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Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa

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Resumo:The world has been experiencing paradigm shifts, with emerging technologies becoming an ever more formidable reality. Nowadays, organizations worldwide must stay current and aligned with this evolution in terms of their processes, harnessing artificial intelligence (AI) techniques as a resource. Only by doing so can they hope to maintain a competitive edge. Auditing plays a crucial role in comprehending and scrutinizing companies' processes to identify any inconsistencies or irregularities in their financial records. In this regard, the convergence of auditing and AI has been gaining prominence, particularly within major auditing firms. The Portuguese Air Force (PAF), recognizing the impact of emerging trends, needs to determine the most effective ways where to apply AI, and one of those areas is internal control. As an integral part of Central Administration, it bears the responsibility of being accountable and therefore necessitates stringent, cohesive, and transparent internal control. With this objective in mind, the utilization of AI, particularly in budgetary control, offers an enticing opportunity for exploring the implementation of new technologies to address or enhance certain existing deficiencies. The results of the study show the usefulness of machine learning algorithms in predicting the occurrence of deviations and their contribution to budgetary control.
Autores principais:Palmas, Pedro de Oliveira
Assunto:Artificial Intelligence Machine Learning Supervised Learning Internal Audit Portuguese Armed Forces Budget Inteligência Artificial Machine Learning Aprendizagem Supervisionada Auditoria Interna Forças Armadas Portuguesas Orçamento
Ano:2023
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade de Lisboa
Idioma:português
Origem:Repositório da Universidade de Lisboa
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author Palmas, Pedro de Oliveira
author_facet Palmas, Pedro de Oliveira
author_role author
contributor_name_str_mv Samagaio, António
Evangelista, Elsa Pereira
Repositório Científico de Acesso Aberto da ULisboa
country_str PT
creators_json_txt [{\"Person.name\":\"Palmas, Pedro de Oliveira\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Samagaio, António
Evangelista, Elsa Pereira
Repositório Científico de Acesso Aberto da ULisboa
datacite.creators.creator.creatorName.fl_str_mv Palmas, Pedro de Oliveira
datacite.date.Accepted.fl_str_mv 2023-10-01T00:00:00Z
datacite.date.available.fl_str_mv 2023-12-14T11:47:16Z
datacite.date.embargoed.fl_str_mv 2023-12-14T11:47:16Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Artificial Intelligence
Machine Learning
Supervised Learning
Internal Audit
Portuguese Armed Forces
Budget
Inteligência Artificial
Machine Learning
Aprendizagem Supervisionada
Auditoria Interna
Forças Armadas Portuguesas
Orçamento
datacite.titles.title.fl_str_mv Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa
dc.contributor.none.fl_str_mv Samagaio, António
Evangelista, Elsa Pereira
Repositório Científico de Acesso Aberto da ULisboa
dc.creator.none.fl_str_mv Palmas, Pedro de Oliveira
dc.date.Accepted.fl_str_mv 2023-10-01T00:00:00Z
dc.date.available.fl_str_mv 2023-12-14T11:47:16Z
dc.date.embargoed.fl_str_mv 2023-12-14T11:47:16Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10400.5/29606
dc.language.none.fl_str_mv por
dc.publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Artificial Intelligence
Machine Learning
Supervised Learning
Internal Audit
Portuguese Armed Forces
Budget
Inteligência Artificial
Machine Learning
Aprendizagem Supervisionada
Auditoria Interna
Forças Armadas Portuguesas
Orçamento
dc.title.fl_str_mv Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_bdcc
description The world has been experiencing paradigm shifts, with emerging technologies becoming an ever more formidable reality. Nowadays, organizations worldwide must stay current and aligned with this evolution in terms of their processes, harnessing artificial intelligence (AI) techniques as a resource. Only by doing so can they hope to maintain a competitive edge. Auditing plays a crucial role in comprehending and scrutinizing companies' processes to identify any inconsistencies or irregularities in their financial records. In this regard, the convergence of auditing and AI has been gaining prominence, particularly within major auditing firms. The Portuguese Air Force (PAF), recognizing the impact of emerging trends, needs to determine the most effective ways where to apply AI, and one of those areas is internal control. As an integral part of Central Administration, it bears the responsibility of being accountable and therefore necessitates stringent, cohesive, and transparent internal control. With this objective in mind, the utilization of AI, particularly in budgetary control, offers an enticing opportunity for exploring the implementation of new technologies to address or enhance certain existing deficiencies. The results of the study show the usefulness of machine learning algorithms in predicting the occurrence of deviations and their contribution to budgetary control.
