Cloud AI for Regulatory Compliance and Risk Management in Financial Institutions
DOI:
https://doi.org/10.47941/ijce.2759Keywords:
AWS Cloud AI, Regulatory Compliance, Risk Management, Financial Institutions, Machine Learning, Data Governance, Real-Time AnalyticsAbstract
Purpose: The financial services industry is increasingly adopting artificial intelligence (AI) solutions hosted in the cloud to meet the dual imperatives of regulatory compliance and effective risk management.
Methodology: AWS Cloud AI offers scalability, adaptability, and advanced analytics that enable financial institutions to monitor, detect, and respond to regulatory and risk-related challenges in near real-time. This paper explores the integration of AWS cloud-based AI technologies in regulatory compliance and risk management within financial institutions.
Findings: It provides a comprehensive overview of the current landscape, discusses prominent use cases, presents a framework for analyzing real-world applications, and outlines future directions.
Unique Contribution to Theory, Practice, and Policy: The financial services industry is increasingly adopting artificial intelligence (AI) solutions hosted in the cloud to meet the dual imperatives of regulatory compliance and effective risk management. AWS Cloud AI offers scalability, adaptability, and advanced analytics that enable financial institutions to monitor, detect, and respond to regulatory and risk-related challenges in near real-time. This paper explores the integration of AWS cloud-based AI technologies in regulatory compliance and risk management within financial institutions. It provides a comprehensive overview of the current landscape, discusses prominent use cases, presents a framework for analyzing real-world applications, and outlines future directions.
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Copyright (c) 2025 Kuthalingam Sankaralingam
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC-BY) 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
