Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasil
Autor(a) principal: | |
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Data de Publicação: | 2003 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Economia Aplicada |
Texto Completo: | https://www.revistas.usp.br/ecoa/article/view/220228 |
Resumo: | The development of scoring models for credit risk management and behaviour analysis of clients is quite important in the routine of commercial banks, financing companies, credit card operations, marketing units and large department stores. Statistical techniques such as logistic regression, discriminant analysis, decision trees etc., have dominated the literature when the subject is related to credit modelling. An important point remains ignored, however: tracking the performance of theses models and validating their predictive ability after their implementation. In this article we present a methodology to track the stability of credit and behaviour scoring models, checking their predictions through time, in order to avoid problems when granting credit for clients. Several examples are presented in order to illustrate the practical use of our proposal. Our proposal seeks to generate actions to avoid possible operational and modelling failures related to these models, suggesting in some cases that these models be replaced by new models. |
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Economia Aplicada |
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Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasilcreditrisk managementcredit modellingcredit scoringbehaviour scoringThe development of scoring models for credit risk management and behaviour analysis of clients is quite important in the routine of commercial banks, financing companies, credit card operations, marketing units and large department stores. Statistical techniques such as logistic regression, discriminant analysis, decision trees etc., have dominated the literature when the subject is related to credit modelling. An important point remains ignored, however: tracking the performance of theses models and validating their predictive ability after their implementation. In this article we present a methodology to track the stability of credit and behaviour scoring models, checking their predictions through time, in order to avoid problems when granting credit for clients. Several examples are presented in order to illustrate the practical use of our proposal. Our proposal seeks to generate actions to avoid possible operational and modelling failures related to these models, suggesting in some cases that these models be replaced by new models.Universidade de São Paulo, FEA-RP/USP2003-08-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/ecoa/article/view/22022810.11606/1413-8050/ea220228Economia Aplicada; Vol. 7 Núm. 4 (2003); 795-818Economia Aplicada; Vol. 7 No. 4 (2003); 795-818Economia Aplicada; v. 7 n. 4 (2003); 795-8181980-53301413-8050reponame:Economia Aplicadainstname:Universidade de São Paulo (USP)instacron:USPporhttps://www.revistas.usp.br/ecoa/article/view/220228/201070Copyright (c) 2003 Economia Aplicadahttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessLuis Fernando Landa LecumberriDuarte Júnior, Antonio Marcos 2023-12-13T14:37:48Zoai:revistas.usp.br:article/220228Revistahttps://www.revistas.usp.br/ecoaPUBhttps://www.revistas.usp.br/ecoa/oai||revecap@usp.br1980-53301413-8050opendoar:2023-12-13T14:37:48Economia Aplicada - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasil |
title |
Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasil |
spellingShingle |
Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasil Luis Fernando Landa Lecumberri credit risk management credit modelling credit scoring behaviour scoring |
title_short |
Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasil |
title_full |
Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasil |
title_fullStr |
Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasil |
title_full_unstemmed |
Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasil |
title_sort |
Uma metodologia para o gerenciamento de modelos de escoragem em operações de crédito de varejo no Brasil |
author |
Luis Fernando Landa Lecumberri |
author_facet |
Luis Fernando Landa Lecumberri Duarte Júnior, Antonio Marcos |
author_role |
author |
author2 |
Duarte Júnior, Antonio Marcos |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Luis Fernando Landa Lecumberri Duarte Júnior, Antonio Marcos |
dc.subject.por.fl_str_mv |
credit risk management credit modelling credit scoring behaviour scoring |
topic |
credit risk management credit modelling credit scoring behaviour scoring |
description |
The development of scoring models for credit risk management and behaviour analysis of clients is quite important in the routine of commercial banks, financing companies, credit card operations, marketing units and large department stores. Statistical techniques such as logistic regression, discriminant analysis, decision trees etc., have dominated the literature when the subject is related to credit modelling. An important point remains ignored, however: tracking the performance of theses models and validating their predictive ability after their implementation. In this article we present a methodology to track the stability of credit and behaviour scoring models, checking their predictions through time, in order to avoid problems when granting credit for clients. Several examples are presented in order to illustrate the practical use of our proposal. Our proposal seeks to generate actions to avoid possible operational and modelling failures related to these models, suggesting in some cases that these models be replaced by new models. |
publishDate |
2003 |
dc.date.none.fl_str_mv |
2003-08-05 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.revistas.usp.br/ecoa/article/view/220228 10.11606/1413-8050/ea220228 |
url |
https://www.revistas.usp.br/ecoa/article/view/220228 |
identifier_str_mv |
10.11606/1413-8050/ea220228 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://www.revistas.usp.br/ecoa/article/view/220228/201070 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2003 Economia Aplicada http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2003 Economia Aplicada http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade de São Paulo, FEA-RP/USP |
publisher.none.fl_str_mv |
Universidade de São Paulo, FEA-RP/USP |
dc.source.none.fl_str_mv |
Economia Aplicada; Vol. 7 Núm. 4 (2003); 795-818 Economia Aplicada; Vol. 7 No. 4 (2003); 795-818 Economia Aplicada; v. 7 n. 4 (2003); 795-818 1980-5330 1413-8050 reponame:Economia Aplicada instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Economia Aplicada |
collection |
Economia Aplicada |
repository.name.fl_str_mv |
Economia Aplicada - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
||revecap@usp.br |
_version_ |
1800221693638082560 |