Using multi-state markov models to identify credit card risk

dc.contributor.authorRINALDO ARTES
dc.contributor.authorRégis, Daniel Evangelista
dc.coverage.cidadeSão Paulopt_BR
dc.coverage.paisBrasilpt_BR
dc.creatorRégis, Daniel Evangelista
dc.date.accessioned2022-08-15T14:56:27Z
dc.date.available2022-08-15T14:56:27Z
dc.date.issued2016
dc.description.notesTexto completopt_BR
dc.description.otherThe main interest of this work is to analyze the application of multi-state Markov models to evaluate credit card risk by investigating the characteristics of different state transitions in client-institution relationships over time, thereby generating score models for various purposes. We also used logistic regression models to compare the results with those obtained using multi-state Markov models. The models were applied to an actual database of a Brazilian financial institution. In this application, multi-state Markov models performed better than logistic regression models in predicting default risk, and logistic regression models performed better in predicting cancellation risk.pt_BR
dc.format.extentp. 220-344pt_BR
dc.format.mediumDigitalpt_BR
dc.identifier.doihttp://dx.doi.org/10.1590/0103-6513.160814pt_BR
dc.identifier.issn01036513pt_BR
dc.identifier.issn19805411pt_BR
dc.identifier.issue2pt_BR
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/3990
dc.identifier.volume26pt_BR
dc.language.isoInglêspt_BR
dc.publisherAssociação Brasileira de Engenharia de Produçãopt_BR
dc.relation.ispartofProductionpt_BR
dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DOS USUÁRIOS INDIVIDUAIS VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITORpt_BR
dc.subject.keywordscredit scoringpt_BR
dc.subject.keywordssurvival analysispt_BR
dc.subject.keywordsMulti-state Markov modelspt_BR
dc.subject.keywordsCredit cardspt_BR
dc.subject.keywordsMarkov processespt_BR
dc.titleUsing multi-state markov models to identify credit card riskpt_BR
dc.typejournal article
dspace.entity.typePublication
local.subject.cnpqCiências Exatas e da Terrapt_BR
local.typeArtigo Científicopt_BR
relation.isAuthorOfPublication8b791c94-f3e5-4e04-af26-594195a8f576
relation.isAuthorOfPublication.latestForDiscovery8b791c94-f3e5-4e04-af26-594195a8f576

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