Credit Risk Assessment Of C Bank Based On KMV Model

Credit risk is the most important risk in the financial industry,and it affects all aspects of economic life.In terms of credit risk measurement,most commercial banks in China adopt traditional qualitative analysis and expert experience judgment.In Western countries,the risk measurement of commercial banks is relatively mature,ranging from qualitative analysis to quantitative analysis,from the credit risk measurement of individual assets to the trend of credit risk measurement of portfolios.In 2004,the International Banking Regulatory Commission announced the Basel New Capital Accord,whose core content is the internal rating method.The New Basel Accord allows banks to use internal models to measure credit risk.Therefore,adopting a suitable risk measurement model is of great significance for improving the credit risk management level of commercial banks.This paper takes C Bank as a sample and analyzes the measurement and control of bank credit risk by combining qualitative analysis with empirical research.First of all,the article summarizes the study of credit risk by Chinese and foreign scholars.It also introduces the credit risk management of commercial banks based on Basel and the application of Basel in China.Secondly,it studies the causes and influencing factors of the credit risk of commercial banks in China,and takes C Bank as an example to analyze the internal and external factors that generate credit risks.Thirdly,the basic ideas,assumptions and calculation steps of the KMV model are expounded,and the credit risk of 33 listed companies of C Bank is empirically analyzed based on the KMV model.The research shows that:1.The data selected by the KMV model is the stock market data of listed companies.The data is relatively real and easy to obtain.The stock market data can comprehensively;fully and accurately reflect the current credit status of the enterprise,and is a risk measurement suitable for banks.model.2.The financial data of 33 listed companies in 2017 and 2018 were measured by KMV,and their default distance and expected default rate were measured and compared with the bank's internal customer ratings.Through comparison between the two,it is found that the KMV model and C Bank internal rating method have similarities and differences in evaluating customer default probability,and KMV can effectively correct the deviation of internal rating results.3.through empirical analysis,it is found that 33 listed companies have good overall credit and controllable risks,but there are still 4 short-term default distances,and the risk of default is relatively large.This paper suggests that if the KMV model is used in combination with the internal rating method,the dynamic and timeliness of C Bank risk monitoring can be strengthened,and C bank's credit risk management capability can be strengthened.The paper also proposes:1.Constructing a comprehensive coverage credit rating system;2.Using the KMV model to continuously optimize internal ratings;3.Establishing and applying a risk portfolio risk management model with a risk measurement model;4.Applying big data and labor Intelligent risk control technology;5.Establish credit risk management organization system;6.Create countermeasures for external environment such as credit risk management.