Estado del arte de Modelos de IA en asignación de créditos bancarios

Abstract

Currently, AI is rapidly expanding, with its algorithms playing a crucial role in research. Integrating AI with bank credit offers a solution to credit decision-making challenges. Credit rating prediction garners significant interest and optimizing this prediction is imperative. The issue of credit for individuals receives considerable attention, influencing services like resource sharing based on credit information. This study aims to provide an updated overview of AI models in allocating Bank Credits in Ecuador through a Systematic Literature Review, combining quantitative and qualitative research methods. Globally, Data Analysis is the primary trend at 55%, with Decision Making being the top recommendation at 58%. In the Ecuadorian context, Data Analysis leads at 83%, while Decision Making is the primary AI usage recommendation, also at 83%.