Authors: Reyvik Sood
Abstract: The transition to SAP S/4HANA and the expansion of digital business models have created a high-velocity data environment that traditional Governance, Risk, and Compliance (GRC) frameworks are no longer equipped to manage. This review article investigates the conceptualization and implementation of an "Intelligent Risk Intelligence Engine" (IRIE) designed to transform enterprise risk management from a reactive, manual exercise into a proactive, predictive digital immune system. By leveraging advanced analytics specifically machine learning for anomaly detection, predictive modeling for financial forecasting, and natural language processing for qualitative risk sensing this engine enables the continuous monitoring of the entire SAP transactional population. We evaluate the multi-layered architectural requirements for such a system, utilizing the SAP Business Technology Platform (BTP) as an intelligence core to ingest and process heterogeneous data streams. A significant portion of the study is dedicated to the "Explainable AI" (XAI) mandate, demonstrating how methodologies like SHAP and LIME provide the transparency necessary to satisfy internal and external audit requirements. The article further explores the automation of internal controls through dynamic key risk indicators and the emergence of "Risk Digital Twins" for stress-testing enterprise resilience. By synthesizing industry-specific case studies and evaluating future directions such as agentic risk frameworks and quantum-accelerated simulations, this research provides a strategic roadmap for organizations to embed autonomous governance into their digital core. Ultimately, we demonstrate that an intelligence-led approach to risk is a fundamental prerequisite for the operational excellence and institutional trust required in the modern intelligent enterprise.
DOI: https://doi.org/10.5281/zenodo.18230094
