Identifying and measuring credit risk of small and medium-sized enterprises should be different from that of large firms, for SMEs appear to be influenced by their owners more directly and significantly. This paper attempts to testify the relationship between default behaviors of SMEs and the credit features of their owners, so that a more appropriate and effective way of credit management of SMEs could be applied in practice. After segregating the owners' characteristics data into variables of basic features, credit capacity features and credit will features, this paper implement an empirical study of logistic regression analysis with repeat sampling data. The result demonstrates that, compare with the owners' credit will variables, variables reflected credit capacity features share more significant relationship with the SMEs' credit default behavior. Specifically, the age of owner, the inquiry frequency of owners' credit information for post-loan risk management and pro-loan approval purpose, and the proportion of overdue loans are the extreme significant variables which are valuable indicators in default risk estimate model.
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