Advanced analytical methods for fraud detection: a systematic literature review

Detalhes bibliográficos
Autor(a) principal: Fernandes, Marta Sequeira Rego
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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spelling 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
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TID:203445970
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