Research On The Credit Risk Evaluation Of Small And Medium-sized Enterprises In The Supply Chain Financing Based On BP Neural Network

Small and medium-sized enterprises in the national economy plays a very important role, is the main driving force of the national economy.Commercial Banks in the credit markets put the SMEs to the place of high profitability and high risks due to the series of problems such as the high unsystematic risks, poor information transparencies, high moral hazards, poor management standardization and the lack of core competence, the small average scale.The problem of financing has been the major impediment to the development of SMEs.However, the practices of supply chain financing in developed countries and domestic practices provide the possible solutions to solve the financing problem of SMEs.The key problems encountered in the development of commercial bank in supply chain financing business are about the credit risks.The purpose of this study is to explore that whether the credit risk evaluation of enterprises in the supply chain financing is effective or not.This article is a research about the evaluation of credit risk of enterprises in supply chain financing based on the BP neural network.The full text altogether is divided into five parts.The first part reviews the research background, significance and research status at home and abroad, the methods and innovation points.The second part summarizes the supply chain financing credit risk theory, mainly discusses the supply chain finance,the classification of supply chain financing, the connotation, measurement,evaluation of the credit risk of supply chain financing, as well as supply chain financing risk relationship with the credit risk of the enterprise in supply chain financing.The third part is about the construction of BP neural network model, including the purpose to choose the method,the profiles and the algorithm of BP neural network.The fourth part mainly carries on the empirical analysis. During Empirical study,collecting 30 samples from small and medium-sized plate in the listed companies through questionnaires and open data query,of which 20 samples as the training samples to construct the BP neural network,the other 10 as the validation samples to measure the effectiveness.The fifth part are the conclusions and prospects.Drawing a conclusion based on the theoretical and empirical analysis:Based on the advantages of BP neural network in the process of supply chain financing credit risk with self-study habits, strong fault tolerance and dealing with nonlinear problem,through the training and validation of the model shows that the sample of the supply chain financing credit risk evaluation model based on BP neural network has high accuracy.The simulation results and expert evaluation value is consistent.I believes that the model will provide a good reference to the commercial banks and other financial institutions to expand the supply chain finance business and enterprise credit risk evaluation.