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eu_rights_str_mv openAccess
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fulltext.url.fl_str_mv https://repositorio.ulisboa.pt/bitstreams/a7a405e3-01a3-4304-8795-65101502dd84/download
id ul_3ecc89f95c8b86dffdd0f71acba24342
identifier.url.fl_str_mv http://hdl.handle.net/10400.5/29606
instacron_str ul
institution Universidade de Lisboa
instname_str Universidade de Lisboa
language por
network_acronym_str ul
network_name_str Repositório da Universidade de Lisboa
oai_identifier_str oai:repositorio.ulisboa.pt:10400.5/29606
organization_str_mv urn:organizationAcronym:ul
person_str_mv Palmas, Pedro de Oliveira
publishDate 2023
publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
reponame_str Repositório da Universidade de Lisboa
repository_id_str urn:repositoryAcronym:ul
service_str_mv urn:repositoryAcronym:ul
spelling porInstituto Superior de Economia e Gestãopt_PTThe world has been experiencing paradigm shifts, with emerging technologies becoming an ever more formidable reality. Nowadays, organizations worldwide must stay current and aligned with this evolution in terms of their processes, harnessing artificial intelligence (AI) techniques as a resource. Only by doing so can they hope to maintain a competitive edge. Auditing plays a crucial role in comprehending and scrutinizing companies' processes to identify any inconsistencies or irregularities in their financial records. In this regard, the convergence of auditing and AI has been gaining prominence, particularly within major auditing firms. The Portuguese Air Force (PAF), recognizing the impact of emerging trends, needs to determine the most effective ways where to apply AI, and one of those areas is internal control. As an integral part of Central Administration, it bears the responsibility of being accountable and therefore necessitates stringent, cohesive, and transparent internal control. With this objective in mind, the utilization of AI, particularly in budgetary control, offers an enticing opportunity for exploring the implementation of new technologies to address or enhance certain existing deficiencies. The results of the study show the usefulness of machine learning algorithms in predicting the occurrence of deviations and their contribution to budgetary control.application/pdfpt_PTAplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea PortuguesaPalmas, Pedro de OliveiraSamagaio, AntónioEvangelista, Elsa PereiraHostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.pt2023-12-14T11:47:16Z2023-102023-10-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/29606http://purl.org/coar/access_right/c_abf2open accessArtificial IntelligenceMachine LearningSupervised LearningInternal AuditPortuguese Armed ForcesBudgetInteligência ArtificialMachine LearningAprendizagem SupervisionadaAuditoria InternaForças Armadas PortuguesasOrçamento2578604 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/a7a405e3-01a3-4304-8795-65101502dd84/download
spellingShingle Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa
Palmas, Pedro de Oliveira
Artificial Intelligence
Machine Learning
Supervised Learning
Internal Audit
Portuguese Armed Forces
Budget
Inteligência Artificial
Machine Learning
Aprendizagem Supervisionada
Auditoria Interna
Forças Armadas Portuguesas
Orçamento
status SINGLETON
subject.fl_str_mv Artificial Intelligence
Machine Learning
Supervised Learning
Internal Audit
Portuguese Armed Forces
Budget
Inteligência Artificial
Machine Learning
Aprendizagem Supervisionada
Auditoria Interna
Forças Armadas Portuguesas
Orçamento
title Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa
title_full Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa
title_fullStr Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa
title_full_unstemmed Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa
title_short Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa
title_sort Aplicação de machine learning na previsão de desvios e controlo orçamental na Força Aérea Portuguesa
topic Artificial Intelligence
Machine Learning
Supervised Learning
Internal Audit
Portuguese Armed Forces
Budget
Inteligência Artificial
Machine Learning
Aprendizagem Supervisionada
Auditoria Interna
Forças Armadas Portuguesas
Orçamento
topic_facet Artificial Intelligence
Machine Learning
Supervised Learning
Internal Audit
Portuguese Armed Forces
Budget
Inteligência Artificial
Machine Learning
Aprendizagem Supervisionada
Auditoria Interna
Forças Armadas Portuguesas
Orçamento
url http://hdl.handle.net/10400.5/29606
visible 1