Behavioral credit scoring model for technology-based firms that considers uncertain financial ratios obtained from relationship banking

Abstract

The Korea government offers technology credit guarantee service to many technology-based small and medium enterprises (SMEs) suffering from funding problems. Many advanced application credit scoring models have been developed based on technology to reduce the high default rates of this service. However, a credit scoring model which can reflect changes in firms after a loan has been granted has not yet been developed. In the study reported here, we propose a behavioral credit scoring model that reflects the debt-paying ability of recipient firms, which is observed as a time series of financial ratios of firms via the relationship banking activities. We utilize this time series, as well as missing patterns of financial information, as additional predictors of loan defaults. We compare our proposed behavioral credit scoring models, fitted at different points of elapsed time, to the application credit scoring model. Finally, we suggest the best behavioral credit scoring model for technology-based SMEs. Our study can contribute to the reduction of the risk involved in credit funding for technology-based SMEs.