Multilayered Risk Interception a Novel Framework for Integrating Corporate Governance Technology and Predictive Analytics in Financial Crime Prevention

Authors

  • Ogunkola Michael

DOI:

https://doi.org/10.38124/ijsrmt.v4i6.608

Abstract

Financial crimes are becoming more complex, faster, and sophisticated, which require a dynamic and combined response by institutions. Nonetheless, the existing methods of financial crime prevention are still divided, most of the time, with governance, technology, and analytics as separate entities rather than part of an integrated risk management strategy. The actuality of this theoretical paper is the Multilayered Risk Interception (MRI) framework that unites corporate governance, regulatory technology (RegTech), and predictive analytics by containing them in a unified, flexible system of preventing financial crimes. Based on the agency theory, systems theory, and techno-regulatory theory, this paper treats MRI as a proactive and real-time interception model that builds institutional resilience, regulatory compliance, and ethical leadership. The structure includes three interconnected levels: a Governance Level facilitating ethical management and strategic compliances, a Technological level of compliance builder realisation through automated technologies, and an Analytics one to identify risks and opportunities in their early stages based on big data analysis and artificial intelligence. Using an extensive literature review, it is found that the major gaps are the absence of holistic models, low levels of real-time adaptation, and the lack of strong accountability mechanisms in data-driven systems. The consequences of the MRI framework are extensive: it allows corporations to have a strategic integration in compliance management, regulators to have the basis of intelligent supervisory practice, and practitioners to have a single view of all risk indications. The study ends with a recommendation that institutions should use the principle of MRI, cross-functional training, and collaboration with regulators to establish ethically transparent AI. This framework provides the much-needed and opportune change to smart, holistic, and ethically based financial crime prevention in the digital age.

Downloads

Download data is not yet available.

Downloads

Published

2025-07-12

How to Cite

Michael, O. (2025). Multilayered Risk Interception a Novel Framework for Integrating Corporate Governance Technology and Predictive Analytics in Financial Crime Prevention. International Journal of Scientific Research and Modern Technology, 4(6), 61–65. https://doi.org/10.38124/ijsrmt.v4i6.608

PlumX Metrics takes 2–4 working days to display the details. As the paper receives citations, PlumX Metrics will update accordingly.