International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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AI-Driven Compliance Training in Finance and Healthcare: A Paradigm Shift in Regulatory Adherence

Author(s) Vijay Kumar Valaboju
Country United States
Abstract This article examines the transformative impact of artificial intelligence (AI) on regulatory compliance training in the finance and healthcare sectors. As these industries face increasingly complex regulatory environments, traditional training methods often fall short in ensuring comprehensive and up-to-date compliance. Through a mixed-methods approach, including surveys of 500 professionals and case studies of two major organizations, this article investigates the effectiveness of AI-powered compliance training systems. Key findings reveal that these systems significantly enhance training personalization, regulatory update integration, and risk management. Notably, organizations implementing AI-driven training reported a 37% reduction in compliance violations and a 42% improvement in employee engagement with training materials. The article also identifies challenges in implementation, including data privacy concerns and integration with legacy systems. This article contributes to the growing body of literature on regulatory technology (RegTech) and provides practical insights for organizations seeking to leverage AI in compliance training. The findings suggest that AI-powered systems represent a paradigm shift in regulatory adherence, offering a more adaptive, efficient, and effective approach to compliance training in high-risk industries.
Keywords Keywords: Artificial Intelligence, Regulatory Compliance, Finance and Healthcare, Adaptive Learning, Risk Management.
Field Computer
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-11-15
Cite This AI-Driven Compliance Training in Finance and Healthcare: A Paradigm Shift in Regulatory Adherence - Vijay Kumar Valaboju - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.30180
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.30180
Short DOI https://doi.org/g8rd5j
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