Research On Personal Credit Risk Measurement Based On Actuarial Method

For a long time,the measurement of personal credit risk has been an important research direction in the financial market.As to how to accurately and objectively measure the probability of credit default,scholars are constantly exploring.This paper reviews and combs the related research at home and abroad,and discusses the mechanism and influencing factors of credit risk.Combined with the method of survival analysis in life insurance actuarial,the size of credit risk factors,the credit default rate of the loan customers and the size of the default loss of the loan portfolio are measured.We first use the Cox risk ratio model in survival analysis to analyze the factors that affect credit risk.The empirical results show that gender,education,loan term,loan amount and other factors will affect the default rate of credit loan.The default rate is positively correlated with the duration and total amount of loans,and negatively related to personal income and academic qualifications.Then we build the CLL model to measure the credit default rate of loan customers.The advantage of this model is to introduce the credit default rate to the time variable,which can well fit the size of the default rate for each customer at different times,and can also measure when the transaction customer will default and then estimate the size of the default loss.We introduce a multi term Vasicek model,which is based on the customer's model.Macroeconomic factors measure the size of default losses at each moment.In the empirical analysis,using the regression results of the Cox risk proportion model,the factors that significantly affect the personal credit risk are introduced into the CLL model,and the measurement and analysis of personal credit risk are realized.In the empirical analysis,the Cox risk ratio model and the CLL model are used to simulate the real data of the transaction customers in the transaction process,and the two model has a good application value for the credit risk measurement.