Secure AI-Based Predictive Risk Analytics for SAP-Enabled Financial and Healthcare Business Processes over 5G Cloud Networks

Abstract

The convergence of SAP-based enterprise systems, cloud computing, artificial intelligence, and 5G connectivity is transforming financial and healthcare business processes, while simultaneously introducing complex security and risk management challenges. This paper proposes a secure AI-based predictive risk analytics framework for SAP-enabled financial and healthcare environments operating over 5G cloud networks. The framework integrates machine learning models with SAP transactional data, network telemetry, and security logs to identify financial anomalies, operational risks, and potential cyber threats in real time. Advanced predictive analytics techniques are employed to assess risk propagation across interconnected business processes, ensuring early detection and mitigation. Security controls such as access governance, encrypted data pipelines, and policy-aware analytics are incorporated to protect sensitive financial and healthcare data. The proposed approach supports scalable deployment in cloud-native SAP architectures while leveraging 5G’s low-latency capabilities for timely risk intelligence. Experimental analysis demonstrates improved prediction accuracy, faster risk response, and enhanced system resilience compared to traditional rule-based monitoring systems. The results highlight the effectiveness of AI-driven risk analytics in strengthening trust, compliance, and operational continuity in next-generation SAP-driven enterprises.