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Analytical models to identify financial crime patterns: a systematic literature review [Modelos analíticos para identificar patrones de delitos financieros: Una revisión sistemática de la literatura]

dc.contributor.authorOrtíz M.M
dc.contributor.authorMarín L.M.G
dc.contributor.authorVillegas H.H.J
dc.contributor.authorEscobar C.C.P.
dc.date.accessioned2023-10-24T19:24:45Z
dc.date.available2023-10-24T19:24:45Z
dc.date.created2022
dc.identifier.issn16469895
dc.identifier.urihttp://hdl.handle.net/11407/7994
dc.description.abstractOne of the greatest challenges facing financial institutions today is the risk of financial crimes that are increasingly sophisticated and global in nature, considering the increasing trends of some types of modalities. For this reason, a systematic literature review on the subject was developed to find out which analytical models are the most used and we managed to detect anomalous situations. From this review, it was identified that, thanks to technology and supervised analytical models such as Support Vector Machine (SVM), Neural Networks, among others, many of the threats that exist in the market today can be considerably mitigated and in this way, it is important to prevent million-dollar losses, however, according to the literature, it is important to take into account that one of the main difficulties in detecting fraud or any other financial crime is unbalanced data, since this implies that the results generated probably show a bias towards the majority class and, in extreme cases, may completely ignore the minority class. © 2022, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.eng
dc.language.isospa
dc.publisherAssociacao Iberica de Sistemas e Tecnologias de Informacao
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85136270393&partnerID=40&md5=a7432c20b91ce25b3d5393519edbc6d4
dc.sourceRev. Iberica Sist. Tecnol. Inf.
dc.sourceRISTI - Revista Iberica de Sistemas e Tecnologias de Informacaoeng
dc.subjectAnalytical modelseng
dc.subjectFinancial crimeseng
dc.subjectMachine Learningeng
dc.titleAnalytical models to identify financial crime patterns: a systematic literature review [Modelos analíticos para identificar patrones de delitos financieros: Una revisión sistemática de la literatura]eng
dc.typeArticle
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programCiencias Básicasspa
dc.publisher.programIngeniería de Sistemasspa
dc.type.spaArtículo
dc.relation.citationvolume2022
dc.relation.citationissueE49
dc.relation.citationstartpage586
dc.relation.citationendpage598
dc.publisher.facultyFacultad de Ingenieríasspa
dc.publisher.facultyFacultad de Ciencias Básicasspa
dc.affiliationOrtíz, M.M., Estudiante Maestría en Modelación y Ciencia Computacional, Universidad de Medellín, Antioquia, Colombia
dc.affiliationMarín, L.M.G., Facultad de Ingenierías, Universidad de Medellín, Antioquia, Colombia
dc.affiliationVillegas, H.H.J., Facultad de Ciencias Básicas, Universidad de Medellín, Antioquia, Colombia
dc.affiliationEscobar, C.C.P., Facultad de Ciencias Básicas, Universidad de Medellín, Antioquia, Colombia
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dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.instnameinstname:Universidad de Medellín


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