A Study on the Process Optimizing of Bank's 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.