Research On Risk Prevention And Control Of Supply Chain Finance Business

In recent years,China's loan policy has continued to tighten,and SME loan financing has been more difficult.In this context,supply chain finance is rapidly emerging with a new credit method.It appears to help SME to solve the problem of financing difficulties to a certain extent,and has become a new growth point of business for commercial banks.The biggest difference between the past and the credit business is that supply chain finance starts from the perspective of the entire supply chain.The financial status of its financing companies will no longer be the single standard for credit evaluation of commercial banks,but will be based on the financing companies in the supply chain and core The stable and good trade relations of the company and the continuous development of the two parties enabled the company to obtain trade financing in banks and other financial institutions.The bank has thus broadened its existing customer base,further developed its credit business and enhanced its profitability.At present,the innovative development of supply chain financial services helps SMEs ease the financing difficulties,broaden financing channels,and increase overall competitiveness.Commercial banks have developed a supplychain finance business and have achieved good economic returns.At the same time,however,we must take note of the risks in the supply chain finance business.As there are more participants in the process of supply chain financial services,the uncertainties faced by them are more.This risk has greater complexity and concealment,and the relevance and the vulnerability of both,the loss of control occurs,it will bring huge losses,which will cause large deviations in the actual income and expected returns of financial institutions such as banks in the supply chain.This is a relatively new area of research.How to accurately identify and correctly manage and control the financial risk of supply chain crucial to the development of the entire industry chain.According to the current development of supply chain finance,this paper studies how to carry out supply chain financial risk management.according to the inherent requirements and logic of the bank's risk management,and compares and summarizes the traditional loan business.It attempts to construct a theoretical model that can provide guidance,finds risk warning and monitoring model suitable for the characteristics of the supply chain financial risk system,and introduces a new idea and method for the modern supply chain financial risk management that is in line with the actual situation.It is worthwhile to pay attention to this article through the actual case of A-bank supply chain finance business,analyze the actual data of the business in recent years,and verify the quantitative early warning monitoring model.The paper is divided into six parts.The first part mainly describes the research background and significance of the article,as well as the related research contents and methods.The second part mainly talks about the research summary of the prevention and control of supply chain financial risk at home and abroad.The third part mainly describes the status quo and problem analysis of China's commercial bank supply chain financial risk.The fourth part designs a comprehensive risk prevention and control index system based on the mechanism of the supply chain financial risk analyzed in the previous section.The fifth part mainly constructs an early warning model of supply chain financial risk,and empirically analyzes the model based on relevant data of relevant sales companies in Bank A,which verifies the validity of the model and provides quantitative monitoring and prevention of supply chain financial risks model.The sixth part is a summary of the study of this article and further prospects.This article,combined with related cases,hopes to provide some reference and reference for China's commercial bank supply chain financial business risk management prevention and control theory core system and the corresponding quantitative model.