Future Potential of Intelligent Systems in Fiscal Oversight: A Systematic Review

Abstract

The way challenges are addressed across multiple areas of knowledge is currently being revolutionized by intelligent systems. These systems offer novel opportunities and viewpoints that deserve examination, particularly in the context of fiscal surveillance and control. However, although recent studies underscore a paradigm shift toward technology-driven audit research, the evidence on intelligent systems in fiscal oversight remains fragmented and has not been systematically organized. This article provides a systematic literature review that examines the potential of intelligent systems for efficiently managing public resources. To conduct the review, a search of documents from 2018 was conducted in databases such as Scopus, ScienceDirect, IEEE Xplore, DOAJ, and Google Scholar, following the PRISMA statement and the Kitchenham and Charters method. The objective was to select 48 documents for analysis, adhering to the inclusion and exclusion criteria, and to address the four research questions posed. Guided by these questions, the review (i) assesses the potential benefits of intelligent systems for fiscal surveillance and control, covering fraud detection, auditing, risk management, financial analysis, and automation; (ii) contrasts those advantages (greater transparency, efficiency, and efficacy) with the associated technical, organizational, legal, and social challenges; (iii) evaluates the current treatment of four core oversight areas; and (iv) identifies the prevailing technological trends, most notably blockchain, data mining, and artificial intelligence. Despite the limitations of the review, including its temporal scope, individual interpretations, and specific focus, these findings can provide valuable information for government agencies, enabling them to prioritize investments and enhance the management of public resources, thereby contributing to fairer and more equitable societies.