Seleção de unidades para auditoria interna na Marinha do Brasil: uma abordagem integrada baseada em risco e dados

Abstract

The proper selection of units for audit is a determining factor for the effectiveness of internal audits, especially in the context of the Brazilian Navy (MB), where academic studies highlight weaknesses in this process, underscoring the need for improvement. In light of this, the present study aimed to investigate how a Risk-Based Audit (RBA) and Audit Data Analytics (ADA) can contribute to enhancing the process of selecting units to be audited within the MB. To structure the research, a methodology was adopted that combines ABR and ADA in the construction of selection models aimed at government internal auditing. Documentary analysis of the MB's audit regulations revealed that the currently employed model prioritizes the criteria of materiality, timeliness, and compliance risk, without considering risk factors related to the organizational performance of the units. Furthermore, the risk matrix used presents limitations, particularly due to the subjectivity involved in assigning scores by specialists. To mitigate these weaknesses, the study was initially limited to the provisioning area, where ten risk factors reflecting the units' performance concerning the MB's administrative controls were developed. Based on these risk factors and the criteria already adopted by the MB to classify the units linked to the provisioning area, a decision matrix encompassing 176 units was constructed using data extracted from government systems managed by the Navy. The multi-criteria methods CRITIC (Criteria Importance Through Intercriteria Correlation) and Weighted Sum were applied to the decision matrix, selected for their ability to reduce subjectivity in the evaluation of risk factors. These methods enabled the ranking of units according to their degree of criticality, facilitating the prioritization of the most vulnerable ones for audit. The comparison between the results of the proposed model and the traditional MB model revealed that the units selected by the new approach showed superior performance by more comprehensively and accurately incorporating organizational specificities. As an academic contribution, this study explores the development of a unit selection process for auditing, a topic still scarcely addressed in the literature. From a practical perspective, the research presents recommendations to the Naval Force, such as optimizing logistics, improving personnel management, and expanding continuous audits. It is expected that the results will support the update of unit prioritization models, consolidating a sustainable, efficient process aligned with the reality of the Brazilian Navy.