A systematic review of machine learning models applied in debt collection operations Uma revisão sistemática de modelos de machine learning aplicados em operações financeiras de cobranças de dívidas

dc.contributor.authorMartins J.A.
dc.contributor.authorVallim-Filho A.R.A.
dc.date.accessioned2024-09-01T06:16:04Z
dc.date.available2024-09-01T06:16:04Z
dc.date.issued2024
dc.description.abstract© 2024, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.Brazil is facing high default rates, due in part to the pandemic, leading to the search for new debt collection strategies. Machine Learning (ML), successfully used in numerous areas, is an ally to increase the effectiveness of these operations. This article seeks to present a current overview of research on ML applications in debt collection operations, through a Systematic Literature Review. The PICO methodology was used, initially identifying 41 documents, of which 11 underwent systematic review. The results showed four objectives pursued by the studies: default prediction, personalization of collection strategies, optimization of debt recovery actions and credit recovery prediction. And the main algorithms used were Decision Tree, Logistic Regression, Random Forest, Naive Bayes, Artificial Neural Network and Deep Learning. The results revealed that ML is still little explored in this area, offering potential for substantial research advances.
dc.description.firstpage5
dc.description.issuenumberSpecial issue E54
dc.description.lastpage21
dc.description.volume2024
dc.identifier.doi10.17013/risti.54.5-21
dc.identifier.issnNone
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/39265
dc.relation.ispartofRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
dc.rightsAcesso Restrito
dc.subject.otherlanguageDebt collection
dc.subject.otherlanguageFinancial operations, Systematic literature review
dc.subject.otherlanguageMachine learning
dc.titleA systematic review of machine learning models applied in debt collection operations Uma revisão sistemática de modelos de machine learning aplicados em operações financeiras de cobranças de dívidas
dc.typeArtigo
local.scopus.citations0
local.scopus.eid2-s2.0-85201603548
local.scopus.updated2025-04-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85201603548&origin=inward
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