Quantum-Enhanced Cloud AI Framework for Privacy-Aware Financial Quality Assurance in SAP with Kubernetes Operators
DOI:
https://doi.org/10.15680/IJCTECE.2025.0805015Keywords:
Quantum Computing, Cloud AI, SAP Integration, Financial Data Privacy, Kubernetes Operators, Quality Assurance, Intelligent AutomationAbstract
The rapid evolution of financial ecosystems demands intelligent, secure, and high-performance frameworks capable of handling complex enterprise operations. This paper presents a Quantum-Enhanced Cloud AI Framework that integrates SAP environments with Kubernetes Operators to achieve scalable automation, enhanced data privacy, and intelligent quality assurance. The proposed architecture leverages quantum-inspired algorithms for accelerated data processing and predictive analytics, improving the accuracy and efficiency of financial anomaly detection and compliance validation. Within this framework, AI-driven test case automation and ETL pipelines are deployed across containerized Kubernetes clusters, enabling dynamic scaling, fault tolerance, and continuous integration of quality metrics. A key focus of this research is on privacy-aware data governance, ensuring that sensitive financial data processed within the SAP landscape adheres to regulatory standards such as GDPR. By combining quantum computing principles, cloud-native orchestration, and machine learning-driven insights, the system enhances transparency, reduces testing overhead, and supports proactive financial risk mitigation. Experimental results demonstrate measurable improvements in test execution speed, data privacy assurance, and resource utilization, highlighting the framework’s potential for next-generation financial automation in enterprise cloud infrastructures.
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