fuzzy relational compositions, Bandler-Kohout products, excluding features, generalized quantifiers, credit assessment, credit scoring, credit evaluation

We show that fuzzy relational compositions assist in evaluating customers creditability (credit scoring) which is one of the most important problems in the financial industry. The purpose is to classify a given customer into two classes of accepted or rejected and to help loan officers to make a better decision. We illustrate an experimental example with initial values provided by a bank expert and use LFL R-package as the practical tool to calculate the compositions for our application. The concept of so-called generalized quantifiers and excluding features incorporating in the compositions will be employed as well.