AI-Enhanced SAP HANA Cloud for Healthcare and Finance: Real-Time Staffing, Data Quality, Scalable Migration, and MFA-Secured Fraud Detection
DOI:
https://doi.org/10.15662/IJRAI.2025.0805010Keywords:
AI-Enhanced SAP HANA Cloud, Healthcare, Finance, Real-Time Staffing, Big Data, Scalable Data Center Migration, Multi-Factor Authentication, Deep Learning, Fraud Detection, Machine Learning, Data Security, Cloud Computing, Financial TechnologyAbstract
AI-Enhanced SAP HANA Cloud has become a transformative technology for both the healthcare and finance sectors. By integrating real-time data processing, AI-driven staffing models, deep learning for fraud detection, and robust security through Multi-Factor Authentication (MFA), SAP HANA Cloud optimizes both operational and decision-making processes. In healthcare, AI enables real-time staffing optimization, reducing inefficiencies in resource allocation. In finance, SAP HANA Cloud facilitates big data quality management, enabling organizations to maintain accurate and consistent financial records while detecting fraudulent activities. The scalability of SAP HANA Cloud supports seamless data-center migration, helping organizations minimize operational risks during transitions. However, challenges related to implementation costs, data privacy concerns, and technical complexity remain. This paper explores the benefits, challenges, and future potential of AI-Enhanced SAP HANA Cloud, with a focus on its applications in healthcare and finance. The discussion also includes the role of deep learning in fraud detection and the importance of data quality and security in these critical sectors.
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