CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of Information Systems and Technology Management (Online) |
Texto Completo: | https://www.revistas.usp.br/jistem/article/view/84677 |
Resumo: | The search for efficiency in the cooperative credit sector has led cooperatives to adopt new technology and managerial knowhow. Among the tools that facilitate efficiency, data mining has stood out in recent years as a sophisticated methodology to search for knowledge that is “hidden” in organizations' databases. The process of granting credit is one of the central functions of a credit union; therefore, the use of instruments that support that process is desirable and may become a key factor in credit management. The steps undertaken by the present case study to perform the knowledge discovery process were data selection, data pre-processing and cleanup, data transformation, data mining, and the interpretation and evaluation of results. The results were evaluated through cross-validation of ten sets, repeated in ten simulations. The goal of this study is to develop models to analyze the capacity of a credit union's members to settle their commitments, using a decision tree—C4.5 algorithm and an artificial neural network—multilayer perceptron algorithm. It is concluded that for the problem at hand, the models have statistically similar results and may aid in a cooperative's decision-making process. |
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CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNIONCredit UnionismData MiningDecision TreeArtificial Neural Network.The search for efficiency in the cooperative credit sector has led cooperatives to adopt new technology and managerial knowhow. Among the tools that facilitate efficiency, data mining has stood out in recent years as a sophisticated methodology to search for knowledge that is “hidden” in organizations' databases. The process of granting credit is one of the central functions of a credit union; therefore, the use of instruments that support that process is desirable and may become a key factor in credit management. The steps undertaken by the present case study to perform the knowledge discovery process were data selection, data pre-processing and cleanup, data transformation, data mining, and the interpretation and evaluation of results. The results were evaluated through cross-validation of ten sets, repeated in ten simulations. The goal of this study is to develop models to analyze the capacity of a credit union's members to settle their commitments, using a decision tree—C4.5 algorithm and an artificial neural network—multilayer perceptron algorithm. It is concluded that for the problem at hand, the models have statistically similar results and may aid in a cooperative's decision-making process.TECSI - FEA - Universidade de São Paulo. Faculdade de Economia, Administração, Contabilidade e Atuária2014-08-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionCase Study; Quantitative method.application/pdfhttps://www.revistas.usp.br/jistem/article/view/8467710.4301/10.4301%2FS1807-17752014000200009Journal of Information Systems and Technology Management; v. 11 n. 2 (2014); 379-396Journal of Information Systems and Technology Management; Vol. 11 No. 2 (2014); 379-396Journal of Information Systems and Technology Management; Vol. 11 Núm. 2 (2014); 379-3961807-1775reponame:Journal of Information Systems and Technology Management (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/jistem/article/view/84677/87391Copyright (c) 2018 JISTEM - Journal of Information Systems and Technology Management (Online)info:eu-repo/semantics/openAccessSousa, Marcos de MoraesFigueiredo, Reginaldo Santana2014-09-16T13:25:36Zoai:revistas.usp.br:article/84677Revistahttp://www.scielo.br/scielo.php?script=sci_serial&pid=1807-1775&lng=pt&nrm=isoPUBhttps://old.scielo.br/oai/scielo-oai.php||jistem@usp.br1807-17751807-1775opendoar:2014-09-16T13:25:36Journal of Information Systems and Technology Management (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION |
title |
CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION |
spellingShingle |
CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION Sousa, Marcos de Moraes Credit Unionism Data Mining Decision Tree Artificial Neural Network. |
title_short |
CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION |
title_full |
CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION |
title_fullStr |
CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION |
title_full_unstemmed |
CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION |
title_sort |
CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION |
author |
Sousa, Marcos de Moraes |
author_facet |
Sousa, Marcos de Moraes Figueiredo, Reginaldo Santana |
author_role |
author |
author2 |
Figueiredo, Reginaldo Santana |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Sousa, Marcos de Moraes Figueiredo, Reginaldo Santana |
dc.subject.por.fl_str_mv |
Credit Unionism Data Mining Decision Tree Artificial Neural Network. |
topic |
Credit Unionism Data Mining Decision Tree Artificial Neural Network. |
description |
The search for efficiency in the cooperative credit sector has led cooperatives to adopt new technology and managerial knowhow. Among the tools that facilitate efficiency, data mining has stood out in recent years as a sophisticated methodology to search for knowledge that is “hidden” in organizations' databases. The process of granting credit is one of the central functions of a credit union; therefore, the use of instruments that support that process is desirable and may become a key factor in credit management. The steps undertaken by the present case study to perform the knowledge discovery process were data selection, data pre-processing and cleanup, data transformation, data mining, and the interpretation and evaluation of results. The results were evaluated through cross-validation of ten sets, repeated in ten simulations. The goal of this study is to develop models to analyze the capacity of a credit union's members to settle their commitments, using a decision tree—C4.5 algorithm and an artificial neural network—multilayer perceptron algorithm. It is concluded that for the problem at hand, the models have statistically similar results and may aid in a cooperative's decision-making process. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-08-21 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Case Study; Quantitative method. |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/jistem/article/view/84677 10.4301/10.4301%2FS1807-17752014000200009 |
url |
https://www.revistas.usp.br/jistem/article/view/84677 |
identifier_str_mv |
10.4301/10.4301%2FS1807-17752014000200009 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/jistem/article/view/84677/87391 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 JISTEM - Journal of Information Systems and Technology Management (Online) info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 JISTEM - Journal of Information Systems and Technology Management (Online) |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
TECSI - FEA - Universidade de São Paulo. Faculdade de Economia, Administração, Contabilidade e Atuária |
publisher.none.fl_str_mv |
TECSI - FEA - Universidade de São Paulo. Faculdade de Economia, Administração, Contabilidade e Atuária |
dc.source.none.fl_str_mv |
Journal of Information Systems and Technology Management; v. 11 n. 2 (2014); 379-396 Journal of Information Systems and Technology Management; Vol. 11 No. 2 (2014); 379-396 Journal of Information Systems and Technology Management; Vol. 11 Núm. 2 (2014); 379-396 1807-1775 reponame:Journal of Information Systems and Technology Management (Online) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Journal of Information Systems and Technology Management (Online) |
collection |
Journal of Information Systems and Technology Management (Online) |
repository.name.fl_str_mv |
Journal of Information Systems and Technology Management (Online) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
||jistem@usp.br |
_version_ |
1748936864340901888 |