Reported by Howard W. Herndon, Robert A. Broadbent, and John M. Scannapieco

(Summarized version featured below)

The article “Bridging the Gap: Applying Anti-Money Laundering Techniques and AI to Combat Tariff Evasion” by Womble Bond Dickinson explores the integration of artificial intelligence (AI) into anti-money laundering (AML) strategies, particularly to address trade-based money laundering (TBML) and tariff evasion. TBML is a complex method where illicit funds are disguised through legitimate trade transactions, making detection challenging due to the vast volume and complexity of global trade data. Traditional AML systems often struggle with high false-positive rates and limited adaptability to evolving laundering techniques.

To enhance detection capabilities, the article advocates for the use of AI-driven tools that can analyze large datasets to identify suspicious patterns indicative of TBML. These advanced systems employ machine learning algorithms to assess various risk factors, such as unusual trade patterns, discrepancies in invoicing, and anomalies in shipment data. By doing so, they can more accurately flag potential illicit activities, reducing the burden of false positives and allowing compliance teams to focus on genuine threats.

Furthermore, the article highlights the importance of integrating AI with existing AML frameworks to create a more robust defense against financial crimes. This includes the adoption of retrieval-augmented generation and semantic search technologies, which enable the system to understand and process complex trade documents and communications. Such integration not only improves the accuracy of detection but also enhances the efficiency of investigations by providing deeper insights into the relationships and networks involved in suspicious transactions.

In conclusion, the article emphasizes that the fusion of AI technologies with traditional AML practices is crucial in the modern financial landscape. As trade-based financial crimes become more sophisticated, leveraging AI’s capabilities allows for more effective monitoring and enforcement, ensuring that financial institutions can stay ahead of illicit activities and maintain the integrity of global trade systems.

Read full report: https://www.womblebonddickinson.com/us/insights/articles-and-briefings/bridging-gap-applying-anti-money-laundering-techniques-and-ai