Enterprise Scale AI Driven Cloud Systems for Cybersecurity Focused Healthcare and Financial Risk Analytics
Abstract
The rapid digitization of healthcare and financial systems has increased exposure to cyber threats and systemic risks, necessitating robust, scalable, and intelligent solutions. This paper explores the design and implementation of enterprise-scale artificial intelligence (AI)-driven cloud systems tailored for cybersecurity-focused healthcare and financial risk analytics. By leveraging cloud-native architectures, machine learning models, and real-time data processing frameworks, these systems enable proactive threat detection, anomaly identification, and predictive risk mitigation. In healthcare, such systems enhance patient data protection, ensure regulatory compliance, and detect breaches in electronic health record (EHR) systems. In financial services, they facilitate fraud detection, credit risk assessment, and market anomaly prediction. The integration of AI with cloud infrastructure supports scalability, cost-efficiency, and continuous learning through adaptive algorithms. However, challenges such as data privacy, model bias, and system interoperability persist. This study proposes a hybrid framework combining deep learning, zero-trust security models, and distributed cloud computing to address these issues. The findings highlight the transformative potential of AI-driven cloud ecosystems in strengthening cybersecurity resilience and improving risk analytics across critical sectors.
Article Information
Journal |
International Journal of Science, Research and Technology |
|---|---|
Volume (Issue) |
Vol. 9 No. 2 (2026): International Journal of Science, Research and Technology (IJSRAT) |
DOI |
|
Pages |
418-426 |
Published |
March 7, 2026 |
| Copyright |
All rights reserved |
Open Access |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
How to Cite |
Bhavesh Dilip Patel (%2026). Enterprise Scale AI Driven Cloud Systems for Cybersecurity Focused Healthcare and Financial Risk Analytics. International Journal of Science, Research and Technology , Vol. 9 No. 2 (2026): International Journal of Science, Research and Technology (IJSRAT) , pp. 418-426. https://doi.org/10.15662/IJSRAT.2026.0902013 |
References
1. Khan, W. A., Ayub, M., Quddoos, M. U., WASEEM, L., RAHIM, M., HAMEED, M., ... & KHAN, M. (2024). Knowledge refinement mechanism in agency using adaptive automata and genetic algorithms. Journal of Infrastructure, Policy and Development, 8(16), 9482.
2. Anand, L. (2024). AI-Powered Cloud Cybersecurity Architecture for Risk Prediction and Threat Mitigation in Healthcare and Finance. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(Special Issue 1), 5-12.
3. Gopinathan, V. R. (2025). Intelligent workload scheduling for telecom cloud architecture using reinforcement learning. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(6), 13244-13255.
4. Sugumar, R. (2025). Unified AI Framework for Predictive Data Engineering and Real Time Prescription and Billing Systems. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 8(5), 17261.
5. Nallamothu, T. K. (2023). GENERATIVE AI IN HEALTHCARE: AUTOMATING CLINICAL DOCUMENTATION, DIAGNOSTICS, AND KNOWLEDGE SYNTHESIS. International Journal of Computer Technology and Electronics Communication, 6(1), 6376-6392.
6. Mudunuri, P. R. (2023). Governance-Aware Infrastructure-as-Code for Regulated Research Environments. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(4), 9017-9027.
7. Appani, C., & Guda, D. P. (2023). Self-supervised representation learning for zero-day attack detection in encrypted network traffic. Computer Fraud & Security, 2023(7), 20–31. Retrieved from: https://computerfraudsecurity.com/index.php/journal/article/view/661
8. Cherukuri, B. R., & Arulkumar, V. (2024, February). Optimization of Data Structures and Trade-Offs with Concurrency Control in Multithread Software Structures Using Artificial Intelligence. In 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT) (Vol. 5, pp. 1860-1865). IEEE.
9. Md Manarat Uddin, M., Rahanuma, T., & Sakhawat Hussain, T. (2025). Privacy-Aware Analytics for Managing Patient Data in SMB Healthcare Projects. International Journal of Informatics and Data Science Research, 2(10), 27-57.
10. Sammy, F., Chettier, T., Boyina, V., Shingne, H., Saluja, K., Mali, M., ... & Shobana, A. (2025). Deep Learning-Driven Visual Analytics Framework for Next-Generation Environmental Monitoring. Journal of Applied Science and Technology Trends, 114-122.
