International Journal of Science, Engineering and TechnologyAuthors: Manjunath gowda .C
Abstract: The rapid digitization of corporate finance has rendered traditional, rule-based fraud detection systems increasingly inadequate against the sophisticated, high-velocity deceptive practices. This review article evaluates the integration of AI-based predictive models within enterprise SAP environments, specifically focusing on the transition from retrospective auditing to proactive, real-time prevention. By leveraging the unified data architecture of the SAP S/4HANA Universal Journal (ACDOCA), organizations can deploy a multi-layered analytical framework comprising supervised learning for known pattern recognition, unsupervised anomaly detection for identifying "zero-day" fraud, and graph-based analysis for uncovering complex collusion networks. The analysis details the technical implementation pathways, contrasting embedded intelligence within the SAP HANA database with side-by-side innovation on the SAP Business Technology Platform (BTP). Furthermore, the article investigates the transformative impact of Generative AI and agentic finance in automating investigative workflows and enhancing Explainable AI (XAI) for regulatory compliance. Strategic challenges, including the mitigation of model drift and the ethical implications of algorithmic bias, are critically examined to ensure a "human-in-the-loop" governance model. The findings provide a comprehensive roadmap for financial architects and security officers, highlighting how federated learning and quantum-resistant architectures will define the future of enterprise security. Ultimately, the synthesis of these technologies enables the emergence of the autonomous enterprise a self-healing financial ecosystem capable of maintaining absolute integrity in an increasingly volatile digital landscape.
DOI: https://doi.org/10.5281/zenodo.18228854
