Secure and Cyber-Resilient Real-Time AI-Cloud Ecosystem for SAP-Integrated Intelligent Loan Management and Banking Operations
DOI:
https://doi.org/10.15662/IJARCST.2024.0706009Keywords:
AI enabled data governance, SAP S/4HANA Finance, Oracle Cloud Infrastructure, financial workloads, metadata management, data lineage, anomaly detection, cloud data governance, finance data quality, regulatory complianceAbstract
The accelerating adoption of cloud infrastructure and artificial intelligence (AI) within financial services is transforming how organizations manage, analyze, and govern critical financial data. This paper investigates how an AI‑enabled data governance framework can be applied to financial workloads running on SAP S/4HANA Finance (and associated SAP financial modules) deployed on Oracle Cloud Infrastructure (OCI). We propose a reference architecture that integrates SAP financial workload data pipelines with an AI‑augmented governance layer running on OCI, which enforces metadata management, data quality, lineage, role‑based access, anomaly detection, and compliance monitoring. A literature review surveys the interplay of AI in data governance, SAP finance system governance, and cloud‑based data platforms. Our research methodology uses a mixed‑method approach: qualitative interviews with finance and IT governance leaders, and a quantitative proof‑of‑concept simulation of governance monitoring in an SAP‑OCI environment. We identify key benefits such as improved data trust, faster detection of anomalies, scalable control across cloud workflows, and alignment with regulatory standards; and limitations including complexity of AI governance, integration challenges, performance overhead, and organizational readiness. The results indicate that embedding AI‑enabled governance within SAP financial workloads on OCI can materially enhance data trust, audit readiness, and control scalability—provided that organizational, technical and process dimensions are addressed. The discussion explores trade‑offs, architectural implications and deployment roadmap. In conclusion, this study offers finance and IT leadership a blueprint for deploying AI‑driven data governance for SAP financial workloads in the cloud, and outlines future work in automation, model explainability, and cross‑cloud governance.
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