Improving Financial Inclusion Using Fuzzy Logic Models to Assess Credit Risk Profiles: A Case Study of Family Farmers in Peru

Soria-Quijaite J.; Ramos-Sandoval R.; Abal R.L.; Ramirez C.C. · International Journal of Fuzzy Logic and Intelligent Systems (2025) · DOI: 10.5391/ijfis.2025.25.2.221

Resumen

Fuzzy logic represents a systematic approach that may prove beneficial in the exploration of financial behavior and credit risk profiles, with the potential to enhance financial inclusion. In this study, fuzzy logic is employed to ascertain the payment behavior indicators of family farmers in Peru. A total of 64 fuzzy rules were validated using the Mamdani method and a fuzzy inference engine was subsequently developed. Consequently, the accuracy of the payment behavior profile of the surveyed farmers was evaluated using a model constructed and assessed with the assistance of a psychometric instrument, which was employed to determine variables such as effective financial decision-making, self-control, and attitude towards money. The payment behavior profile of farmers was considered the dependent variable. The results are used to validate the accuracy of the model and the performance of its architecture and design using the Mamdani method, proposed fuzzy rules, and membership functions used in the fuzzy sets. © The Korean Institute of Intelligent Systems

Instituciones: Universidad Tecnológica del Perú