Advanced analytical methods for fraud detection: a systematic literature review
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.26/48682 |
Resumo: | The developments of the digital era demand new ways of producing goods and rendering services. This fast-paced evolution in the companies implies a new approach from the auditors, who must keep up with the constant transformation. With the dynamic dimensions of data, it is important to seize the opportunity to add value to the companies. The need to apply more robust methods to detect fraud is evident. In this thesis the use of advanced analytical methods for fraud detection will be investigated, through the analysis of the existent literature on this topic. Both a systematic review of the literature and a bibliometric approach will be applied to the most appropriate database to measure the scientific production and current trends. This study intends to contribute to the academic research that have been conducted, in order to centralize the existing information on this topic. |
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Advanced analytical methods for fraud detection: a systematic literature reviewBig dataSystematic literature reviewBibliometric IndicatorsFraud detectionAdvanced analytical methodsThe developments of the digital era demand new ways of producing goods and rendering services. This fast-paced evolution in the companies implies a new approach from the auditors, who must keep up with the constant transformation. With the dynamic dimensions of data, it is important to seize the opportunity to add value to the companies. The need to apply more robust methods to detect fraud is evident. In this thesis the use of advanced analytical methods for fraud detection will be investigated, through the analysis of the existent literature on this topic. Both a systematic review of the literature and a bibliometric approach will be applied to the most appropriate database to measure the scientific production and current trends. This study intends to contribute to the academic research that have been conducted, in order to centralize the existing information on this topic.Pedrosa, Isabel Maria MendesLaureano, Raul Manuel SilvaRepositório ComumFernandes, Marta Sequeira Rego2024-01-04T17:47:30Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.26/48682TID:203445970enginfo: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:RCAAP2024-01-11T02:15:41Zoai:comum.rcaap.pt:10400.26/48682Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:35:49.684903Repositório 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 |
Advanced analytical methods for fraud detection: a systematic literature review |
title |
Advanced analytical methods for fraud detection: a systematic literature review |
spellingShingle |
Advanced analytical methods for fraud detection: a systematic literature review Fernandes, Marta Sequeira Rego Big data Systematic literature review Bibliometric Indicators Fraud detection Advanced analytical methods |
title_short |
Advanced analytical methods for fraud detection: a systematic literature review |
title_full |
Advanced analytical methods for fraud detection: a systematic literature review |
title_fullStr |
Advanced analytical methods for fraud detection: a systematic literature review |
title_full_unstemmed |
Advanced analytical methods for fraud detection: a systematic literature review |
title_sort |
Advanced analytical methods for fraud detection: a systematic literature review |
author |
Fernandes, Marta Sequeira Rego |
author_facet |
Fernandes, Marta Sequeira Rego |
author_role |
author |
dc.contributor.none.fl_str_mv |
Pedrosa, Isabel Maria Mendes Laureano, Raul Manuel Silva Repositório Comum |
dc.contributor.author.fl_str_mv |
Fernandes, Marta Sequeira Rego |
dc.subject.por.fl_str_mv |
Big data Systematic literature review Bibliometric Indicators Fraud detection Advanced analytical methods |
topic |
Big data Systematic literature review Bibliometric Indicators Fraud detection Advanced analytical methods |
description |
The developments of the digital era demand new ways of producing goods and rendering services. This fast-paced evolution in the companies implies a new approach from the auditors, who must keep up with the constant transformation. With the dynamic dimensions of data, it is important to seize the opportunity to add value to the companies. The need to apply more robust methods to detect fraud is evident. In this thesis the use of advanced analytical methods for fraud detection will be investigated, through the analysis of the existent literature on this topic. Both a systematic review of the literature and a bibliometric approach will be applied to the most appropriate database to measure the scientific production and current trends. This study intends to contribute to the academic research that have been conducted, in order to centralize the existing information on this topic. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023 2023-01-01T00:00:00Z 2024-01-04T17:47:30Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.26/48682 TID:203445970 |
url |
http://hdl.handle.net/10400.26/48682 |
identifier_str_mv |
TID:203445970 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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.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 |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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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1799136833624342528 |