小额贷款公司中小企业信用贷款风险实证研究—基于Logistic和Probit模型
An Empirical Credit Risk Study of SEMs in Small Loan Companies—Based on Logistic Model and Probit Model
DOI: 10.12677/SA.2014.34022, PDF, HTML, 下载: 3,568  浏览: 10,891  国家自然科学基金支持
作者: 张佳敏, 周建军:云南大学,数学与统计学院统计系,昆明
关键词: 小额贷款公司中小企业信用风险Logistic模型Probit模型Small Loan Companies SMEs Credit Risk Logistic Model Probit Model
摘要: 本文以小额贷款公司主要的客户群体中小企业作为研究对象,立足于公司日常的信用贷款业务,基于Logistic与Probit模型进行风险评估实证分析。在小额贷款行业专家的帮助下,采取头脑风暴法获得建立模型所需的八项指标。这八项指标作为模型的自变量,从内容上可分为两部分,一部分描述借款人个人情况,另一部分衡量企业经营状况。在昆明高新科创小额贷款公司数据支持下获得模型结果。在面对具体的贷款业务时,可以通过相应模型计算客户信用风险得分,最终做出是否予以贷款的决策。经检验,研究成果可行、有效。
Abstract: SMEs (small and medium-sized enterprises) as small loan companies’ main customer groups are objects of study in this paper. Based on the companies’ day-to-day credit loan business, Logistic model and Probit model are applied to this empirical analysis of credit risk assessment. Adopt brainstorming to get eight required indicators with the help of experts on microcredit industry. These eight indicators as independent variables in the model can be divided into two parts ac-cording to content. One part is used to describe borrower’s personal circumstances and another part is used to measure companies’ business conditions. Data from Kunming KC small loan company are fitted with these two models. In the face of a specific loan, calculate the corresponding credit risk score and then make the decision. Upon examination, results of this study are feasible and effective.
文章引用:张佳敏, 周建军. 小额贷款公司中小企业信用贷款风险实证研究—基于Logistic和Probit模型[J]. 统计学与应用, 2014, 3(4): 159-166. http://dx.doi.org/10.12677/SA.2014.34022