In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, may deliver expectations over many application sectors across field. For this to occur, expert systems and rule-based models need overcome limitation of fairness interpretability. Paradigms underlying problem fall within so-called explainable AI (XAI) This report presents work on German credit card dataset...

Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular approaches for building credit scoring models. Despite their popularity, quite a few limitations are known to be associated with these methods, such as being instable with high-dimensional data (also known as combinat...

The primary concern of the rating policies for a banking industry is to develop a more objective, accurate and competitive scoring model to avoid losses from potential bad debt. This study proposes an artificial immune classifier based on the artificial immune network (named AINE-based classifier) to evaluate the applicants’ credit scores. Two experimental credit datasets are used to show the a...

The paper considers a general approach for classifying objects using mathematical programming algorithms. The approach is based on optimizing a utility function, which is quadratic in indicator parameters and is linear in control parameters (which need to be identified). Qualitative characteristics of the utility function, such as monotonicity in some variables, are included using additional co...