Research Paper: A Risk Scoring Model for Managing Money Laundering Transactions

This report is a collaborative effort between the Research and Innovation Centre of Rabdan Academy, the MENA FCCG Working Group on Artificial Intelligence and the ADGM Academy Research Centre. It is our hope that the findings will serve as a catalyst for change, continued dialogue, collaboration, and action towards strengthening resilience against money laundering in the UAE and global financial sector.

The paper presents a high-level overview of the results of implementing a machine learning model for evaluating a risk score for anti-money laundering alerts and the impact on operational efficiency.  It outlines how this was achieved by enhancing the existing rules-based transaction monitoring process with a complementary machine learning model.  

The model allowed the compliance team within a UAE bank to better manage risk by auto-escalating high-risk alerts and hibernating low-risk alerts.