Research On Credit Risk Evaluation Of Commercial Bank's Supply Chain Finance Business

In recent years, GDP created by China's small and medium enterprises(SME) has promoted the rapid development of China's economy, and the financing difficulties of SMEs has always been an important obstacle to the development of small and medium enterprises. In recent years, the supply chain financial service has been raised gradually, and has been paid attention by commercial banks and financial institutions. To a certain extent, supply chain finance has come to an effective result to solve the high threshold for SMEs. Supply chain finance is a significance for commercial banks to expand the new business, but the risk assessment system for Supply Chain Finance has not yet formed. Although Supply Chain Finance business can help commercial banks reduce the loan default risk, there still hides new financial risks by its own characteristics. Based on the development of the supply chain finance business in the bank, this paper studies the credit risk assessment of the supply chain finance based on the existing credit risk evaluation theory and model.This paper analyzes the detailed characteristics of the supply chain finance, the basic theory of financial risk, and the current domestic and foreign research on financial risk measurement methods, compares the advantages and disadvantages of each model of supply chain finance business risk application. Logistic regression model is more suitable for quantitative risk assessment of supply chain financial services, and can be used to extract the key indicators of the impact of supply chain finance. In the construction of the model, the selection of indexes is analyzed from four aspects:the core enterprise, the small and medium-sized enterprise, the logistics enterprise and the supply chain. In the empirical process, using principal component analysis and factor analysis, the independent variables are screened to overcome the data of the co linearity, so that the evaluation results are more scientific and objective. The empirical result showslogistic model has a high accuracy rate in the credit risk evaluation of supply chain finance, and found the specific factors affecting the supply chain finance credit risk. This model can be used in the actual case, providing a tool for banks in the credit loan decision. This paper also suggests establishing supply chain financial risk management and perfecting system, and put forward some solutions to help commercial banks develop supply chain finance in an improving operating system and safe and sound environment.