Research On Financial Credit Risk Evaluation Of Internet Supply Chain

The traditional financial industry is developing towards a new form under the Internet model,which has spawned a number of new Internet financial companies and brought new Internet financial products.Internet-based supply chain financial products are still in a rapid development stage in China,and Internet financial companies have launched their own supply chain financial products.The measurement and prevention of financial supply chain financial product risks also need to keep pace with the times,and the traditional supply chain financial risk assessment methods need to be changed according to the characteristics of new products.This article mainly studies the credit risk assessment of the Internet supply chain.It establishes a credit risk assessment index system including the credit status of financing companies,the credit status of core companies,the status of supply chain relationships,and the status of the Internet platform.Logistic regression,BP neural networks,and machine learning Method to establish a credit risk assessment model.Based on the data and materials of JD Finance and the automotive industry case,a credit risk evaluation index system for Internet supply chain finance that cannot be achieved by traditional supply chain financial credit risk evaluation is established.The empirical part of this article compares the newly established Internet-based supply chain financial credit risk evaluation index system with the traditional supply chain financial credit risk evaluation index system by empirical testing,and uses the analysis obtained by the Logistic model,BP model,and SVM model.As a result,it can be seen through the MATLAB program that the combination of the credit risk evaluation index system based on Internet supply chain finance and the SVM model has the best analysis effect.In the comparison of the two index systems,the overall classification accuracy of the Internet-based supply chain financial credit risk evaluation index system is 95.33%,which is a certain advantage over the traditional supply chain financial credit risk evaluation index system of 88%.In the comparison of the three models,the overall classification accuracy of the Logistic model is 82.50%,and the overall classification accuracy of the BP model is 82.33%.It can be seen that the classification effect of the Logistic model and the BP model is not as good as the overall classification of the sample of the SVM model.The rate is 95.33%.In addition,in terms of the first type of error rate that is more important in credit risk evaluation,the SVM-based Internet supply chain financial credit risk evaluation model is not only lower than the traditional model based on SVM,but also lower than the Internet supply based on BP neural network.Chain Finance Credit Risk Evaluation Model.Therefore,it can be explained that the SVM-based Internet supply chain financial credit risk evaluation model is more effective and superior,and can better and more accurately evaluate credit risk in the supply chain.