Research On Default Probability Model Of Consumer Loan: Based On The Data From Commercial Banks In China

In the accelerated development of globalization and liberalization in financial market,the risk of finance has appeared to be highly inter-related,frequently occurred and caused heavily losses.A series of events such as bank crisis in Latin America,the Asian financial crisis,the subprime mortgage crisis in the US reflected fragility of finance market,and it also arose the further thinking of the commercial banks' credit risk management in banking section and academic world.Basel capital accord,which is enacted by Basel Committee on Banking Supervision(as the formal institution for international settlement) is the standards of regulation of commercial banks accepted globally.The Committee issued the new Basel accord in 2006.It included the credit risk,market risk,liquidity risk and operational risk into the research field of the measuring risk;hence he argued the three pillars of capital regulation,namely capital adequacy ratio,supervision and inspection,market discipline.The new accord has set up more tightened requirements in the credit risk management of commercial bank.The new approach ranked the measurement and evaluation of the default probability as the core of Internal Rating Based(IRB) approach;it proposed that IRB should be adopted in practice of risk weight as well as the counting and drawing of capital at risk.Meanwhile,theoretical circles have done a lot of works on the research of Probability of Default Model.It mainly focused on the option of influence on the key factor of default rate and established Probability of Default Model to historical data as driven,on the basis of mathematical models and statistical methods based on classification algorithm.China's modern commercial banking system had just been established,the limited level of their risk management,as well as the inadequate accumulation of historical data,all of those were not possible to meet all forms of commercial banks loans accurate security measurement.However,as the China's commercial banks deepening degree of internationalization,based on the new Basel Accord,the China Banking Regulatory Commission required the major commercial banks to enhance their level of consumer credit risk management,and focused on studying the loan default probability,at the same time of enhancing building default loss rate history databases.Based on the systematic reviews of relevant literature on researching consumer credit loan default probability measurement,this paper constructed SenV-RBF-SA and time-varying covariates quantitative model to measure consumer credit loan default risk,and established the commercial bank Overall consumer credit risk measurement model using Copula method,and using actual commercial bank consumer credit loan data to research.The main work and the results of this paper are as follows:First of all,considering the SenV-RBF neural network had no requirements for data distribution,and the characterization in dealing with non-linear problems,as well as the semi-parametric Cox proportional hazard model can dynamically predict default probability,this paper constructed SenV-RBF-SA dynamic models of default probability to measure borrower's default probability in a future point.At the same time,the empirical research on actual data of commercial banks consumer credit, found that this hybrid model had a certain degree of competitive in the identification accuracy and robustness compared with traditional model.Secondly,taking into account the systemic risks impact on borrowers,caused by GDP,interest rates,CPI,the Shanghai Composite Index and Etc.macroeconomic fluctuations.Base on the above hybrid model,this paper used the time-varying Cox proportional hazard model to build a class of consumer credit default probability measure model,and objectively measure the impact of the macro-economic factors on the borrowers' average default level.The model overcomed the limitations of traditional model which took the Logistic regression model for representative,which only considered individual non-systemic risk when measured consumer credit default probability.Finally,through empirical analysis,the time-varying model had higher accuracy and robustness compared with the traditional default probability model,this is a development study of the third chapter. Finally,this chapter mainly investigated the dependent relationship of prepayment and real default,and constructed a model which can measure the whole default risk between prepayment and real default based on the Copula method.We gained survival time maginal distribution of the two groups of credit products through non-parameter kernel density estimation method.Then optimal Copula would be chosen by QQ diagram and Kolmogorov-Smirnov test on every dependent structure of generated Copula.And then a new PD model of dependent risk was established based on measurement ideas of Copula and default marginal distribution.At last gave the kendallτbased on Copula dependent default measure,and conducted empirical research.