Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru

• Autor: Quiroz Calderón, Milagro Baldemar
• Formato: artículo
• Fecha de Publicación: 2020
• Institución: Universidad Nacional Mayor de San Marcos
• Repositorio: Revistas - Universidad Nacional Mayor de San Marcos
• Lenguaje: español
• OAI Identifier: oai:ojs.csi.unmsm:article/17697
• Enlace del recurso: https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/17697
• Nivel de acceso: acceso abierto
• Materia: Risk; credit; microfinance; technology; market; Riesgo; crédito; microfinanzas; tecnología; mercado

Objective: Develop a Credit Scoring model for the microcredit portfolio microcredits from a Municipal Banks in the city of Piura. Method: Binary Logistic Regression was applied as a technique to set out a model whose response or dependent variable is a discrete dichotomous variable. Results: The treatment of the database of the microcredit portfolio of the Municipal Banks of the city of Piura, using the binary logistic regression module of the SPSS software version 24, was obtained as a result the probability of default. Conclusions: it achieved a statistical rating model capable to correctly predict the 96.7% of the credits of portfolio of the municipal bank.