Illicit activity tied to trade has existed since nearly the inception of international trade, yet trade-based money laundering, or TBML, remains deeply challenging for regulators and financial institutions alike.

Global trade is voluminous, and many trade transactions are still heavily reliant on paper documentation and manual processes. Limited resources at financial institutions and cross-border challenges complicate things further.

By and large, these issues have not been resolved despite being recognized by the AML world for decades. The silver lining is that emerging tools and technologies, including AI and machine learning, may offer at least a partial answer to the question of how to tackle trade-based financial crime.

In this energetic conversation with Simon Moss, CEO of SymphonyAI Sensa, we explore why TBML has become such an entrenched problem in the financial crime world, what strategies and resources financial institutions need to tackle it, and how a combination of data-sharing consortiums, international cooperation and tech tools could offer a way out of the TBML conundrum.