Intelligent Cloud AI Framework for Automated Test Case Execution and Secure Financial Data Management in SAP Environments

Abstract

The increasing complexity of financial systems in the digital era demands robust, intelligent frameworks that ensure accuracy, security, and efficiency. This study presents a comprehensive cloud-based AI framework integrating test case automation, quality assurance, and financial data privacy management within SAP environments. Leveraging ETL (Extract, Transform, Load) processes, the framework efficiently handles large-scale financial datasets while ensuring data consistency, integrity, and compliance with privacy regulations. To enhance anomaly detection and predictive insights, the system incorporates Support Vector Machine (SVM) algorithms, enabling real-time identification of potential errors, fraud, or inconsistencies in financial transactions. Intelligent system components orchestrate automated test case execution, monitoring, and reporting, significantly reducing manual effort and operational overhead while improving overall system reliability. The proposed framework also emphasizes secure cloud integration, ensuring that sensitive financial data remains protected during both processing and storage. Experimental results demonstrate that this AI-driven approach not only optimizes testing and quality assurance workflows but also enhances decision-making capabilities, strengthens data privacy adherence, and provides a scalable, efficient solution for modern financial enterprises. This framework represents a forward-looking model for intelligent, secure, and automated financial operations in enterprise environments.