农村信用社信贷违约识别模型及其应用

发布时间：2019-07-06 21:11

【摘要】：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.
[Abstract]:It is of great significance to construct the credit risk model of rural credit cooperatives to perfect the rural financial risk management system and improve the management of rural credit cooperatives. Based on the willingness to repay and the ability to repay, this paper systematically analyzes the main factors that affect the default rate of the loan debtors of rural credit cooperatives. On this basis, the prediction model of the default rate of the debtors of agricultural credit cooperatives is established by using logistic method, and the distinguishing ability and recognition ability of the model are verified and evaluated by Gini coefficients. The empirical results show that the debtor age, the region where the loan amount accounts for the household income, the close relationship between the loan amount and the credit union credit and the status of the account are significant, and the default rate prediction model has a good ability to identify the default in both the sample and the sample, which can provide a powerful reference for the debtor credit evaluation, loan issuance and risk management before the agricultural credit cooperatives lend.
【作者单位】：北京工商大学经济学院;中国科学院数学与系统科学研究院;中央财经大学管理科学与工程学院;
【基金】：北京工商大学青年基金(QNJJ20123-11) 教育部人文社会科学研究青年基金(11YJC790015) 首都流通业研究基地资助(JD-Y-2014-12) 国家自然科学青年基金(71203247)
【分类号】：F832.35;F224;F832.4

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