农村信用社信贷违约识别模型及其应用

构建农村信用社信用风险模型对完善农村金融风险管理体系、提高农村信用社经营管理意义重大.基于还款意愿和还款能力两方面,系统分析了影响农信社贷款债务人违约率的主要因素,在此基础上应用logistic方法建立农信社债务人违约率预测模型,并通过Gini系数对模型区分能力和识别能力进行验证评估.实证结果表明,模型中债务人年龄、所在地区、贷款额所占家庭收入比例、与信用社信贷关系密切程度以及户口状况等因素都表现显著;违约率预测模型在样本内和样本外均有较好的违约识别能力,从而可为农信社放贷前的债务人信用评估、贷款发放和风险管理提供有力参考.

Recognition Model of Credit Default in Rural Credit Cooperatives and Application

Constructing a risk assessment model for rural credit cooperative is critical for perfecting rural finance risk management mechanism and improving the ability of risk controlling.This paper analyzes the key factors affecting probability of default systematically based on the debtor's will and capability of paying back.On top of that,we build logistic model to predict probability of default,and verify the model's ability for default distinguishing and recognition.The result shows that probability of default is related to debtor age,district,the proportion between loaning amount and household income,relationship between debtor and creditor and registration properties(temporary residents or permanent residents) and the model has better performance on default identification in sample and out of sample.Therefore,this model provides foundation for credit assessment before lending,risk management for rural credit cooperative.