Automation And Public Oversight In Brazil: Evaluating The Monitoring Of Fiscal Management Reports

This study aims to the relationship between the implementation of automation solutions in the analysis of FMRs and the efficiency of oversight activities carried out by the TCU. Despite regulatory and theoretical advances in public sector automation, empirical gaps remain regarding the quantitative effects of technologies like Robotic Process Automation (RPA) on audit efficiency. To address this, a quantitative methodology was applied, using multiple linear regression models and correlation analysis. Data were collected from 42 FMR monitoring processes conducted by the TCU between 2010 and 2024, drawn from the institution’s digital platform. The sample includes processes with and without RPA usage, allowing comparative analysis. The results demonstrate that RPA implementation has a statistically significant negative effect on process duration and a positive impact on the length of reports. Specifically, RPA contributed to an average reduction of 72 days in process duration and an increase of 14 pages per report, highlighting gains in both efficiency and content depth. The study confirms theoretical expectations from the Unified Theory of Acceptance and Use of Technology (UTAUT), particularly regarding performance expectancy. This research contributes to the public administration literature by empirically validating the role of automation in improving audit efficiency, offering practical insights for TCU’s decision-makers and other oversight institutions. The findings suggest that automation can streamline processes, reallocate human resources to more complex tasks, and enhance transparency. The results also support further investment in digital tools, paving the way for integrating advanced technologies such as artificial intelligence in fiscal oversight.