Credit Risk Assessment Of SMEs From The Perspective Of Supply Chain Finance

Benefiting from the correct guidance of national policies,small and medium-sized enterprises have become an important subject for the implementation of mass entrepreneurship and innovation,which is of great strategic significance to national economic and social development,but the problem of financing difficulties for small and medium-sized enterprises still exists.Supply chain finance as a financing model that has been pinned on high hopes in recent years,will become a major breakthrough for small and medium-sized enterprises to solve the problem of financing difficulties and financing difficulties,thanks to the rapid development of the manufacturing industry,China’s supply chain finance continues to innovate,in just a dozen years from scratch,opened up its own unique development model and development path.As a new financing model,supply chain finance has been accompanied by credit risk problems while alleviating the difficulty and high cost of financing for small and medium-sized enterprises.Based on the supply chain finance model,this paper collects the diversity and complexity characteristics of the influencing factors of credit risk under the supply chain finance model by comparing the differences with the characteristics of the traditional financial model,and selects the perspective of supply chain finance to study credit risk.Taking the small and medium-sized enterprises with relatively perfect development in supply chain finance in the two major sectors of small and medium-sized sectors and Chi Next as the research objects,indicators including financing enterprise indicators,core enterprise indicators,supply chain financial status indicators and industry background macro environment indicators were selected.After that,after the correlation test and principal component analysis and other methods of screening indicators,33 indicators were finally retained to establish a credit risk index system.Eighty small and medium-sized enterprises with low credit risk and 43 small and medium-sized enterprises with high credit risk impact were selected,and the common factor was first extracted by factor analysis,and a logistic regression model was established on this basis.In order to compare the prediction results of multiple models and combined models,this paper uses SVM support vector machine model and Logistic-SVM combination model to analyze the credit risk of SMEs under supply chain finance.The empirical results can be seen: first,the logistic regression model shows that the default risk of financing enterprises is related to the profitability,development ability,solvency and historical credit history of financing enterprises,as well as the operating ability of core enterprises;Second,by comparing the three methods,it can be seen that the prediction results of SVM model are better than those of Logistic regression model.Third,by comparing the two types of errors made by the combined model prediction results with the two types of error results made by the single model prediction results,it can be concluded that the combined model has better effectiveness than the two single models in credit risk assessment prediction,and the prediction accuracy of the combined model is higher.Finally,starting from the model conclusion,the return index is based on the current situation,and targeted suggestions are put forward for relevant departments,which provides certain ideas and reference significance for the credit risk assessment of SMEs under the supply chain finance model.