Abstract
Probability of default (PD) of a small company is estimated by the credit scoring model which mainly includes financial indices. Default is affected by not only a specific factor but also common factors. It is desirable to include the macroeconomic factors as explanatory variables in order to improve the accuracy of the estimated PDs. However, we have a serious problem that there are not enough time series data of default to determine the macroeconomic indices by the regression model. Recently, we begin to recognize a strong need to model the credit scoring with macroeconomic variables because the actual default rates (DRs) are higher than the estimated PDs by the serious downturn in economy from about 2007. In this paper, we determine the macroeconomic indices by using about 540,000 of loan data in Micro Business and Individual Unit of Japan Finance Corporation, and compensating for the lack of the time series data of macroeconomic factors. As a result of the analysis, we find that the previous default rate in a month is significant. We improve the accuracy of the estimated PDs by using the modified credit scoring model with the previous default rate in a month. The difference between the estimated PDs and the actual DRs can be reduced at a maximum of 0.72%.
