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本文以某商业银行化工行业2006年小微企业信贷数据为基础,综合运用因子分析和Logistic回归分析,对小微企业进行客户违约风险预警,并运用2007年的实际违约客户数据对模型风险预警能力进行验证,结果显示模型预警效果较好,这对加强银行的信贷风险管理具有参考意义。
Based on the credit data of small and micro enterprises in chemical industry of a commercial bank in 2006, this paper comprehensively uses factor analysis and Logistic regression analysis to predict the default risk of small and micro enterprises, and uses the real default customer data of 2007 to predict risk of model risk The results show that the model has a good early warning effect, which has reference significance for strengthening the bank’s credit risk management.