The Commercial Bank Credit Default Risk Comparative Research Based On The KMV Model

International credit crisis is often triggered by a handful of banks in credit risk, such as,the Wall Street crisis in the early20th century was caused by the long-term Capital Management in United States, and the Lehman Brothers triggered a global financial crisis, which are all due to the small number of financial institutions with credit risk. Credit default risk have a tremendous impact on the entire financial system, even led to financial crises. Therefore, estimating the default risk level to guard against credit risk is critical to the stability of the financial system.Credit default risk calculation method has matured in foreign banks and have established a huge and detailed database of information, which provides a basis for credit risk evaluation from all aspects. While in China’s banking samples’analysis, different scholars have used different methods to estimates bank default risk. Their research focuses on the effectiveness comparation of several model or adaptive native correction. The evaluation mainly uses non-performing assets ratio and capital adequacy ratio, the banking credit risk evaluation uses the five classification. Compared to the new Basel’s requirements, there is still a certain distance to the global banking credit rating system, like the KMV ratings used by most developed countries.In view of the important role of the credit default risk estimation of the financial system, We used the latest econometric models--KMV model to estimate the default risk of the banks in China, and choose the credit default distance, asset volatility and equity volatility as evaluation indexes of credit risk, then analyzed the factors that affects. Firstly we select the four-years data of16the bank already on the market as a research object, and divided them into the traditional state-owned commercial banks, joint-stock commercial banks and city commercial banks in accordance with the factor classification, and make a contrast within the group based on scoring results. Secondly, we make a few adaptive correction to the KMV model, and calculated their credit default distance using the sample equity and asset data Finally, we analyzed calculated credit default distance of the three banks groups, the overall trend of the banks samples within the group, binding factor grouping results, and made predictions.Our research showed that16listed banks’credit risk control is in good condition. Joint-stock commercial banks have a minimum and more stable credit risk, which shows their credit risk mechanism has matured and been improved. The traditional state-owned banks followed, but the changes of credit risk with a characteristics of pro-cyclical fluctuations. Meanwhile, the local commercial banks’credit risk exposed and with a overall large number, indicating that their credit risk control is far from perfect, it also sounded the alarm to the quickly and largely establishment of local financial institutions.