Credit Risk Identification And Prevention Of City Commercial Banks

With the accelerating pace of financial reform,commercial banks are facing fiercer competition than ever before.In this case,the continuous scale expansion of commercial banks and the lowering of customer credit evaluation standards in order to maintain the original market share all lead to the rapid expansion of bank credit risk to varying degrees,exposing many drawbacks of the traditional credit risk control mode of commercial banks.City commercial banks,as an important part of the banking industry,play an important role in driving regional economic development.Meanwhile,compared with large state-owned banks and joint-stock commercial banks,city commercial banks are weak in their ability to resist credit risks.Therefore,it is a key practical problem for city commercial banks to explore more perfect and efficient ways to prevent and control credit risks.This thesis takes Shengjing Bank,the largest urban commercial bank in Liaoning Province,as the analysis object to carry out a case study on the identification,prevention and control of credit risk of urban commercial banks.Firstly,this thesis reviews the relevant research on the credit risk of city commercial banks by domestic and foreign scholars and introduces the relevant theories and models of credit risk,explains the rationality of choosing KMV model for credit risk measurement in this thesis and elaborates the KMV model in detail.Secondly,it explains the basic situation,credit risk management principles and main evaluation indicators of Shengjing Bank and analyzes the causes of credit risk of Shengjing Bank.In the empirical study,this thesis selects the financial data of Shengjing Bank from 2015 to 2022 and uses KMV model to analyze the change trend of default distance of Shengjing Bank,and selects seven city commercial banks as the control group to measure default distance,and evaluates the credit risk level of Shengjing Bank from both vertical and horizontal dimensions.After that,this thesis uses the method of multiple linear regression analysis to explore the factors that significantly affect the credit risk level of Chinese city commercial banks,and puts forward corresponding rectification measures for the prevention and control of credit risk of Chinese city commercial banks.By measuring the credit risk of Shengjing Bank,this thesis finds that since the second half of 2020,Shengjing Bank’s credit risk level continues to improve,and its credit risk is at a high level in the industry.At the same time,through multiple regression analysis,this thesis explores four indicators that significantly affect the credit risk level of urban commercial banks--total asset scale,capital adequacy ratio,loan-to-deposit ratio and stock price volatility.Finally,in view of the current situation of the high level of credit risk of Chinese city commercial banks,this thesis points out that city commercial banks should prevent and control credit risk by paying attention to the influence of macro-economy on their own credit risk,actively expanding non-interest business income,implementing credit business chain monitoring,and improving the internal governance mechanism.