating in Kenya between the year 2012and 2020 where census was employed. The researcher compiled financial data from secondary data for between 2012 and 2020. Quantitative analysis approach was applied in the analysis to yield respective statistics; descriptive and inferential. The study concludes that; capital adequacy has a statistically significant positive, assets quality has a statistically significant negative, management efficiency has a statistically significant positive, earnings ability has a statistically significant positive, and liquidity has significant negative, effect on financial performance of Islamic banks in Kenya. Accordingly, CAMEL rating model is appropriate for assessing financial performance of Islamic bank in Kenya. The study recommends that the Kenyan Islamic bank, should employ the optimal investment strategy for capital adequacy determination, manage their assets, enhance their management efficiency capability, improve their earnings ability, and strictly adhere to recommended liquidity levels. The research recommends that Kenyan IBs should be employing CAMEL rating model on yearly basis to identify elements requiring special attention.

The determinants of banks' credit risk: Review of the literature and future research agenda

AbstractBanks' credit risk, mostly conveyed by the level of non‐performing loans (NPLs) and considered as a prominent threat to the banking sector stability, has been widely discussed among researchers and policymakers. Given the growing body of literature on this topic, this paper aims to provide a structured review of literature on the determinants of NPLs with a focus on the current dynamics of the field. This study discusses the main theories that shaped the debate on NPLs and their bank‐specific, macroeconomic and industry‐related determinants. A thorough understanding of these latter would enable policymakers, regulators and bank managers to anticipate banks' failures and, academicians to advance their research. To facilitate further knowledge in this field, this paper reviews 69 studies published between 1987 and 2019 in 40 peer‐reviewed journals. We argue that despite the extensive empirical and theoretical work accomplished over the last decades, the issue of credit risk remains an unsolved line of inquiry, which leaves ample room for critical debates. Beside mapping the emerging discourse on this area, this study proposes a promising future research agenda to guide research advancement.

Revisiting the Role of Bank’s Capital, Loan Loss Provisioning and Risky Assets to Credit Risk in Malaysia: An Application of Dynamic Heterogenous Panel Technique

The issue of credit risk among financial institutions has become de rigueur matter for many years particularly among risk managers, market players, regulators and academia in Malaysia. The negligence over specific credit risk factors in credit risk management could herald to the balance sheet loss as what happened in the US mortgage prime crisis. This paper is presented primarily to investigate the long run and short run relationship between credit risk and bank specific factors such as capital adequacy(CAR), loan loss provisioning(PROV) and risky assets (RWA) across different types of banks comprising Islamic banks, Islamic banking windows, commercial banks and investment banks in Malaysia. The application of heterogeneous panel model namely Pooled mean group (PMG) will allow for heterogeneity effect across non-homogenous banking operations. From our findings, it is evident that an increase in capital level reduces default problem for Islamic banking windows. Further, we find positive association between RWA and NPL and also between PROV and NPL which implies that loan loss provisioning could be important signal of risk taking behaviour. Besides that, our results also suggest that the nature of credit risk among Islamic banks in Malaysia are still following market force given by the fact that their credit risk management routines still follow the conventional practices.

Analytic of B2C E - Commerce Credit Mechanism Mixed Strategy Risk Behavior Based on Logical Game Petri Nets

B2C is a commercial retail model of e-commerce for selling products and services directly to consumers. To solve the credit risk issues in B2C e-commerce, in this paper, a credit risk game mechanism is proposed based on game theory and logical Petri nets theory. First, by combining logical Petri nets with game theory, a theoretical modeling method called the logical game Petri nets is proposed. To characterize the utility that each body gained during the competition processes using the least square method, utility functions that describe the relationships between enterprises in different business modes are derived; next, a logical game Petri net model to specify the interactions among different bodies in the enterprise competition module is constructed. To analyze the behavior of the competition module, a reachable marking graph for this logical game Petri net model is established. According to this reachable graph, a utility matrix is subsequently designed to obtain the maximum expected utility for the bodies; finally, through analysis of the logical game Petri nets model for the enterprise competition module, the local optimal utility, as well as the global optimal utility of the individuals and groups, can be guaranteed.

Credit risk management at retail in Mexico: An econometric improvement in the selection of variables and changes in their characteristics

The early prediction of bad debtors for revolving credits in Mexico is a relevant issue today. The credit behavior econometric model proposed considers the changes in the characteristics of the consolidated accredited and provides better results than those obtained with the methodology utilized by the CNBV on provision matters. The results obtained show that the possibility of replacing the current model, minimizing the expected loss and increasing the ROA per financial institution at a national level by 2.20%, complies with the methodological criteria and the statistical tests in accordance with the Compiled Banking Regulation and Basel II guidelines on credit risk issues.

