Research On Optimization Of Retail Credit Risk Management Of Auto Finance Company A

Since 2018,the growth rate of the automotive market has slowed down,while the competition in the field of auto finance continues to intensify.At present,the number of licensed auto finance companies in our country has reached 25.Different from the bank-based auto finance business,although auto finance companies cannot compare with them in terms of scale,auto finance companies have unique advantages in terms of providing professional services.Nevertheless,due to the incomplete coverage of domestic credit system construction and the lack of auto finance professionals,auto finance companies still have many problems in risk management.Among them,credit risk is the most prominent.The paper takes Auto Finance Company A as an example to study the problems that arise in the process of credit risk management,then raises optimization plans for the above problems and evaluate the corresponding results.The paper first introduced the current status of Auto Finance Company A's credit risk management,then,pointed out the problems exist in the credit risk management process.In the pre-loan management stage,there exists problems such as decline in credit asset quality,increase in fraud risk and lack of efficiency in credit reviewing process.In the loan management stage,there exists problem such as high lack of credit files.In the postloan management stage,there exists problem such as low collection efficiency.The paper then uses a variety of research methods such as data-driven and questionnaire surveys to explore the causes of the above problems.In the pre-loan management stage,the problems were caused by the lack of scientific and effective credit risk measurement methods,the lack of effective fraud risk detection methods and the low degree of automation of approval.In the loan management stage,the problems were caused by the irregular dealer management.In the post-loan management stage,the problems were caused by the lack of a collection management system and the inflexible collection strategy.The paper subsequently raised optimization solutions for the above problems.In the pre-loan management stage,the solutions include building of credit score card,anti-fraud system and optimization on decision engine.In the loan management stage,the solution includes stablishing of dealer management system.In the post-loan management stage,the solutions include strengthening outsourced collection and establishing of dynamic collection strategy.At the same time,in order to make sure the optimization solutions implement smoothly,the paper proposes safeguard measures such as construction of risk culture,strengthen personnel training mechanisms,establishing of scientific assessment system and improving of information technology infrastructure.Finally,in the conclusion part,the paper sorts out the optimization results as conclusion and providing useful experiences for the industry.