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The rapid evolution of financial technology has introduced complex risks that challenge traditional risk management frameworks, necessitating innovative solutions. This review paper aims to examine and synthesize existing research on real-time financial monitoring systems that use advanced AI and ML technologies to enhance risk management through continuous oversight. The focus includes traditional financial institutions and fintech companies across various regions to address disparities in risk management capabilities. The reviewed studies span five years, from 2018 to 2023, incorporating transactional records, compliance reports, and stakeholder surveys, providing a comprehensive informational and statistical basis. Using a mixed-methods approach that includes qualitative interviews and quantitative data analysis, the literature confirms that real-time monitoring systems significantly improve risk detection accuracy and operational efficiency. Specifically, the studies show a reduction in fraud incidents by 35% and an improvement in credit risk assessment accuracy by 25%. These findings indicate enhanced predictive capabilities and faster response times to emerging threats. The conclusions drawn are relevant for financial institutions, regulators, and policymakers aiming to improve risk management practices and compliance standards. The potential for further application includes broader adoption of real-time systems across the financial sector, ensuring enhanced stability and security in the face of evolving digital threats.
Abikoye et al. (Tue,) studied this question.