Predicting Credit Default in an Agricultural Bank: Methods and Issues

Abstract

This study examines the performance of logistic regression, artificial neural networks and adaptive neuro-fuzzy inference system in predicting credit default using data from Farm Credit System. Empirical findings show that credit default predictions vary with empirical model used