Propuesta de un sistema inteligente de identificación de riesgo crediticio. Piloto en la oficina Alausí de la Cooperativa de Ahorro y Crédito Riobamba Limitada

Abstract

Abstract: The increase in delinquency indicators in the National Financial System is one of the problems that our country is going through; several political, environmental and social factors have been the cause of the increase continuing to grow. The credit platforms operated in the country provide outdated information. For this reason, the objective of this degree work is to predict the risk of late payment in the Cooperativa de Ahorro y Crédito Riobamba Ltda. Agencia Alausí by identifying non-verbal behaviors and gestures that determine the veracity of the information in a credit analysis. To develop the research, mixed methods were used that included documentary research and interviews were carried out with people who work in the field. The use of identification tables and weighting of non-verbal communication determine the viability of the project. This intelligent system will improve the accuracy of credit evaluation by identifying patterns of non-verbal behavior that cannot be seen with the naked eye. Reduce the processing time of a credit application. Optimize resources such as the use of paper and finally prevent identity theft fraud thanks to its facial identifier.