Enhancing Regulatory Intelligence Through Financial Data Analytics: An Integrated Framework for Fraud Detection, Compliance Monitoring, and System Stability

Abstract

The study assesses how intelligent analytics can enhance the monitoring for anti-money laundering (AML), fraud prevention, regulatory reporting precision, and proactive monitoring of risk. The results show that financial data analytics can play a critical role in improving regulatory intelligence, providing the ability to monitor financial data in real-time, identify vulnerabilities early on, and make informed decisions based on the data. Regulatory systems can move from a reactive compliance management to a proactive risk governance by using machine learning based approaches. Moreover, the framework also promotes greater transparency, efficiency and stability of the financial system, by enhancing the coordination between financial institutions and financial regulators.