A Survey on Regulatory Compliance and AI-Based Risk Management in Financial Services
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V4I4P106Keywords:
Artificial Intelligence, Machine Learning, Financial Risk Management, RegTech, Regulatory Compliance, Natural Language ProcessingAbstract
Artificial Intelligence (AI) has immensely changed the models for risk management and regulatory compliance in financial services delivery. The author of this article explains how artificial intelligence (AI) techniques, including machine learning (ML) algorithms, natural language processing (NLP), and predictive analytics, may be used in risk assessment, identification, and mitigation plans. AI makes it possible to automate compliance procedures, such as time data analysis and decision-making improvement, fraud detection, regulatory reporting, and anomaly identification. The advent of RegTech explains how the sector is moving towards the technologically enabled compliance that allows financial institutions to keep up with the rapidly changing regulatory landscapes. Against these developments, there are still outstanding issues, such as explaining AI models, data privacy, or standard regulatory principles. The thorough literature review allows pointing out the variety of methodological tools used to investigate the influence of AI on financial risk and compliance, including textual analysis, qualitative study, and empirical analysis. The findings demonstrate AI's revolutionary potential in addition to the essential limitations that need to be addressed. The present research is part of developing an understanding of the ways the AI revolutionizes financial supervision, suggesting that the future research direction should focus on the ethical implementation of AI, explainability, and regulation compatibility. Altogether, AI is a breakthrough in the progressive development of data-based financial governance
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