11. Karvannan, R. (2024). Human AI partnerships: Unlocking a more efficient, healthier future. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(5), 11243–11255.
12. Gentyala, R. (2024). From features to financial personas: Mapping feature transformation efficacy to customer archetypes in behavioral banking data. International Journal of Computer Science and Engineering Research and Development, 14(1), 127-145.
13. Dave, B. L. (2024). FUTURE-PROOF LIVING LEADING A BETTER LIFE WITH ARTIFICIAL INTELLIGENCE. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(5), 11233-11242.
14. Balamuralidhar Sarabu, V. (2020). Scalable data processing patterns for national retail platforms: An enterprise architecture for high-volume transaction systems. International Journal of Computer Technology and Electronics Communication (IJCTEC), 3(3), 1–14.
15. Raja, G. V. (2020). Metadata gets a makeover: The machine learning approach. International Journal of Computer Technology and Electronics Communication, 3(6), 2900-2903.
16. Jayaraman, S., Rajendran, S., & P, S. P. (2019). Fuzzy c-means clustering and elliptic curve cryptography using privacy preserving in cloud. International Journal of Business Intelligence and Data Mining, 15(3), 273-287.
17. Akila, R. (2024). A deep reinforcement learning approach for optimizing inventory management in the agri-food supply chain. J. Electrical Systems, 20(4s), 2238-2247.
18. Vayyasi, N. K. (2020). Intelligent transaction prediction and fraud detection in crypto markets using Java and generative AI. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 3(1), 2765–2779.
19. Soundappan, S. J. (2022). AI-based fault detection and isolation for reliability in modern power systems. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7106-7110.
20. Mathew, A. (2024). AI TRiSM: Trust, Risk, and Security Management in Cybersecurity. Cybersecurity, 4(3), 84-90.
21. Vimal Raja, G. (2025). Context-Aware Demand Forecasting in Grocery Retail Using Generative AI: A Multivariate Approach Incorporating Weather, Local Events, and Consumer Behaviour. International Journal of Innovative Research in Science Engineering and Technology (Ijirset), 14(1), 743-746.
22. Panda, S. S. (2025). Breaking dependency chains: Evaluating Microsoft’s Maia 100 as an alternative to NVIDIA GPUs in AI workloads. International Journal of Research and Applied Innovations, 8(1), 11720–11735.
23. Akash, T. R., Shokran, M., & Ferdousi, J. (2026). Role of Machine Learning in Securing US Digital Advertising Ecosystems Against Fraud and Market Manipulation. American Journal of Economics and Business Management, 9(2).
24. Gentyala, R. (2024). The Trust Threshold: How Public Perception of AI Harm Moderates the Impact of FinTech Innovation on Systemic Banking Stability. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(3), 169-190.
25. Suddala, V. R. A. K. (2025). Healthcare e-commerce platforms driving secure, scalable, and auditable service delivery. International Journal of Engineering & Extended Technologies Research (IJEETR), 7(1), 9340–9351.
26. Katta, T. B. (2023). Towards unified enterprise integration: Leveraging hybrid integration platforms to bridge on-premises and cloud environments. International Journal of Computer Technology and Electronics Communication (IJCTEC), 6(5), 7354–7365. https://doi.org/10.15680/IJCTECE.2023.0605014
27. Nallamothu, T. K. (2022). TRANSFORMING CLINICAL DOCUMENTATION AND ANALYTICS USING POWER BI AND DAX COPILOT. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7111-7119.
28. Devineni, A. (2025). Cognitive Load Reduction in On-Call Rotations via Predictive Alert Severity Scoring Using Machine Learning in Financial Cloud Operations. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 6(1), 268-273.
29. Joyce, S. (2023). Optimizing SAP workloads on cloud-native platforms: A framework for intelligent resource allocation and performance scaling. International Journal of Science, Research and Technology (IJSRAT), 6(1), 9210–9219. https://doi.org/10.15662/IJSRAT.2023.0601002
30. Subramanyam, S. P. (2023). Cloud infrastructure automation and role-based access governance in Azure Kubernetes services. International Journal of Research Publications in Engineering, Technology and Management, 6(2), 8392–8400.
