Evaluation On Financial Credit Risk Of Supply Chain In Commercial Banks

According to the "Chinese bankers survey report (2014)" published by China Banking Association and Price Waterhouse Coopers,in recent years,bankers continuously loans to small and medium-sized enterprises,and listed them as a new territory of commercial bank in customers and business competition.As one of the most important innovation mode, supply chain finance attract extensive attention by Chinese banking industry and will serve as a key business to expand the layout.However,banks,in reality,carrying out such operations will inevitably encounter various problems,one of the largest assessment of them is credit risk.This paper will study the credit risk of supply chain finance.Firstly,This paper introduced the related theory of supply chain finance and credit risk assessment.Then using the game simulation analysis method to identify the credit risk factors,and establishing the corresponding evaluation index system.After this step,this paper use the correlation method and differential analysis method to delete and optimize index.Finally,due to the the lack of data and large index dimension,this paper choose the most suitable empirical analysis method of the support vector machine(SVM).After series steps—data normalization, parameter optimization and kernel function selection,SVM made satisfactory results.This study showed that using the SVM method to evaluate the credit of supply chain finance has high accuracy and strong generalization ability,and the credit risk of supply chain finance platform,which is selected as the empirical object,is at a lower level. The research process,index system,the application of this method also has a good reference significance for credit risk assessment in commercial banks.