Research On Risk Management Of China Everbright Bank’s Automotive Supply Chain Financing Businesses

China has become the largest automobile production and consumption market in the world.However,in the automotive industry chain financing businesses,small and medium-sized automobile dealers,as an important circulation link,often face issues such as small enterprise scale,ordinary qualifications,financial insufficiency,private owners,and lack of mortgageable assets,making it difficult to obtain bank financing during traditional bank credit approvals.Supply chain financing is based on the logistics,information flow,and capital flow of upstream and downstream enterprises in the supply chain,which is led by financial institutions represented by commercial banks to provide financing for enterprises in the supply chain.In the practice of supply chain financing,China Everbright Bank’s automotive supply chain financing business has been under operation in the market for 18 years.Based on the “self-liquidating nature of trade” and relying on the supervision of automobile certifications,it has become the banks’ promotional product for the expansion of credit customers in the automotive industry.Although China Everbright Bank’s automotive supply chain financing business has formed a full-process risk management model of pre-loan investigation,loan review and approval,loan lending and operation,and post-loan management,it is based on the mutual verification of information flow,logistics,and capital flow.The key point of risk control is the supervision of automobile certificate as a means,and the release of credit line after the return of sales funds.However,seemingly perfect risk control design,in recent years,cases of risk exposure have emerged endlessly,which is mainly due to the failure of risk monitoring methods to identify other operations other than the borrower’s main business in a timely manner,without regulations to avoid third-party supervision of fraud by companies,single approval for single business,single household management and control,high cost,high time consuming,difficult to achieve control and other issues.The reason behind this is mainly because the existing risk control methods do not well avoid the issue of information unsymmetrized,adverse selection and moral hazard,and can’t avoid the defects of the principal and agent mechanism inside and outside commercial banks.With the transformation of financial technology and the development of Internet technology and the practical application of big data in various industries,it has become possible to provide financing services relying on Internet technologies and tools.Banks can use the massive amount of user data and data resources that they can master to build a loan service scenario,and they can also use the information flow,capital flow,and logistics data collected by core enterprises to use credit as basic and value-added service contents through data models.The author proposed to introduce real-time monitoring of the risk early-warning management system at each stage of risk management in a timely manner,and to use big data to collect and analyze transaction data of each risk control link,then compare it with the mean in real time,and identify customers in time through the data models to identify degree of deviation between the existing trading behavior and the mean.The degree of deviation is considered normal within our tolerance range.Once the degree of deviation exceeds our tolerance range,the system automatically prompts an exception.In this paper,through in-depth research on the risk management methods of the automotive supply chain financing businesses,the key points of the original business’ s risk control were extracted.Through case analysis,the issues in the original risk management model were discovered,and the reasons behind the issues were found.Analysis of the two games between dealers and OEMs,dealers and third-party regulatory companies,and the shortcomings of the original risk management model were found.The original risk management process was carried out by introducing a big data separate control model and a risk early warning system.The improvement can not only improve the accuracy and timeliness of the information obtained,but also reduce the management cost of the account manager’s pre-loan,loan operation,and post-loan links,improve management efficiency,increase income levels,and help the rapid promotion of the automotive supply chain financing business.In the context of economic transformation,interest rate liberalization,financial disintermediation,and fintech transformation,the issues in the risk control of China Everbright Bank’s automotive supply chain financing business were studied.The most important point is to study the risk control mode and risk control behind its business operations,which can provide the direction and model on how to improve the original business to better adapt to the current economic and financial environment,how to promote it to other supply chain financing businesses,expand the scale of bank credit business,and better serve SMEs.