31. Tiwari, S. K. (2025). Automation Driven Digital Transformation Blueprint: Migrating Legacy QA to AI Augmented Pipelines. Frontiers in Emerging Artificial Intelligence and Machine Learning, 2(12), 01-20.
32. Karnam, V. S. (2025). Enhancing User Experience and Resilience Through System Scalability for Transforming Aviation Kiosk Systems Using Artificial Intelligence. Journal Of Engineering And Computer Sciences, 4(7), 738-745.
33. Potluri, M. K. (2025). Next-Gen Business Intelligence in Financial Services-Transforming Financial Efficiency with AI-Driven BI, Integration of AI/ML with BI tools. IJSAT-International Journal on Science and Technology, 16(4).
34. Panyala, V. R. (2025). Groundbreaking data processing architectures for petabyte-scale cloud storage systems. International Journal of Research Publications in Engineering, Technology and Management, 8(5), 12939–12943.
35. Rongali, L. P. (2025). Compliance and Governance: Address the Role of Devops in Maintaining Compliance and Ensuring Governance throughout the Development Lifecycle. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5229546
36. Namdeo, A., Atulkar, A., & Porwal, R. K. (2022, August). Investigation of Two-Stage Epicyclic Gearbox for an Automobile for Energy Regeneration. In Biennial International Conference on Future Learning Aspects of Mechanical Engineering (pp. 363-376). Singapore: Springer Nature Singapore.
37. Pasumarthi, H. (2026). Architecting event-driven data pipelines for real-time supply chain decisioning. International Journal of Research and Applied Innovations (IJRAI), 9(2), 82–86.
38. Jabed, M. M. I., Ferdous, S., Ankhi, R. B., Gupta, A. B., & Hossain, M. S. (2025). AI-Driven Intrusion Detection Systems: A Business Analyst’s Framework for Enhancing Enterprise Security and Intelligence. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(5), 12708-12719.
39. Pradhan, C. COMPARATIVE STUDY OF MULTI-CLOUD DATA ENGINEERING STRATEGIES. https://www.researchgate.net/profile/Chittaranjan-Pradhan-4/publication/394442285_COMPARATIVE_STUDY_OF_MULTI-CLOUD_DATA_ENGINEERING_STRATEGIES/links/689ad689a49b125ba30cafdf/COMPARATIVE-STUDY-OF-MULTI-CLOUD-DATA-ENGINEERING-STRATEGIES.pdf
40. Hossain, M. S., Rahman, M. W., Hossain, M. S., & Ali, M. (2023). Applying Predictive Analytics to Optimize Government Operations and Improve Public Service Delivery in the United States. Applying Predictive Analytics to Optimize Government Operations and Improve Public Service Delivery in the United States, 1(8), 170-196.
41. Ganesh, N., Sriram, A., Krishnan, S. N., & Rao, T. S. (2025, June). Simultaneous Enhancement and Detection of Brain Tumors Using GAN. In Intelligent Computing-Proceedings of the Computing Conference (pp. 206-220). Cham: Springer Nature Switzerland.
42. Sengupta, J. (2024). Investigation of deep learning models for analysis of heart disorders in smart health care based IoT environment. J. Smart Internet Things (JSIoT), 2024, 01-16.
2. Anand, L. (2024). AI-Powered Cloud Cybersecurity Architecture for Risk Prediction and Threat Mitigation in Healthcare and Finance. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(Special Issue 1), 5-12.
3. Gopinathan, V. R. (2025). Intelligent workload scheduling for telecom cloud architecture using reinforcement learning. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(6), 13244-13255.
4. Sugumar, R. (2025). Unified AI Framework for Predictive Data Engineering and Real Time Prescription and Billing Systems. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 8(5), 17261.
5. Nallamothu, T. K. (2023). GENERATIVE AI IN HEALTHCARE: AUTOMATING CLINICAL DOCUMENTATION, DIAGNOSTICS, AND KNOWLEDGE SYNTHESIS. International Journal of Computer Technology and Electronics Communication, 6(1), 6376-6392.
6. Mudunuri, P. R. (2023). Governance-Aware Infrastructure-as-Code for Regulated Research Environments. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 6(4), 9017-9027.
