AI-Driven Compliance Intelligence: A Conceptual Framework for Enterprise Financial Governance
Keywords:
AI-driven compliance, enterprise financial governance, anomaly detection, regulatory automation, audit intelligence, machine learning, ERP integration, explainable AI, knowledge graphs, RAG-based enterprise systems, risk management, compliance maturity modelAbstract
Enterprise financial governance is increasingly challenged by the complexity of globalregulatory environments, legacy system debt, and the exponential growth of transactional data.Traditional compliance frameworks, which rely primarily on periodic audits and static rule-based controls, are ill-equipped to meet the demands of real-time financial integrity across multi-entity
References
M. Protiviti and D. Beasley, "Internal audit and financial controls in a digital age," Protiviti Risk & Business Consulting, Technical Report, 2023.
KPMG International, "The future of compliance: From periodic reviews to continuous assurance," KPMG Insights Series, 2022.
Downloads
Published
2026-05-19
How to Cite
Ajay Mirani. (2026). AI-Driven Compliance Intelligence: A Conceptual Framework for Enterprise Financial Governance . Journal of Computational Analysis and Applications (JoCAAA), 35(5), 116–131. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5467
Issue
Section
Articles
