Systemic acquired critique of credit card deception exposure through machine learning

Detalhes bibliográficos
Autor(a) principal: Dantas, Rui
Data de Publicação: 2022
Outros Autores: Firdaus, Raheela, Jaleel, Dr. Farrokh, Mata, Pedro, Mata, Mário Nuno, Li, Gang
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.21/15504
Resumo: Artigo publicado em revista científica internacional
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spelling Systemic acquired critique of credit card deception exposure through machine learningAlgorithmsCredit cardDatabaseFraudFinancial organizationMachine learningDatasetArtigo publicado em revista científica internacionalA wide range of recent studies are focusing on current issues of financial fraud, especially concerning cybercrimes. The reason behind this is even with improved security, a great amount of money loss occurs every year due to credit card fraud. In recent days, ATM fraud has decreased, while credit card fraud has increased. This study examines articles from five foremost databases. The literature review is designed using extraction by database, keywords, year, articles, authors, and performance measures based on data used in previous research, future research directions and purpose of the article. This study identifies the crucial gaps which ultimately allow research opportunities in this fraud detection process by utilizing knowledge from the machine learning domain. Our findings prove that this research area has become most dominant in the last ten years. We accessed both supervised and unsupervised machine learning techniques to detect cybercrime and management techniques which provide evidence for the effectiveness of machine learning techniques to control cybercrime in the credit card industry. Results indicated that there is room for further research to obtain better results than existing ones on the basis of both quantitative and qualitative research analysis.MDPIRCIPLDantas, RuiFirdaus, RaheelaJaleel, Dr. FarrokhMata, PedroMata, Mário NunoLi, Gang2023-02-08T16:21:41Z2022-102022-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/15504engDantas, R. M., Firdaus, R., Jaleel, F., Neves Mata, P., Mata, M. N., & Li, G. (2022). Systemic Acquired Critique of Credit Card Deception Exposure through Machine Learning. Journal of Open Innovation: Technology, Market, and Complexity, 8(4), 192. https://doi.org/10.3390/joitmc8040192https://doi.org/10.3390/joitmc8040192info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-03T10:13:07Zoai:repositorio.ipl.pt:10400.21/15504Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:23:09.912757Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Systemic acquired critique of credit card deception exposure through machine learning
title Systemic acquired critique of credit card deception exposure through machine learning
spellingShingle Systemic acquired critique of credit card deception exposure through machine learning
Dantas, Rui
Algorithms
Credit card
Database
Fraud
Financial organization
Machine learning
Dataset
title_short Systemic acquired critique of credit card deception exposure through machine learning
title_full Systemic acquired critique of credit card deception exposure through machine learning
title_fullStr Systemic acquired critique of credit card deception exposure through machine learning
title_full_unstemmed Systemic acquired critique of credit card deception exposure through machine learning
title_sort Systemic acquired critique of credit card deception exposure through machine learning
author Dantas, Rui
author_facet Dantas, Rui
Firdaus, Raheela
Jaleel, Dr. Farrokh
Mata, Pedro
Mata, Mário Nuno
Li, Gang
author_role author
author2 Firdaus, Raheela
Jaleel, Dr. Farrokh
Mata, Pedro
Mata, Mário Nuno
Li, Gang
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Dantas, Rui
Firdaus, Raheela
Jaleel, Dr. Farrokh
Mata, Pedro
Mata, Mário Nuno
Li, Gang
dc.subject.por.fl_str_mv Algorithms
Credit card
Database
Fraud
Financial organization
Machine learning
Dataset
topic Algorithms
Credit card
Database
Fraud
Financial organization
Machine learning
Dataset
description Artigo publicado em revista científica internacional
publishDate 2022
dc.date.none.fl_str_mv 2022-10
2022-10-01T00:00:00Z
2023-02-08T16:21:41Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/15504
url http://hdl.handle.net/10400.21/15504
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Dantas, R. M., Firdaus, R., Jaleel, F., Neves Mata, P., Mata, M. N., & Li, G. (2022). Systemic Acquired Critique of Credit Card Deception Exposure through Machine Learning. Journal of Open Innovation: Technology, Market, and Complexity, 8(4), 192. https://doi.org/10.3390/joitmc8040192
https://doi.org/10.3390/joitmc8040192
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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