Exploration of Audit Technologies in Public Security Agencies: Empirical Research from Portugal

Diogo Leocádio, Luís Malheiro and João Reis ()
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Diogo Leocádio: Department of Military Sciences, Portuguese Military Academy and CINAMIL, Avenida Conde Castro Guimarães, 2720-113 Lisbon, Portugal
Luís Malheiro: Department of Military Sciences, Portuguese Military Academy and CINAMIL, Avenida Conde Castro Guimarães, 2720-113 Lisbon, Portugal
João Reis: Industrial Engineering and Management, Faculty of Engineering, Lusófona University, Campo Grande, 1749-024 Lisbon, Portugal

JRFM, 2025, vol. 18, issue 2, 1-18

Abstract: The integration of artificial intelligence (AI) in the public sector is driving significant advancements in governance and management, changing the way public organizations operate. In particular, AI technologies have a profound impact on auditing practices, enhancing efficiency and accountability. This article aims to explore how AI can improve audit processes in a Portuguese public security agency, focusing on its transformative potential in streamlining tasks such as data extraction, analysis, and verification. Using a qualitative research approach, the study employs custom Python algorithms to examine the integration of key indicators into the audit process, specifically through the analysis of economic classification and expenditure limits. The findings demonstrate that personalized algorithms can reduce manual workloads, improve accuracy, and strengthen compliance with financial regulations, providing valuable contributions for decision-making. However, challenges such as data privacy and infrastructure investment remain, emphasizing the need for further research. Future studies should focus on adapting AI-based auditing models to various public administration contexts, addressing organizational changes, and advancing public governance.

Keywords: artificial intelligence; auditing; Portugal; public sector; python (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2025
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