State of the art of artificial intelligence in internal audit context
Main Author: | |
---|---|
Publication Date: | 2020 |
Other Authors: | , |
Language: | por |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10071/22739 |
Summary: | Artificial intelligence (AI) is a technological field that stands out for what can do and for the advantages that can provide to various sectors of activity. An internal audit could benefit from the introduction of AI in its tasks, namely though the automation of audit processes that make it faster and more efficient allowing an increase in the degree of complexity of the tasks that internal auditors may perform. This will enhance the skills of internal auditors in fields like the determination of business processes and associated risks and controls in anticipated detection of fraud and the following up of anomalies in real-time. This article features a set of technologies of AI and the set of benefits it adds to the internal audit. Two models of internal audit applied to artificial intelligence demonstrate how internal audit and internal auditors must adapt to the new reality of AI, by not losing their purpose and by bringing benefits to organizations. |
id |
RCAP_f315bece4815a8a0f4e6be93c0d52d5d |
---|---|
oai_identifier_str |
oai:repositorio.iscte-iul.pt:10071/22739 |
network_acronym_str |
RCAP |
network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository_id_str |
https://opendoar.ac.uk/repository/7160 |
spelling |
State of the art of artificial intelligence in internal audit contextArtificial intelligenceInternal auditBig dataMachine learningText miningProcess miningArtificial intelligence (AI) is a technological field that stands out for what can do and for the advantages that can provide to various sectors of activity. An internal audit could benefit from the introduction of AI in its tasks, namely though the automation of audit processes that make it faster and more efficient allowing an increase in the degree of complexity of the tasks that internal auditors may perform. This will enhance the skills of internal auditors in fields like the determination of business processes and associated risks and controls in anticipated detection of fraud and the following up of anomalies in real-time. This article features a set of technologies of AI and the set of benefits it adds to the internal audit. Two models of internal audit applied to artificial intelligence demonstrate how internal audit and internal auditors must adapt to the new reality of AI, by not losing their purpose and by bringing benefits to organizations.IEEE2021-06-15T10:51:18Z2020-01-01T00:00:00Z20202021-06-15T11:48:32Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10071/22739por978-989-54659-0-32166-072710.23919/CISTI49556.2020.9140863Couceiro, B.Pedrosa, I.Marini, A.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-07-07T02:49:18Zoai:repositorio.iscte-iul.pt:10071/22739Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T18:08:11.509761Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
State of the art of artificial intelligence in internal audit context |
title |
State of the art of artificial intelligence in internal audit context |
spellingShingle |
State of the art of artificial intelligence in internal audit context Couceiro, B. Artificial intelligence Internal audit Big data Machine learning Text mining Process mining |
title_short |
State of the art of artificial intelligence in internal audit context |
title_full |
State of the art of artificial intelligence in internal audit context |
title_fullStr |
State of the art of artificial intelligence in internal audit context |
title_full_unstemmed |
State of the art of artificial intelligence in internal audit context |
title_sort |
State of the art of artificial intelligence in internal audit context |
author |
Couceiro, B. |
author_facet |
Couceiro, B. Pedrosa, I. Marini, A. |
author_role |
author |
author2 |
Pedrosa, I. Marini, A. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Couceiro, B. Pedrosa, I. Marini, A. |
dc.subject.por.fl_str_mv |
Artificial intelligence Internal audit Big data Machine learning Text mining Process mining |
topic |
Artificial intelligence Internal audit Big data Machine learning Text mining Process mining |
description |
Artificial intelligence (AI) is a technological field that stands out for what can do and for the advantages that can provide to various sectors of activity. An internal audit could benefit from the introduction of AI in its tasks, namely though the automation of audit processes that make it faster and more efficient allowing an increase in the degree of complexity of the tasks that internal auditors may perform. This will enhance the skills of internal auditors in fields like the determination of business processes and associated risks and controls in anticipated detection of fraud and the following up of anomalies in real-time. This article features a set of technologies of AI and the set of benefits it adds to the internal audit. Two models of internal audit applied to artificial intelligence demonstrate how internal audit and internal auditors must adapt to the new reality of AI, by not losing their purpose and by bringing benefits to organizations. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01T00:00:00Z 2020 2021-06-15T10:51:18Z 2021-06-15T11:48:32Z |
dc.type.driver.fl_str_mv |
conference object |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/22739 |
url |
http://hdl.handle.net/10071/22739 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
978-989-54659-0-3 2166-0727 10.23919/CISTI49556.2020.9140863 |
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 |
IEEE |
publisher.none.fl_str_mv |
IEEE |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
_version_ |
1833597210058555392 |