Continuous Auditing in Decentralized Public Institutions: Analytical Perspectives on Big Data, Accountability, and Governance

The accelerating digitalization of public governance has transformed how accountability is conceptualized and practiced. This narrative literature review discusses the subject of continuous auditing within decentralized institutions of the government with its analytical intersections of big data, accountability, and governance ethics. Based on peer-reviewed literature and the current trends in data-driven oversight, the review builds on the findings of numerous authors in the disciplines of public administration, information systems, and accounting to explain how continuous auditing redefines accountability as a real-time operation as opposed to an infrequent review. The results show that technological infrastructures, especially AI, predictive analytics, and blockchain systems, are used to monitor and automatically assure distributed governance networks in real-time. However, such innovations lead to new tensions: decentralized ownership of accountability, the opaqueness of the algorithms, and the ethical challenge of balancing the need to become transparent and the need to have privacy. Among the research gaps found in the review, there is no longitudinal evidence, insufficient theorization of algorithmic accountability, and a weak comparative outlook of the national contexts. Ideally, the paper proceeds to promote continuous auditing as a technological and institutional innovation, which mediates both efficiency and legitimacy. It suggests a governance-accountability feedback model, in which information, auditing, and policy are co-innovated via learning. The review concludes by proposing multi-stakeholder, data-integrated, and ethically-based research on governance in order to make sure that the continuous auditing enhances, but does not replace, democratic accountability in the digital era.