Cloud-Based AI/ML Framework for Fraud Detection and Cybersecurity in SAP HANA Banking
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Abstract
The increasing adoption of cloud-based banking platforms has intensified the need for robust fraud detection and cybersecurity mechanisms capable of handling high-volume, real-time financial data. This paper presents a cloud-based AI/ML framework for fraud detection and cybersecurity in SAP HANA banking environments. The proposed framework leverages SAP HANA’s in-memory computing capabilities integrated with scalable cloud services to enable real-time data ingestion, feature extraction, and intelligent threat analysis. Advanced machine learning and deep learning models are employed to detect fraudulent transactions, anomalous user behavior, and cyber intrusions with improved accuracy and reduced latency. The architecture incorporates automated risk scoring, adaptive learning, and secure data governance to ensure regulatory compliance and data privacy. Experimental insights indicate that AI-driven analytics within SAP HANA cloud ecosystems can significantly enhance detection performance while strengthening cyber resilience in modern banking systems. The framework demonstrates a scalable and secure approach for protecting cloud-based financial infrastructures against evolving cyber threats.
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