Design and Development of an AI-Optimized Cloud Banking Ecosystem: Oracle-SAP Integration with Quantum Computing and Risk Intelligence
DOI:
https://doi.org/10.15662/IJRAI.2024.0706009Keywords:
AI-Optimized Cloud, Banking Ecosystem, Oracle-SAP Integration, Quantum Computing, Risk Intelligence, Predictive Analytics, Cloud-Native Architecture, Financial Technology, Secure Data Processing, Real-Time Decision SupportAbstract
The rapid evolution of digital banking demands intelligent, scalable, and secure ecosystem architectures capable of handling large-scale data and complex financial operations. This study presents the design and development of an AI-optimized cloud banking ecosystem integrating Oracle and SAP platforms, enhanced with quantum computing capabilities for accelerated data processing and decision-making. The proposed framework leverages AI-driven analytics to optimize operational efficiency, automate transaction processing, and provide predictive risk intelligence for real-time financial decision support. By integrating quantum algorithms with cloud-native architectures, the system ensures enhanced computational performance, robust security, and adaptive scalability. Experimental evaluations demonstrate significant improvements in risk assessment accuracy, transaction throughput, and predictive insights, highlighting the potential of quantum-AI-enabled banking ecosystems for next-generation financial services.
References
1. Pfadler, A., Zhu, R., Chen, W., Huang, B., Zeng, T., Ding, B., & Zhou, J. (2021). Baihe: SysML Framework for AI driven Databases. arXiv. https://arxiv.org/abs/2112.14460
2. Sangannagari, S. R. (2023). Smart Roofing Decisions: An AI-Based Recommender System Integrated into RoofNav. International Journal of Humanities and Information Technology, 5(02), 8-16.
3. Nayak, N., Schönberger, M., Uotila, V., Yan, Z., Groppe, S., Lu, J., & Mauerer, W. (2024). “QCE’24 Tutorial: Quantum Annealing – Emerging Exploration for Database Optimization.” arXiv. https://arxiv.org/abs/2411.04638
4. Sugumar, R. (2023, September). A Novel Approach to Diabetes Risk Assessment Using Advanced Deep Neural Networks and LSTM Networks. In 2023 International Conference on Network, Multimedia and Information Technology (NMITCON) (pp. 1-7). IEEE.
5. “Oracle Introduces Integrated Vector Database to Augment Generative AI and Dramatically Increase Developer Productivity.” (2023, September 19). Oracle. https://www.oracle.com/in/news/announcement/ocw integrated-vector-database augments-generative-ai 2023 09 19/
6. Cherukuri, B. R. (2024). Serverless computing: How to build and deploy applications without managing infrastructure. World Journal of Advanced Engineering Technology and Sciences, 11(2).
7. “Oracle Announces Exadata Exascale, World’s Only Intelligent Data Architecture for the Cloud.” (2024, July 11). Oracle ASEAN. https://www.oracle.com/asean/news/announcement/oracle-announces-exadata-exascale-worlds-only-intelligent-data-architecture-for-the-cloud-2024-07-11/
8. AZMI, S. K. (2021). Markov Decision Processes with Formal Verification: Mathematical Guarantees for Safe Reinforcement Learning
9. Gosangi, S. R. (2022). SECURITY BY DESIGN: BUILDING A COMPLIANCE-READY ORACLE EBS IDENTITY ECOSYSTEM WITH FEDERATED ACCESS AND ROLE-BASED CONTROLS. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(3), 6802-6807.
10. Jabed, M. M. I., Khawer, A. S., Ferdous, S., Niton, D. H., Gupta, A. B., & Hossain, M. S. (2023). Integrating Business Intelligence with AI-Driven Machine Learning for Next-Generation Intrusion Detection Systems. International Journal of Research and Applied Innovations, 6(6), 9834-9849.
11. “Enhancing AI Application Development with Oracle Database 23ai’s AI Vector Search and Exadata X10M.” (2024). The Futurum Group / Oracle PDF Whitepaper.
12. Kumbum, P. K., Adari, V. K., Chunduru, V. K., Gonepally, S., & Amuda, K. K. (2023). Navigating digital privacy and security effects on student financial behavior, academic performance, and well-being. Data Analytics and Artificial Intelligence, 3(2), 235–246.
13. Narapareddy, V. S. R., & Yerramilli, S. K. (2022). RISK-ORIENTED INCIDENT MANAGEMENT IN SERVICE NOW EVENT MANAGEMENT. International Journal of Engineering Technology Research & Management (IJETRM), 6(07), 134-149.
14. Gonepally, S., Amuda, K. K., Kumbum, P. K., Adari, V. K., & Chunduru, V. K. (2022). Teaching software engineering by means of computer game development: Challenges and opportunities using the PROMETHEE method. SOJ Materials Science & Engineering, 9(1), 1–9.
15. “Availability of Oracle Exadata Exascale Intelligent Data Architecture for Cloud.” (2024, July 16). StorageNewsletter. https://www.storagenewsletter.com/2024/07/16/availability-of oracle exadata exascale intelligent data architecture-for-cloud/
16. Venkata Ramana Reddy Bussu,, Sankar, Thambireddy, & Balamuralikrishnan Anbalagan. (2023). EVALUATING THE FINANCIAL VALUE OF RISE WITH SAP: TCO OPTIMIZATION AND ROI REALIZATION IN CLOUD ERP MIGRATION. International Journal of Engineering Technology Research & Management (IJETRM), 07(12), 446–457. https://doi.org/10.5281/zenodo.15725423
17. Raj, A. A., & Sugumar, R. (2023, June). Early Detection of COVID-19 with Impact on Cardiovascular Complications using CNN Utilising Pre-Processed Chest X-Ray Images. In 2023 International Conference on Applied Intelligence and Sustainable Computing (ICAISC) (pp. 1-6). IEEE.
18. ElephantSqlDB, Inc. (n.d.). “Explore ElephantSqlDB: Quantum Computing Applications for Advanced Database Solutions.” https://www.elephantsqldb.com/elephantsqldb technology
19. Manda, P. (2023). LEVERAGING AI TO IMPROVE PERFORMANCE TUNING IN POST-MIGRATION ORACLE CLOUD ENVIRONMENTS. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(3), 8714-8725.
20. Reddit user post. (2023, March 16). “How true is it that OCI is more efficient than GCP/AWS in AI workloads.” r/oracle. https://www.reddit.com/r/oracle/comments/11sm6qrh
