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

Exploration of Financial Market Credit Scoring and Risk Management and Prediction Using Deep Learning and Bionic Algorithm

The purpose is to effectively manage the financial market, comprehensive assess personal credit, reduce the risk of financial enterprises. Given the systemic risk problem caused by the lack of credit scoring in the existing financial market, a credit scoring model is put forward based on the deep learning network. The proposed model uses RNN (Recurrent Neural Network) and BRNN (Bidirectional Recurrent Neural Network) to avoid the limitations of shallow models. Afterward, to optimize path analysis, bionic optimization algorithms are introduced, and an integrated deep learning model is proposed. Finally, a financial credit risk management system using the integrated deep learning model is proposed. The probability of default or overdue customers is predicted through verification on three real credit data sets, thus realizing the credit risk management for credit customers.

Analysis of Credit Risk, Intellectual Capital and Financial Performance of Listed Deposit Money Banks in Nigeria

This paper examined the effects of credit risk, intellectual capital as well as credit risk moderated by intellectual capital on financial performance of fifteen listed deposit money banks in Nigeria (DMBs) from 2007 to 2016. Data were sourced from annual reports of banks and Nigerian National Bureau of Statistics and analysed using Generalised Method of Moments (GMM). The study finds that credit risk index by loan loss ratio negatively affects financial performance of the sampled banks; while capital employed efficiency, loan loss provision moderated by intellectual capital, capital adequacy ratio, income and diversification have positive relationship with banks’ financial performance. Thus, the study recommends that banks should strengthen their credit risk management culture to ensure prompt repayment of loans. The banks should operate within the required capital adequacy ratio to serve as buffer against loan loss provisions provided by the Central Bank of Nigeria. A strong credit risk management culture should be embedded within intellectual capital structure of banks, where all persons at all levels appreciate and understand the banks’ risk management policies as well as strategies and incorporate same into decision-making and business processes.

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.