The Empirical Analysis Of Credit Risk Models Of SMEs In China

Bank is one of the channels of direct financing for SMEs. Due to the small amount of each single loan and the high risk, SMEs are restricted to loan from the banks, which affect the expansion of SME and directly hinder the healthy development of small and medium private enterprises. At the same time, banks lack of SME methodologies and proprietary research model of credit risk measurement. This study will start from the difficulties of getting loans from banks. Following will be a systematic introduction of the development of credit risk evaluation methods as well as foreign credit risk measurement models for SMEs. By comparing the sophisticated credit risk models, this paper will choose the suited models for SMEs in China.In the empirical measurement section, this paper will divide the SMEs into listed and unlisted emterprises and do research separately. A true evaluation is the base for a fair loan. thereby the posibility and efficiency of loans to SMEs could be enhanced. For those listed SMEs in this paper, KMV model is introduced to measure their credit risk. For unlisted SMEs in this paper RiskCalc model is introduced by explaining the principle and calculation method to analyze the applicability of the model. Through empirical analysis, this paper obtain the conclusion that the default risk of SMEs has a negative correlation with its asset size, net assets per share and rates of net assets return, in which assets and net assets yield rate have a larger impact on the credit risk of SMEs.In order to provide financial support and offer better service to the SMEs by the financial institutions, it is particularly necessary for the government to adopt policies to encourage commercial banks loaning to small business. In addition, the supervision of commercial bank to small enterprises should be differentiated. In the future, the credit risk models will be widely used by commercial banks when assessing the credit risk of small business. An accurate and robust database need to be set up as the basis for the use of credit risk models, which is also the basis for risk management system.