Bibliographic citations
Luyo, A., Muñoz, J. (2022). Sistema de gestión de evaluación crediticia en el sector cooperativo de ahorro y crédito con análisis predictivo usando machine learning [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/667864
Luyo, A., Muñoz, J. Sistema de gestión de evaluación crediticia en el sector cooperativo de ahorro y crédito con análisis predictivo usando machine learning [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2022. http://hdl.handle.net/10757/667864
@misc{sunedu/3408577,
title = "Sistema de gestión de evaluación crediticia en el sector cooperativo de ahorro y crédito con análisis predictivo usando machine learning",
author = "Muñoz Cavero, Johan Artemio",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2022"
}
The main objective of the thesis is to propose a solution that automates the credit assessment process in the cooperative’s credit unit, where the credit analysts verify and evaluate the loan applications entered by sales executives, coming from the diverse needs of the partners; however, the default of borrowers, due to internal or external factors, has been a problem that affects the institution's liquidity and the imminent increase in the delinquency rate. Understanding the problematic situation of the credit unit and based on an analysis according to the scenario, the proposed solution is to implement a credit assessment web system with in-house infrastructure and integrated with a cloud-based predictive tool for the credit management process, to streamline the flow of information from partners and, above all, provide a technological predictive tool that supports the analysis of a credit for decision making, especially in cases where the analyst requires expert judgment based on experience or soft skills. In alignment with the three strategic objectives of the cooperative that refer to increasing loan participation, boosting productivity, and diversifying income with reliable and fast information systems that enhance decision making, our technological proposal meets transversally in the operativity of the credit unit and the support in decision making for a business opportunity.
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