Study On Credit Risk Evaluation Of Supply Chain Finance Based On The Theory Of BP Neural Network

In recent years, small and medium-sized enterprises (SMEs) which accounted for more than90percent of the total number of enterprises in China plays an irreplaceable role in the development of China’s national economy. They promote fair competition among enterprises, increase employment opportunities; they even played an important role in maintaining social stability. However, the SMEs’access to credit to support their developments is very disproportionate to their social contribution. It has become the main problem and bottleneck of the funds to hinder the development of SMEs. Supply chain finance business is tailored to the new mode of financing for SMEs.This paper studies from the point of supply chain financing credit risk assessment. The paper first proposes the background of the study and outlines the current status of research in this field at home and abroad. Then it points out the inadequacies of the existing research results. On this basis, it establishes the research emphasis of the paper. Secondly, this paper discusses the importance of credit risk assessment in risk management and control of the supply chain financing business; definite the concept of supply chain financing of commercial bank credit risk; presents the theory of the BP neural network, as well as the construction of the supply chain financing business credit risk assessment system. On the basis of research results of domestic and international scholars in the field of supply chain finance, the paper summarizes the entire financing processes in the supply chain finance business and presents the28risk impact factors with correlation analysis and discernment analysis. The establishment of the supply assessment is the core of supply chain financing business risk management and the emphasis of this study. This paper first analyzes the advantages of the evaluation of supply chain financing credit risk using BP neural network, and then builds the BP neural network model to determine the network topology, neuron excitation function, the network learning algorithm and network the initial parameters in order to establish the supply chain financing credit risk evaluation model. On this basis, through the use of query publicly available data combining the method of questionnaire, the paper collects13sample of the supply-chain financing business and normalizes them. According to the needs of research, this paper randomly selects data of10samples as training samples and the remaining three sets of data as test samples. Finally, the paper simulates the training samples using the neural network toolbox of MATLAB7.0platform for supply chain financing credit risk assessment model and test samples to test the validity of the model.This paper focuses on the construction of credit risk assessment system of the supply chain financing of commercial banks, and builds an assessment system model which has a good ability to assess credit risk of supply chain financing business based on BP neural network with more fully Empirical Analysis of verification. We believe that with continuous improvement and application the model provide reference for commercial banks to reduce credit risk of the supply chain financing business and has a strong practical significance.