Research Of Peasant Household Credit Scoring System For Gaoling Branch Of Rural Credit Cooperatives

Information asymmetry between financial institutions and farmers is an importantreason which restricts farmers to get the loan and even the economic and financedevelopment in rural area. As one of the most important agricultural financialinstitutions, rural credit cooperatives need to solve the information asymmetry and tobuild a system for controlling of credit risks. To establish a scientific system for peasanthousehold credit scoring is an important part for the lending of agricultural financialinstitutions and the controlling of credit risks. It could also solve the informationasymmetry and adverse selection problem. So it is the objective requirement to speed upthe pace of the rural credit system construction and to improve the rural creditenvironment. Therefore, building a scientific and rational peasant household creditscoring system has become the current urgent need to solve the financing problem ofChinese farmers and to promote rural economic and financial development.This paper does the research basing on practice, which first analyses theimportance of establishing peasant household credit scoring system and elaborating thebackground of this paper. The author as the main members of the working grouptogether with other colleagues use the method of expert risk models to build the creditrating index system and the information management system for the Gaoling branch ofrural credit cooperatives. Because expert risk models have same insufficient, such as thehigh of artificial factors and the lack of objectivity, the author builds the Logisticregression model basing on of the above system data, which using principal componentanalysis (PCA) to determine the initial modeling variables, builds the Logistic regression model, uses test samples to test the effectiveness of the model and finallyeffects very well. Then compared the expert risk model and the customization modelwith random samples, consistent rate is high. The author suggests combining the twomodels together, and adding the Logistic regression model results to the peasanthousehold credit scoring system of the Gaoling branch of rural credit cooperatives tosolute the problem of how to effectively predict in the case of lacking information.Finally, combined with related conclusions, the paper puts forward the relevantmeasures to strengthen the peasant household credit scoring system of the Gaolingbranch of rural credit cooperatives.