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

Along with the economic globalization,especially the rapid development of financial globalization,China's financial market is influenced by many factors,the instability is obvious,while China is currently in the stage of rapid improvement of the marketization of interest rate,commercial banks are facing opportunities and challenges,especially the credit risk of the hitherto unknown challenge.At present,the environment of commercial banks is becoming more and more competitive.How to scientifically and effectively manage the credit risk in the credit business is directly related to the healthy development of commercial banks.At the stage of reform and development,commercial banks,the original credit risk management system has been difficult to apply,the traditional analysis method can not meet its rapid development in the new situation.Based on this,this paper based on the basic characteristics of China's commercial banks,trying to study the neural network method is applied to the study on credit risk management of credit business,provide a kind of effective risk assessment techniques to.This paper first gives an analysis and demonstration of the commercial bank credit risk assessment model of existing,based on defining the connotation of the commercial bank credit risk,the credit risk factors of influence deeply,and summed up the credit risk management system is not enough.Further,this paper extracts 17 indicators from the five levels,and the index system into the BP neural network,establishing a set of commercial bank credit risk assessment model.Finally,through a large of data,used MATLAB software to empirical analysis,The result shows that the risk evaluation model established in this paper has higher discrimination accuracy,in practice it is helpful to the commercial banks on credit business credit risk evaluate,provides reliable basis for credit risk management,it has certain research value.