Financial ratios and prediction on corporate bankruptcy in the Atlantic salmon industry

ABSTRACTThis article addresses the issue of credit risk in the salmon industry. During the period 2000–2002 the Norwegian salmon industry witnessed a period of low prices leading to a wave of defaults and bankruptcies. The consequences were large monetary losses for both investors and banks, highlighting the importance of early detection of failing firms. Using financial ratios measuring the firms’ financial status prior to this event, two credit risk models are developed; one using logit regression and the other Classification and Regression trees. The performance of the two models developed is compared to a cross-industry benchmark model developed by the Norwegian Central Bank. The model estimated on industry data is better at separating between companies with high and low credit risk in the salmon industry compared to the benchmark model.

Rating as a Useful Tool for Credit Risk Measurement

Abstract The present contribution deals with the issue of credit risk and rating, which is one of the useful tools for measuring to credit risk. Rating and credit risk are closely linked. In general, we can define credit risk as the probability of loss from a debtor's default. While rating is like a meter, by which it should be possible to compare two borrowers and determine, which of them has more likely, that in the end he pays for his obligation. In the rating process are systematic processed information about enterprise's developments from its past and the future outlook. The rating of the enterprise is carried out by taking into account quality criteria (“soft facts”) and quantitative criteria (“hard facts”). Hard facts are calculated from the financial statements of the company through the implementation of financial-economic analysis. So, hard facts provide a reliable statement about of the financial stability of the company and its financial health. The values of indicators which are achieved are combined according to their significance and then they are transferred to the internal rating scale. Then this value is used to express quantitative rating of enterprise. Present contribution is going to deal with calculation of hard facts and quantitative criteria for rating measurement. Rating assignment is going to be carried out on a model example. Hard facts are going to be determined based on the financial statements of the selected company and the rating is going to be assigned according to the rating scale which is going to be established for model example.

10.5937/skolbiz1-5797 = Theoretical concept of credit risk management

With the development of the banking business and the economy, exposure to different types of risk becomes greater. Identifying all risks and adequate measures have become an extremely important factor in business success in the increasingly complex economic conditions. Risks in business, in the last ten years have become the burning issue in debates among the scientific experts. With the aim of stable development of its business and equal participation in a large competitive market, primarily in order to protect its depositors and preserve system stability and liquidity, banks have to incorporate into their strategic goals the strategies of banking risks. Credit risk is of great value within the overall risks that accompany the business activity of banks, economy, and other forms of business organization. Its nature and presence in all segments of the business activities speak enough about its importance and the need for its management. Permanently growing trend of credit risk is a reality faced by not only the banking organization, but also the subjects in the economic and non-economic sector, which makes the issue of credit risk extremely important and relevant. The subject of this paper is a theoretical analysis of credit risk in banking business. Banking operations are increasingly exposed to credit risk, which indicates the inability of banks to settle their claims based on previously approved loans, and this is the case-in-point for this specific research subject.

On Consumer Credit Outcomes in the U.S.-Mexico Border Region

The ease in mobility of people across the U.S.-Mexico border region provides a natural setting for analyzing the role of economic interdependency on consumer credit outcomes. Since the U.S. and Mexican economies are not entirely synchronized and have different growth rates, the growing Mexican border economy is likely to increase the consumption of U.S. goods and services in the region, and provide additional job opportunities to the U.S. border residents. Thus, the effect of being located at the border (‘border effect’) might reduce default and bankruptcy in the U.S. However, if both economies are nearly perfectly correlated, then the ‘border effect’ is likely to be insignificant. Our results are consistent with the border effect lowering the rate of bankruptcies and mortgage defaults in the U.S. counties that share a border with Mexico. An increase in the level of economic interdependency, as measured by the differential economic growth between Mexican municipalities and their sister U.S. county, decreases the bankruptcy rates in the U.S. border region. Overall, this research helps understand credit risk issues in the U.S.-Mexico border region.

On Consumer Credit Outcomes in the U.S.-Mexico Border Region

The ease in mobility of people across the U.S.-Mexico border region provides a natural setting for analyzing the role of economic interdependency on consumer credit outcomes. Since the U.S. and Mexican economies are not entirely synchronized and have different growth rates, the growing Mexican border economy is likely to increase the consumption of U.S. goods and services in the region, and provide additional job opportunities to the U.S. border residents. Thus, the effect of being located at the border (‘border effect’) might reduce default and bankruptcy in the U.S. However, if both economies are nearly perfectly correlated, then the ‘border effect’ is likely to be insignificant. Our results are consistent with the border effect lowering the rate of bankruptcies and mortgage defaults in the U.S. counties that share a border with Mexico. An increase in the level of economic interdependency, as measured by the differential economic growth between Mexican municipalities and their sister U.S. county, decreases the bankruptcy rates in the U.S. border region. Overall, this research helps understand credit risk issues in the U.S.-Mexico border region.