Article Series: 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 Financial Crime Compliance Group (MENA FCCG) and the ADGM Academy Research Centre.

The report is a joint undertaking by the three entities, and 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.

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.  

The paper outlines how this was achieved by enhancing the existing rules-based transaction monitoring process with a “bolt on” machine learning model.  The model allowed the bank to better manage risk by auto-escalating high-risk alerts and hibernating low-risk alerts. The document serves as a blueprint for Financial Institutions to develop similar models.