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World Journal of Advanced Research and Reviews
Article . 2025 . Peer-reviewed
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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Financial services in the cloud: Regulatory compliance and AI-driven risk management

Authors: Aladiyan, Anbarasu;

Financial services in the cloud: Regulatory compliance and AI-driven risk management

Abstract

This comprehensive article examines the transformative impact of cloud computing and artificial intelligence on regulatory compliance and risk management in the financial services sector. It explores how financial institutions are embracing cloud technologies to enhance operational capabilities while navigating an increasingly complex regulatory landscape. The article details how AI-driven solutions are reshaping compliance frameworks through advanced machine learning for fraud detection, natural language processing for regulatory analysis, and enhanced anti-money laundering systems. The article analyzes architectural considerations and implementation strategies for AI-powered compliance frameworks, supported by real-world case studies that demonstrate significant improvements in efficiency and effectiveness. Furthermore, the article investigates emerging technologies poised to further transform regulatory compliance, including federated learning, explainable AI, quantum computing, and solutions for decentralized finance. By examining both the opportunities and challenges of AI-driven compliance, this research provides valuable insights for financial institutions seeking to optimize regulatory compliance while maintaining operational efficiency in cloud environments.

Keywords

Risk Management, Artificial Intelligence, Regulatory Technology, Cloud Computing, Financial Compliance

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Top 10%
Average
Green
gold