Credit Risk^(+) 모형을 이용한 가계신용대출의 신용위험에 대한 연구 : 대전지역 거주자를 중심으로
(A) Study on the Credit Risk of Individual Credit Loan by Credit Risk^(+) Model
Credit Risk^(+) 가계신용대출 신용위험;
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Recently, financial institutions have made drastic shift from enterprise-loan to individual-loan. However, along with a great number of credit defaulters, delinquency caused by recent economic stagnation has a bad influence on the sound management of financial institutions. Most financial institutions deal with much real estate loan. We may face the second financial crisis when the real estate market situation is confirmed as a bubble. Until now financial institutions have not assessed the loaner's willingness and ability to pay as well as credit status. And they have just concentrated on expanding real estate loan. As a whole, it is time to introduce Credit Scoring System as means of making objective decision. In this study, I survey and analyze the credit risk of individual credit loan categorized by certain standards to manage the insolvent individual credit loan; customer class, ages, income status, housing type, application score and behavior score. Credit Risk^(+) model introduced in CSFB(Credit Suisse First Boston)is applied in this study. Assessed credit loss is named Credit at Risk(CaR). Collected 421 individual loan cases were used for data from Korean K-bank, which amounted to 4,112 million won. I estimated CaR of individual credit loan using Credit Risk^(+) model for this study. It shows that 95% CaR is 15.74% of the total individual loan and 99% CaR is 20.17% of the total individual loan. Analyzing the credit risk depending on ranks of customers, I get the expected value that risk contribution rate to the total loan of the upper customers is 8.6% and risk contribution rate to the total loan of the lower customers loan is 15.72%. The category divided by ages shows that the 30s' risk contribution rate to their total loan is 20.61%i. It is lowest ratio among the groups. The 20s' keeps higher risk contribution rate than others. It is 46.21%. There is also a difference between groups in the category by income status. Generally the customers whose incomes are under 20million won a year have 23.68% risk contribution rate to their total loan which is much higher than others. As for the housing type, there was no notable difference. When it comes to behavior score and application score, the higher score loaners have, the lower risk contribution they keep, and the lower score they have, the higher risk contribution they keep. I excluded the top 10% high risk group and retested CaR. As a result, 95% CaR shows only 46.86% to the total loan(95% CaR). 99% CaR indicates 42.96%. If we exclude top 10% high risk group, there is a great decrease in CaR. This is going to be very useful in the management of credit risk.