Financial Cloud-Based Framework for Secure Large-Scale Healthcare Analytics

John Anderson Barnes

doi:10.15662/IJRAI.2023.0606021

Authors

John Anderson Barnes Senior Cloud Engineer, Helsinki, Finland Author

DOI:

https://doi.org/10.15662/IJRAI.2023.0606021

Keywords:

Financial Analytics, Cloud Computing, Software Engineering, Healthcare Analytics, Data Security, Large-Scale Systems, Predictive Modeling

Abstract

The exponential growth of healthcare data and the widespread adoption of cloud computing have opened new avenues for advanced analytics, enabling improvements in patient care, operational efficiency, and strategic decision-making. However, the integration of financial and healthcare analytics at scale presents critical challenges, including data security, privacy compliance, and system reliability. To address these issues, this paper proposes a Financial Cloud-Based Software Engineering Framework for Secure Large-Scale Healthcare Analytics. The framework leverages cloud-native architectures, secure software engineering practices, and scalable data pipelines to manage and analyze large volumes of healthcare and financial data efficiently. It incorporates robust security measures, including encryption, access control, and compliance monitoring, to meet regulatory standards such as HIPAA, PCI-DSS, and GDPR. Modular and reusable software components, automated workflows, and AI-driven analytics enable predictive modeling, risk assessment, and operational optimization. Experimental results demonstrate enhanced data security, improved system scalability, and accurate analytics outcomes across large-scale healthcare datasets. This framework provides a comprehensive and secure foundation for organizations aiming to integrate financial and healthcare analytics in cloud environments effectively.

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