Research on Credit Risk Evaluation Method for Auto Parts Suppliers

Against the backdrop of the rapid development of the new energy vehicle industry, auto parts suppliers are facing financial turnover pressure. Considering the long supply chain and close cooperation between enterprises in automotive industry, through the evaluation of the industrial and commercial information, finance and supply chain relationships data of 484 listed auto parts companies, a set of credit evaluation indicators for automotive parts suppliers is constructed in this research. Logistic regression model is applied for risk prediction, aiming to improve the accuracy of credit evaluation, optimize automobile supply chain financial services, and promote capital flows to the enterprises in need efficiently.