Using Hybrid Approaches for Credit Application Scoring

Abstract

Using various methods of computational intelligence, scores for credit applications are predicted for making a decision to accept or to reject. Past data about credits accepted in a financial institution are used to develop hybrid models implementing gradient boosting and attention supported neural networks. The performance (Gini scores above 0.7), limitations and further research directions are discussed. © 2023 IEEE.