7. Appani, C., & Guda, D. P. (2023). Self-supervised representation learning for zero-day attack detection in encrypted network traffic. Computer Fraud & Security, 2023(7), 20–31. Retrieved from: https://computerfraudsecurity.com/index.php/journal/article/view/661
8. Cherukuri, B. R., & Arulkumar, V. (2024, February). Optimization of Data Structures and Trade-Offs with Concurrency Control in Multithread Software Structures Using Artificial Intelligence. In 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT) (Vol. 5, pp. 1860-1865). IEEE.
9. Md Manarat Uddin, M., Rahanuma, T., & Sakhawat Hussain, T. (2025). Privacy-Aware Analytics for Managing Patient Data in SMB Healthcare Projects. International Journal of Informatics and Data Science Research, 2(10), 27-57.
10. Sammy, F., Chettier, T., Boyina, V., Shingne, H., Saluja, K., Mali, M., ... & Shobana, A. (2025). Deep Learning-Driven Visual Analytics Framework for Next-Generation Environmental Monitoring. Journal of Applied Science and Technology Trends, 114-122.
11. Karvannan, R. (2024). Human AI partnerships: Unlocking a more efficient, healthier future. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(5), 11243–11255.
12. Gentyala, R. (2024). From features to financial personas: Mapping feature transformation efficacy to customer archetypes in behavioral banking data. International Journal of Computer Science and Engineering Research and Development, 14(1), 127-145.
13. Dave, B. L. (2024). FUTURE-PROOF LIVING LEADING A BETTER LIFE WITH ARTIFICIAL INTELLIGENCE. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(5), 11233-11242.
14. Balamuralidhar Sarabu, V. (2020). Scalable data processing patterns for national retail platforms: An enterprise architecture for high-volume transaction systems. International Journal of Computer Technology and Electronics Communication (IJCTEC), 3(3), 1–14.
15. Raja, G. V. (2020). Metadata gets a makeover: The machine learning approach. International Journal of Computer Technology and Electronics Communication, 3(6), 2900-2903.
16. Jayaraman, S., Rajendran, S., & P, S. P. (2019). Fuzzy c-means clustering and elliptic curve cryptography using privacy preserving in cloud. International Journal of Business Intelligence and Data Mining, 15(3), 273-287.
17. Akila, R. (2024). A deep reinforcement learning approach for optimizing inventory management in the agri-food supply chain. J. Electrical Systems, 20(4s), 2238-2247.
18. Vayyasi, N. K. (2020). Intelligent transaction prediction and fraud detection in crypto markets using Java and generative AI. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 3(1), 2765–2779.
19. Soundappan, S. J. (2022). AI-based fault detection and isolation for reliability in modern power systems. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7106-7110.
20. Mathew, A. (2024). AI TRiSM: Trust, Risk, and Security Management in Cybersecurity. Cybersecurity, 4(3), 84-90.
21. Vimal Raja, G. (2025). Context-Aware Demand Forecasting in Grocery Retail Using Generative AI: A Multivariate Approach Incorporating Weather, Local Events, and Consumer Behaviour. International Journal of Innovative Research in Science Engineering and Technology (Ijirset), 14(1), 743-746.
22. Panda, S. S. (2025). Breaking dependency chains: Evaluating Microsoft’s Maia 100 as an alternative to NVIDIA GPUs in AI workloads. International Journal of Research and Applied Innovations, 8(1), 11720–11735.
23. Akash, T. R., Shokran, M., & Ferdousi, J. (2026). Role of Machine Learning in Securing US Digital Advertising Ecosystems Against Fraud and Market Manipulation. American Journal of Economics and Business Management, 9(2).
24. Gentyala, R. (2024). The Trust Threshold: How Public Perception of AI Harm Moderates the Impact of FinTech Innovation on Systemic Banking Stability. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 5(3), 169-190.
25. Suddala, V. R. A. K. (2025). Healthcare e-commerce platforms driving secure, scalable, and auditable service delivery. International Journal of Engineering & Extended Technologies Research (IJEETR), 7(1), 9340–9351.
