An automated credit intelligence learning system

Abstract

To accelerate the financial service, microfinance need a tool and technology to provide an automated dynamic credit decision which provides an accountable and efficient system. Taking case on loan disbursement in the micro-business sector, this study presents a vary comprehensive innovation, namely Credit Intelligence Learning System (ACILES) which consist of dynamic credit scoring (CS) and optimal dynamic credit pricing: derived from tenor, rate, installment, and plafond (TRIP). While credit pricing is obtained by the profit based pricing and simulation process, the credit scoring is developed by modeling not only the borrowers data profile but also psychometric analysis of both borrower and surveyor’s perception via Item Response model which combined with Multivariate Adaptive Regression Splines (MARS) model and Structural Equation Modeling (SEM), respectively. Based on our experiment, it can be seen clearly that ACILES can be implemented in order to augment microfinance