Engineering and Applied Sciences Journal

Leveraging Generative AI for Real-Time Anomaly Detection in SAP FICO: A Paradigm Shift in Financial Governance

Abstract

Srinivas Raju Gottimukkala

In the era of digital transformation, the integration of artificial intelligence within enterprise resource planning (ERP) systems is redefining financial management. This research explores the unprecedented application of generative AI models such as transformer-based architectures for real-time anomaly detection within SAP FICO modules. Unlike traditional rule based or statistical approaches, generative AI can learn complex, dynamic financial patterns, enabling the proactive identification of irregularities in general ledger entries, accounts receivable, and accounts payable. This study proposes a novel framework that embeds generative AI directly into SAP FICO workflows, facilitating continuous monitoring, adaptive learning, and automated escalation of financial anomalies. The research also addresses data privacy, explain ability, and integration challenges, offering a roadmap for organizations seeking to enhance their financial governance and compliance posture. Through simulation and case-based analysis, the paper demonstrates how this approach can reduce financial fraud, improve audit readiness, and drive operational efficiency heralding a new era of intelligent financial oversight in SAP environments

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