A Bibliometric Analysis of Competence, Independence, and Big Data Analytics in Enhancing Investigative Audit Effectiveness

The This research emerged in response to the increasing need for more effective investigative auditing amid growing demands for accountability, transparency, and data-driven decision-making. The primary objective of this systematic literature review is to identify, characterize, and analyze global research trends related to auditor competence, professional independence, and the application of big data analytics in investigative audit practices. Using systematic review techniques as the core methodology, researchers collected and analyzed 795 documents from the Scopus database, covering the publication period from 2020 to 2025. The findings reveal a consistent increase in research interest, with significant contributions from various countries, particularly the United States, the United Kingdom, and Indonesia. The documents reviewed highlight themes such as the role of auditor skills in fraud detection, the influence of independence on audit objectivity, and the transformative potential of big data technologies. Factors such as international collaboration, institutional support, and the growing complexity of financial ecosystems contribute to the acceleration of scholarly output in this field. This study offers key insights and practical recommendations to strengthen audit quality by integrating behavioral, ethical, and technological dimensions within investigative audit frameworks.