SAP-Integrated Large Language Models for Secure Cloud-Based Enterprise Analytics and Risk Detection
DOI:
https://doi.org/10.15662/IJEETR.2023.0506014Keywords:
SAP Integration, Large Language Models, Cloud Computing, Enterprise Analytics, Cybersecurity, Risk Detection, Artificial IntelligenceAbstract
The increasing reliance on cloud-based enterprise systems has intensified the need for intelligent analytics and proactive risk detection mechanisms that ensure security, compliance, and operational resilience. This paper proposes a SAP-integrated framework that leverages Large Language Models (LLMs) to enable secure cloud-based enterprise analytics and intelligent risk detection. By integrating SAP Business Technology Platform (BTP), AI and machine learning services, and cloud-native data pipelines, the proposed system analyzes structured and unstructured enterprise data in real time. LLMs are utilized to interpret logs, transactions, and user behavior patterns, enabling contextual threat detection, risk forecasting, and automated decision support. The framework enhances cybersecurity by identifying anomalies, policy violations, and potential insider threats while maintaining data privacy through role-based access control and encrypted data flows. In addition, the solution supports advanced business and marketing analytics by generating actionable insights from large-scale enterprise datasets. Experimental evaluation demonstrates improved analytical accuracy, faster risk identification, and enhanced security posture compared to traditional rule-based and non-AI approaches. The proposed SAP-integrated LLM architecture provides a scalable and future-ready solution for secure enterprise analytics in cloud environments.
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