Real-Time Regulatory Intelligence Framework: LLM-powered compliance automation for financial services

Pulikonda, Naga Krishna Mahesh (2025) Real-Time Regulatory Intelligence Framework: LLM-powered compliance automation for financial services. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 3106-3115. ISSN 2582-8266

This article presents a novel real-time regulatory intelligence framework leveraging Large Language Models (LLMs) to transform compliance automation in financial services. The article addresses the growing complexity of regulatory requirements that financial institutions face globally by developing an integrated system that continuously monitors regulatory sources, interprets complex requirements, and implements compliant controls. The framework consists of a layered architecture with specialized components for data ingestion, regulatory interpretation, policy orchestration, and governance with human oversight. Extensive evaluations demonstrate the framework's ability to significantly improve interpretation accuracy, reduce time-to-compliance, and enhance risk management compared to traditional approaches. Case studies across multiple regulatory domains confirm the system's versatility and effectiveness, while implementation data from financial institutions validates substantial cost reductions and operational improvements. The article identifies promising directions for further enhancement and examines broader implications for the regulatory technology landscape, suggesting a paradigm shift in how compliance is managed and how regulators and regulated entities interact in an increasingly digital financial ecosystem.