Research On The Credit Risk Evaluation Of Commercial Bank Based On Neural Network

Credit risk is one of the most important risks that the financial institutions face. As the economic globalization process accelerated, credit risk management in the past 20 years has made tremendous progress. The credit risk management in developed commercial banks is more mature and more mature in practice and theory corresponding system. Credit risk analysis adopts new techniques day by day. By comparison, China commercial banks'credit risk management system is not perfect and management technology is relatively simple, it still can not meet the commercial banks'requirements to manage credit risk.The development of commercial bank plays an important role in the whole economy development. The credit risk management in developed commercial banks is more mature but premature in our country. So this paper starts from the research background of credit risk, studying and remarking on the research status of domestic and overseas'finding the drawback of present research as for which is the stressed point of this paper. Then this paper demonstrates the importance of credit risk evaluation to credit risk management,the definition to the related conceptions of commercial bank's credit risk. What's more, it demonstrate the theory foundation of credit risk and BP neutral network,the necessity of building credit risk evaluation system. Secondly, it adopts the overseas scholars'research result and S&P credit corporation. Basing on the systematic and profitable characteristics, it designs the credit risk evaluation index system of the commercial bank. The evaluation index system contains the enterprise's aptitude, the enterprise loyalty,the enterprise scale, the debt liability, the profitability and the grow ability, and all these index is make up of second index, including pay back status, net asset's yield and other 24 index. Basing on these indexes and BP neutral network method, the paper establishes the credit risk evaluation model of the commercial bank. Through the T-test and factor analysis method, we know that the nine indexes including debt payback period and ratio,the whole asset's profit rate,net profit increase rate have statistical meaning. At last, the author collects 161 loan operation of one commercial bank and analyzes it by the methods of the above. It uses the 3sigma evaluation rule to determine the initial customer's credit level and uses the Matlab to test the model. This article primarily studies how to build index system to evaluate credit risk of commercial bank, which is based on BP neutral network. The paper also use the index system to demonstrate a practical model. All of these is helpful for commercial bank to lower the credit risk.