Overdue Risk Identification And Control Strategies Of Peasant Household Micro-credit In Gansu Rural Credit Union

With the change of rural industrial structure,more and more farmers begin to apply to financial institutions for loans to develop scale operation in order to achieve income growth.As the main force serving agriculture,rural areas and farmers,Gansu Rural Credit Union timely launched peasant household micro-credit.However,due to the imperfection of the rural financial system and the particularity of farmers’ credit risk,the overdue rate of credit business remains high,resulting in a serious shrinkage of credit assets in some outlets,which affects the normal issuance of micro-credit loans to farmers by financial institutions.Gansu Rural Credit Union Peasant household micro-credit includes three stages: credit rating,loan issuance and post-loan management.Based on the results of credit rating,farmers’ willingness to repay and repayment ability are evaluated.Whether peasant household micro-credit rating is accurate or not has a great impact on the effect of business risk management.According to the research framework of risk management,this paper uses data mining tools to identify the key risk points in the micro-credit business of rural credit farmers in Gansu Province,quantitatively evaluate them,and formulate corresponding risk management strategies to promote the sustainable and healthy development of business.Firstly,the paper selected 272,132 sample data of peasant household micro-credit from August 2016 to August 2017 of Gansu Rural Credit Union(including 151,419 sample data of planting credit and 120,713 sample data of farming credit).The target variable was whether the credit loan was overdue or not.The 18 indicators in the current credit rating system were taken as risk characteristic variables,and the SPSS19.0 statistical analysis software was used to select the data.Logistic regression analysis was used to identify the risk points of the two credit sub-businesses used in farming and aquaculture.Secondly,combined with the actual data,the identified risk points are quantitatively evaluated from the two dimensions of overdue probability and loss scale,and then risk classification is carried out.Finally,according to the quantitative results,we put forward targeted risk management strategies.The results of data mining show that there are 17 key overdue risk points in the farming credit business and 12 key overdue risk points in the farming credit business.The risk types,risk performance and risk structure of the two sub-types of credit business are quite different,and the difference is very significant.This means that there are obvious drawbacks in the current management model of "package" of micro-credit for farmers.Regardless of credit rating or post-loan supervision,risk classification management is more reasonable.Classification management helps to improve the accuracy and effectiveness of risk identification.On this basis,the design of corresponding risk management strategies will have better pertinence and effectiveness.