基于Logistic模型的住房抵押贷款违约风险实证研究

An Empirical Study on Default Risk of Housing Mortgage Loans Based on Logistic Model

住房抵押贷款已成为我国商业银行拓展信贷营销业务、优化信贷资产结构的主要手段。但是随着中国住房抵押贷款的发展,风险也日益突出。在实地调研的基础上,利用Logistic回归模型对影响我国住房抵押贷款违约风险的因素进行了实证分析,研究发现,借款人每月偿还贷款金额与家庭收入之比越高,违约率就越高;借款人年龄越大,违约率就越高;借款人受教育程度越高,违约率就越低;借款人工作稳定性越高,违约率就越低。这为商业银行在住房抵押贷款发放时管理违约风险提供了有益的帮助。

Housing mortgage loan has become a major means for Chinese commercial banks to expand credit marketing business and optimize credit assets structure. However, with the development of Chinese housing mortgage loan, its risks have become more severe increasingly. This paper conducts an empirical analysis on factors influencing the default risk of Chinese housing mortgage loan using Logistic regression model based on field research. The research finds that, the higher the ratio of monthly credit repayment amount to household income of borrower, the higher the default rate; the elder the borrower, the higher the default rate; the higher the education level of the borrower, the lower the default rate; the higher the work stability of the borrower, the lower the default rate. This provides favorable help for commercial banks to manage default risk while issuing housing mortgage loans.