La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY 4.0 Internacional, https://creativecommons.org/licenses/by/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico revista_cya@fca.unam.mx.
Ver términos de la licencia
Facultad de Contaduría y Administración, UNAM
Revista
Repositorio
Contacto
Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx
Medina Reyes, José Eduardo, et al. (2024). Credit risk management analysis: An application of fuzzy theory to forecast the probability of default in a financial institution. Contaduría y Administración; Vol. 69, Núm. 1. Recuperado de https://repositorio.unam.mx/contenidos/4158951
Autor(es)
Medina Reyes, José Eduardo; Instituto Politécnico Nacional; Castro Pérez, Judith Jazmin; Instituto Politécnico Nacional; Cruz Aké, Salvador; Instituto Politécnico Nacional
Tipo
Artículo de Investigación
Área del conocimiento
Ciencias Sociales y Económicas
Título
Credit risk management analysis: An application of fuzzy theory to forecast the probability of default in a financial institution
Fecha
2023-06-28
Resumen
The aim of this research is to model the credit risk, estimating the impact of operational risk and customer features, using the fuzzy version of the LOGIT model. For this purpose, it proposes a Fuzzy Financial Risk Management Model, composed of a Credit score estimated with a Fuzzy LOGIT model and a Fuzzy Triangular Value-at-Risk adjustment. For this purpose, the probability of default of 3,746 commercial loans was predicted. The results show that the proposed methodology recognises the relationship between credit and operational risk better than traditional models. In conclusion, the proposed model provides an assessment of risk and measures it in terms of interest rate basis points. In addition, it provides the expected loss for three degrees of uncertainty. Therefore, the proposed methodology provides a suitable support for the design of credit policies in a financial institution.
Tema
C49; G21; G32; Fuzzy Statistics; Data Analysis; Fuzzy Control; Credit Risk; Operational Risk
Idioma
spa
ISSN
ISSN electrónico: 2448-8410; ISSN impreso: 0186-1042
