A Study on the Process Optimizing of Banks Lending Service

摘要：

The commercial banks can be seen as an enterprise which manufacture loan for firms and individuals. In the process of lending, credit-scoring model has play an important role in evaluating the probability of default of the ban application. In general, credit-scoring models suffer from a sample-selection bias. This paper uses the bivariate probit approach to estimate an unbiased models scoring model The data set with large commercial loans data provided by a commercial bank of China to estimate the model contains some financial and firm information on both rejected and approved applicants.In the bivariate probit model, we find the bivariate selection model provides more efficient estimates than does a single equation mode. The results show that the bivariate probit model can help the loan committee of the commercial to optimize the process of lending service.

关键词： Lending process Credit scoring Sample Selection Bias Bivariate Probit Selection Model

作者: HUANG Xiaokun

作者单位: Schoole of Business Administration,South China University of Technology,Guangzhou,P.R.China,510640

会议类型: 国际会议

会议名称: The 5th International Annual Conference on WTO and Financial Engineering(第五届WTO与金融工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 45-50

在线出版日期: 2008-05-18（万方平台首次上网日期，不代表论文的发表时间）