Abstract
Government audit, characterized by systematic examinations and evaluations of public sector organizations, is pivotal in ensuring the integrity, transparency, and accountability of public finances. Given this scenario, this paper presents a comprehensive exploration of the integration of Machine Learning (ML) within Government Auditing, with a specific focus on financial statements, and to study how ML has influenced the analysis and decision-making of the auditors. Following the PRISMA methodology, this literature review explored publications from the past five years using keywords in both English and Portuguese to ensure comprehensive coverage. The review revealed the multifaceted applications of ML in various contexts of financial auditing within governments worldwide, elucidating the diverse approaches employed in these scenarios and their success rates, providing valuable insights into emerging trends and best practices. Overall, this paper contributes to advancing knowledge and understanding of ML in Government Auditing, providing valuable insights for practitioners, policymakers, and researchers in the field.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
AICPA: what is a governmental audit? https://us.aicpa.org/interestareas/governmentalauditquality/information-on-governmental-audits
Carmo, P.N.S.D., Souza, B.F.D., Reis, M.V.G.D., Vieira, J.C.: Aprendizado de máquina em ações de controle no tribunal de contas do estado do maranhão. VII Jornada de Informática do Maranhão (2018)
Costa, M.B., Bastos, P.R.L.: Alice, monica, adele, sofia, carina e ágata: o uso da inteligência artificial pelo tribunal de contas da união. Controle Externo: Revista do Tribunal de Contas do Estado de Goiás, Belo Horizonte, ano 2, 11–34 (2020)
Cruz, T.D.S., et al.: Automatizando a fiscalização de gastos públicos por meio da classificação automática de empenhos utilizando aprendizado de máquina (2021)
DataSnipper: types of governmental audits: a comprehensive overview. https://www.datasnipper.com/resources/types-governmental-audits#:~:text=Governmental%20audits%20are%20systematic%20examinations,and%20effectiveness%20of%20internal%20controls
Europe Union, E.U.: Supreme sudit institutions in the EU and its member states – an overview. https://doi.org/10.2865/686084
Guimarães, T.R., et al.: Análise dos fatores que contribuem para a recuperação dos créditos de icms inscritos em divida ativa no estado do rio de janeiro (2023)
Hamelers, L.: Detecting and explaining potential financial fraud cases in invoice data with machine learning (2021). http://essay.utwente.nl/85533/
Hildebrand, R.O.C.: A experiência do tribunal de contas da união com inteligência artificial (2021)
Lins, G.D., Marcelo, D.A.T., et al.: Parametrização de despesas municipais e detecção de anomalias (2021)
Ludermir, T.B.: Inteligência artificial e aprendizado de máquina: estado atual e tendências 35(101), 85–94 (2021). https://doi.org/10.1590/s0103-4014.2021.35101.007
Mabelane, K., Mongwe, W.T., Mbuvha, R., Marwala, T.: An analysis of local government financial statement audit outcomes in a developing economy using machine learning. Sustainability 15(1) (2023). https://doi.org/10.3390/su15010012, https://www.mdpi.com/2071-1050/15/1/12
MIT: Libguides: database search tips: Boolean operators. https://libguides.mit.edu/c.php?g=175963&p=1158594
Mitchell, T.M.: Machine Learning. McGraw-Hill Education, 1 edn. (1997)
de Oliveira Andrade, A., et al.: Prediction and visualisation of siconv project profiles using machine learning. Systems 10(6) (2022). https://doi.org/10.3390/systems10060252, https://www.mdpi.com/2079-8954/10/6/252
Page, M.J., et al.: Prisma 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. bmj 372 (2021)
Sohrabi, C., et al.: Prisma 2020 statement: what’s new and the importance of reporting guidelines (2021)
Souza, J.J.d.: A necessidade de regulação do uso da inteligência artificial nas ações de controle do tribunal de contas da união (2021)
TCU: artificial intelligence boosts productivity in the federal court of accounts (2018). https://portal.tcu.gov.br/en_us/imprensa/news/artificial-intelligence-boosts-productivity-in-the-federal-court-of-accounts.htm
TCU: Zello (2020). https://portal.tcu.gov.br/data/pages/8A81881F77D527280177D58177E75C93.htm
TCU: Em seminário internacional, presidente do TCU defende o uso de ciência e tecnologia no combate à corrupção | Portal TCU — portal.tcu.gov.br (2023). https://portal.tcu.gov.br/imprensa/noticias/em-seminario-internacional-presidente-do-tcu-defende-o-uso-de-ciencia-e-tecnologia-no-combate-a-corrupcao.htm
THEIIA: the role of auditing in public sector governance. https://www.ca-ilg.org/sites/main/files/file-attachments/auditing_in_public_sector.pdf?1441835528 (2006)
Watson, J.: How artificial intelligence will impact the accounting industry? (2023). https://www.acecloudhosting.com/blog/artificial-intelligence-impact-accounting/
Acknowledgement
This research was supported by the Federal Institute of Maranhão (IFMA), the Foundation for the Support of Research and Scientific and Technological Development of Maranhão (FAPEMA), and the Polytechnic of Porto (ISEP). Their support is gratefully acknowledged.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Coelho, H.G., Marreiros, G., Maia, L.F. (2025). Machine Learning Applied in Government Audit with Focus on Financial Statement: A Systematic Literature Review. In: González-Briones, A., et al. Highlights in Practical Applications of Agents, Multi-Agent Systems, and Digital Twins: The PAAMS Collection. PAAMS 2024. Communications in Computer and Information Science, vol 2149. Springer, Cham. https://doi.org/10.1007/978-3-031-73058-0_18
Download citation
DOI: https://doi.org/10.1007/978-3-031-73058-0_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-73057-3
Online ISBN: 978-3-031-73058-0
eBook Packages: Artificial Intelligence (R0)