Financial Leasing Company’s Customer Credit Risk Identification And Management

Since the obvious conflict between great development of Chinese leasing industry and lagging-behind risk control method, this Essay set up credit default stimulation model according to 40 default lessees and 40 no credit-default lessees as stimulation samples from the authors ‘company and build up six factors as stimulation variant. In this essay, we use binary Logistic regression model to make the empirical analysis, moreover, we find out that credit default is significantly influenced by Log(Asset), accounts receivable turnover ratio, short loan revenue ratio. Therefore, we can find out more effective risk control during our private-owned enterprise as a lessee in Chinese leasing industry.Moreover, in this essay, the author analyze the effectiveness of current leasing risk control method,risk-return premium system and warning mechanism of asset management.Also, the author make relevant management suggestion according to the study.This essay also argues that quantitative index selection and weighting index in the existing leasing risk control methods should prefer to use the relevant results of empirical analysis concluded in this essay. Furthermore, it also suggests the discrete and continuous risk premium delivery mechanism of price; simultaneously, based on different Z values corresponding to different risk-preference, this essay define safety-factor to apply for asset management warning mechanism.