26. Katta, T. B. (2023). Towards unified enterprise integration: Leveraging hybrid integration platforms to bridge on-premises and cloud environments. International Journal of Computer Technology and Electronics Communication (IJCTEC), 6(5), 7354–7365. https://doi.org/10.15680/IJCTECE.2023.0605014
27. Nallamothu, T. K. (2022). TRANSFORMING CLINICAL DOCUMENTATION AND ANALYTICS USING POWER BI AND DAX COPILOT. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7111-7119.
28. Devineni, A. (2025). Cognitive Load Reduction in On-Call Rotations via Predictive Alert Severity Scoring Using Machine Learning in Financial Cloud Operations. International Journal of Artificial Intelligence, Data Science, and Machine Learning, 6(1), 268-273.
29. Joyce, S. (2023). Optimizing SAP workloads on cloud-native platforms: A framework for intelligent resource allocation and performance scaling. International Journal of Science, Research and Technology (IJSRAT), 6(1), 9210–9219. https://doi.org/10.15662/IJSRAT.2023.0601002
30. Subramanyam, S. P. (2023). Cloud infrastructure automation and role-based access governance in Azure Kubernetes services. International Journal of Research Publications in Engineering, Technology and Management, 6(2), 8392–8400.
31. Tiwari, S. K. (2025). Automation Driven Digital Transformation Blueprint: Migrating Legacy QA to AI Augmented Pipelines. Frontiers in Emerging Artificial Intelligence and Machine Learning, 2(12), 01-20.
32. Karnam, V. S. (2025). Enhancing User Experience and Resilience Through System Scalability for Transforming Aviation Kiosk Systems Using Artificial Intelligence. Journal Of Engineering And Computer Sciences, 4(7), 738-745.
33. Potluri, M. K. (2025). Next-Gen Business Intelligence in Financial Services-Transforming Financial Efficiency with AI-Driven BI, Integration of AI/ML with BI tools. IJSAT-International Journal on Science and Technology, 16(4).
34. Panyala, V. R. (2025). Groundbreaking data processing architectures for petabyte-scale cloud storage systems. International Journal of Research Publications in Engineering, Technology and Management, 8(5), 12939–12943.
35. Rongali, L. P. (2025). Compliance and Governance: Address the Role of Devops in Maintaining Compliance and Ensuring Governance throughout the Development Lifecycle. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5229546
36. Namdeo, A., Atulkar, A., & Porwal, R. K. (2022, August). Investigation of Two-Stage Epicyclic Gearbox for an Automobile for Energy Regeneration. In Biennial International Conference on Future Learning Aspects of Mechanical Engineering (pp. 363-376). Singapore: Springer Nature Singapore.
37. Pasumarthi, H. (2026). Architecting event-driven data pipelines for real-time supply chain decisioning. International Journal of Research and Applied Innovations (IJRAI), 9(2), 82–86.
38. Jabed, M. M. I., Ferdous, S., Ankhi, R. B., Gupta, A. B., & Hossain, M. S. (2025). AI-Driven Intrusion Detection Systems: A Business Analyst’s Framework for Enhancing Enterprise Security and Intelligence. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(5), 12708-12719.
39. Pradhan, C. COMPARATIVE STUDY OF MULTI-CLOUD DATA ENGINEERING STRATEGIES. https://www.researchgate.net/profile/Chittaranjan-Pradhan-4/publication/394442285_COMPARATIVE_STUDY_OF_MULTI-CLOUD_DATA_ENGINEERING_STRATEGIES/links/689ad689a49b125ba30cafdf/COMPARATIVE-STUDY-OF-MULTI-CLOUD-DATA-ENGINEERING-STRATEGIES.pdf
40. Hossain, M. S., Rahman, M. W., Hossain, M. S., & Ali, M. (2023). Applying Predictive Analytics to Optimize Government Operations and Improve Public Service Delivery in the United States. Applying Predictive Analytics to Optimize Government Operations and Improve Public Service Delivery in the United States, 1(8), 170-196.
41. Ganesh, N., Sriram, A., Krishnan, S. N., & Rao, T. S. (2025, June). Simultaneous Enhancement and Detection of Brain Tumors Using GAN. In Intelligent Computing-Proceedings of the Computing Conference (pp. 206-220). Cham: Springer Nature Switzerland.
42. Sengupta, J. (2024). Investigation of deep learning models for analysis of heart disorders in smart health care based IoT environment. J. Smart Internet Things (JSIoT), 2024, 01-16.