A qualidade da auditoria interna em instituições federais de ensino brasileiras: uma análise segundo a percepção dos integrantes das auditorias internas e da alta gestão - Borges, Gislaine (2021)
The objective of this study was to analyze the factors that influence the quality of internal audits (IAs) of Brazilian Federal Higher Education Institutions (HEIs), and to propose suggestions for improvement. This research was characterized by being an applied quantitative survey with exploratory objectives. Regarding data collection, it was decided to use an online questionnaire applied to the members of the IAs and the senior management of the HEIs. A sample of 301 valid responses was obtained, of which 158 were from members of AIs and 143 from councilors of collegiate bodies of the aforementioned Institutions. The analyzes carried out included descriptive statistics of the sample, exploratory factor analysis, t and ANOVA tests to verify differences in means, Pearson's correlation and multiple regression analysis. In summary, the results showed that the IA Quality, IA Work, Continuous Improvement, IA Management Support, IA Independence and Effectiveness dimensions, in general, had a positive perception by the respondents. On the other hand, the construct Relationship between Internal and External Auditors presented the greatest disagreements regarding the items “the control bodies (CGU and TCU) discuss their plans with IA” (average 2.68) and “the auditors of the control and AIs share work roles” (mean 2.91). Regarding the IA Functioning dimension, two questions showed relative neutrality on the part of the respondents, namely: does the IA have sufficient budget to carry out its attributions and responsibilities (general average 3.37) and does the IA have a Management Program and Quality Improvement (average of the AI group 3.49). On the AI quality factors, obtained through factor analysis, they were the following: AI Operation (FAI), Relationship between Internal and External Auditors (REL), Continuous Improvement Practices (PMC), AI Autonomy (AAI) and Organizational Support (APO). In the topic related to the difference in means, there were statistically significant means between the groups “Members of AIs” and “Senior Management” with the factors FAI, REL and PMC; and between the group of individuals with “Doctorate” and the REL and APO factors. Regarding the correlation between the factors created, there was a high association between IA Quality and FAI (0.781) and a low association between REL and AAI (0.297). Regarding the multiple regression, it was found that FAI, PMC and REL had a positive impact on the Quality of IAs. APO and AAI were not statistically significant. In summary, it was found that there are relevant factors for the quality of IAs. Therefore, they deserve attention from the analyzed HEIs, as they represent important drivers that positively impact the structuring and maintenance of a quality IA.