Intelligent Risk Monitoring Systems: A Review Of Machine-Learning Tools Advancing Early Detection of Financial Irregularities in U.S. Markets

Christian; Issabella

Intelligent Risk Monitoring Systems: A Review Of Machine-Learning Tools Advancing Early Detection of Financial Irregularities in U.S. Markets

Author(s)	Christian, Issabella
Country	United States
Abstract	The financial markets in the United States are rapidly evolving and data-intensive environments, where traditional rule-based risk monitoring systems are constrained in their ability to detect financial irregularities at an early stage. The review examines how machine learning intelligent risk monitoring systems are transforming early detection practices in the U.S. financial markets. The study is based on peer-reviewed literature published between 2020 and 2025, identified through Google Scholar and ScienceDirect. The study provides a synthesis of evidence on machine learning structures, the fields where financial applications are to be implemented, the performance of early detection, the issues in implementation, and the governance of AI. The results demonstrate a noticeable shift from periodic risk assessment to continuous monitoring systems that apply supervised, unsupervised, deep learning, and hybrid approaches in detecting fraud, credit risk assessment, market monitoring, and operational risk management. The literature suggests that dependable early detection in practice depends on more than algorithmic performance, but also data quality, system adaptability, organisational coordination, and regulatory compliance. Matters of governance, such as explainability, accountability, and human oversight, emerge as central determinants in sustainable adoption within regulated financial environments. By incorporating technical and governance approaches, the review explains the context within which intelligent risk monitoring systems enhance early detection and the existence of persistent gaps concerning long-term system performance, resilience, and the assessment of early detection capabilities in U.S. markets.
Field	Business Administration
Published In	Volume 17, Issue 1, January-June 2026
Published On	2026-03-09
Cite This	Intelligent Risk Monitoring Systems: A Review Of Machine-Learning Tools Advancing Early Detection of Financial Irregularities in U.S. Markets - Christian, Issabella - IJAIDR Volume 17, Issue 1, January-June 2026.

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Intelligent Risk Monitoring Systems: A Review Of Machine-Learning Tools Advancing Early Detection of Financial Irregularities in U.S. Markets

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