Credit scoring model using MARS method to comply with FSA regulation

Abstract

Financial Service Authority (FSA) introduced a new policy on Sustainable Finance to financial institutions such as Banks. It is currently a hot issue that needs to be implemented in the selection process of potential debtors. Consequently, the credit rating system needs to be renewed. Statistical methods can help to include permits and environmental impact in the selection process. Thus, this study intends to formulate a credit rating model for productive debtors. This study used a quantitative method using Multivariate Adaptive Regression Splines (MARS). Our study’s significant finding is that the credit rating model for productive debtors that have been formulated has type I error of 0.00% and type II error of 0.54%. Furthermore, the authors believe that this model can be used to asses potential debtors’ credit rating while adhering to the policy of Sustainable Finance.