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

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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:&nbs...

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Detalles Bibliográficos
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
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spelling Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-PeruCredit scoring una herramienta para minimizar el riesgo de crédito de las instituciones microfinancieras-PerúQuiroz Calderón, Milagro BaldemarRiskcreditmicrofinancetechnologymarketRiesgocréditomicrofinanzastecnologíamercadoObjective: 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.Objetivo: Plantear un modelo de Credit Scoring para la cartera de microcréditos de una Caja Municipal de la ciudad de Piura. Método: Se aplicó la Regresión Logística Binaria como técnica para plantear un modelo cuya variable respuesta o dependiente es una variable discreta dicotómica. Resultados: El tratamiento de la base de datos de la cartera de microcréditos de la Caja Municipal de la ciudad de Piura, mediante el módulo de regresión logística binaria del Software SPSS versión 24, se obtuvo como resultado la probabilidad de default. Conclusiones: Se logra obtener un modelo de calificación estadística capaz de predecir correctamente el 96,7% de los créditos de la cartera de la Caja Municipal.Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Contables2020-05-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttps://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/1769710.15381/quipu.v28i56.17697Quipukamayoc; Vol. 28 Núm. 56 (2020); 69-75Quipukamayoc; Vol. 28 No. 56 (2020); 69-751609-81961560-9103reponame:Revistas - Universidad Nacional Mayor de San Marcosinstname:Universidad Nacional Mayor de San Marcosinstacron:UNMSMspahttps://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/17697/14859https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/17697/14870Derechos de autor 2020 Milagro Baldemar Quiroz Calderónhttps://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessoai:ojs.csi.unmsm:article/176972020-06-16T16:55:52Z
dc.title.none.fl_str_mv Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru
Credit scoring una herramienta para minimizar el riesgo de crédito de las instituciones microfinancieras-Perú
title Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru
spellingShingle Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru
Quiroz Calderón, Milagro Baldemar
Risk
credit
microfinance
technology
market
Riesgo
crédito
microfinanzas
tecnología
mercado
title_short Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru
title_full Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru
title_fullStr Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru
title_full_unstemmed Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru
title_sort Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru
dc.creator.none.fl_str_mv Quiroz Calderón, Milagro Baldemar
author Quiroz Calderón, Milagro Baldemar
author_facet Quiroz Calderón, Milagro Baldemar
author_role author
dc.subject.none.fl_str_mv Risk
credit
microfinance
technology
market
Riesgo
crédito
microfinanzas
tecnología
mercado
topic Risk
credit
microfinance
technology
market
Riesgo
crédito
microfinanzas
tecnología
mercado
description 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.
publishDate 2020
dc.date.none.fl_str_mv 2020-05-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/17697
10.15381/quipu.v28i56.17697
url https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/17697
identifier_str_mv 10.15381/quipu.v28i56.17697
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/17697/14859
https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/17697/14870
dc.rights.none.fl_str_mv Derechos de autor 2020 Milagro Baldemar Quiroz Calderón
https://creativecommons.org/licenses/by-nc-sa/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2020 Milagro Baldemar Quiroz Calderón
https://creativecommons.org/licenses/by-nc-sa/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/html
dc.publisher.none.fl_str_mv Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Contables
publisher.none.fl_str_mv Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Contables
dc.source.none.fl_str_mv Quipukamayoc; Vol. 28 Núm. 56 (2020); 69-75
Quipukamayoc; Vol. 28 No. 56 (2020); 69-75
1609-8196
1560-9103
reponame:Revistas - Universidad Nacional Mayor de San Marcos
instname:Universidad Nacional Mayor de San Marcos
instacron:UNMSM
instname_str Universidad Nacional Mayor de San Marcos
instacron_str UNMSM
institution UNMSM
reponame_str Revistas - Universidad Nacional Mayor de San Marcos
collection Revistas - Universidad Nacional Mayor de San Marcos
repository.name.fl_str_mv
repository.mail.fl_str_mv
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Credit scoring a tool to minimize the credit risk ok the micro-financial institutions-Peru
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