An Intelligent Analytics Architecture for Decision Support in Compliance-Critical Systems

Abstract

Compliance-critical systems operate under strict regulatory, legal, and ethical constraints while supporting high-impact operational decisions. As organizations increasingly rely on advanced analytics and intelligent systems, the challenge lies in delivering timely, accurate, and explainable decision support without violating compliance obligations. This review examines the evolution of intelligent analytics architectures designed for decision support in environments where accountability, traceability, and governance are non-negotiable. The article synthesizes prior research across data management, analytics, artificial intelligence, and governance frameworks to identify architectural patterns, analytical capabilities, and control mechanisms that enable compliant decision-making. By integrating insights from diverse domains, the review highlights architectural principles that balance analytical intelligence with regulatory assurance and operational trust.