The trade finance system is being targeted by money launderers and terrorist financiers as they increasingly turn to global trade for moving illicit funds into the formal economy.
A new PwC US whitepaper reports that the rise of trade-based money laundering (TBML) presents serious and costly risks associated with a growing number of fraudulent transactions.
Conveying value through goods, not dollars
Money laundering and terrorist funding activities continue to gain strength and prominence. As much as 80% of illicit financial flows from developing countries are now channeled through TBML methods, according to Global Financial Integrity, a research and advocacy organization. The growing number of TBML transactions has gained the attention of regulators, who are increasingly citing these illicit activities in warnings issued to global financial institutions.
The Association of Certified Anti-Money Laundering Specialists, ACAMS, describes TBML as the process by which criminals use a legitimate trade to disguise criminal proceeds. The crime involves a number of schemes in order to complicate the documentation of legitimate trade transactions. Such actions may include moving illicit goods, falsifying documents, misrepresenting financial transactions, and under- or over-invoicing the value of goods.
“Today’s trade-based money laundering activity goes beyond traditional laundering of criminal funds to include terrorist financing and intentional efforts to circumvent international sanctions,” says Vikas Agarwal, a managing director in PwC’s Advanced Risk and Compliance Analytics practice. “To evade detection, traffickers are becoming more sophisticated in their methods, and financial institutions should remain two steps ahead by deploying advanced analytical and statistical techniques.”
The challenge, according to PwC, lies in identifying the questionable transactions within the haystack of the massive global trade business. Among the TBML techniques used by launderers, under- and over-invoicing is quite common, as small discrepancies in stated values make the odds of detection, using current systems, close to zero.
Big data holds clues to illicit trade
PwC’s whitepaper points to the mining of big data as a critical component of an effective anti-TBML program, which involves extracting and analyzing data that is both structured and unstructured, and that resides both in-house and externally.
A viable program should also properly align across key business areas and incorporate automated processes using a variety of advanced techniques, including:
• Text analytics. Text analytic tools can identify suspicious numbers, words, and important data points. They can also identify context such as specific form fields (e.g., customer names, types of products).
• Web analytics and web-crawling. These methods can search websites to review shipment and customs details and compare them against their corresponding documentation.
• Unit price analysis. A statistics-driven approach that uses publicly available data and algorithms. This method relies on detecting if unit prices exceed or fall far below global and regional established thresholds.
• Unit weight analysis. This technique involves searching for instances where money launderers are attempting to transfer value by overstating or understating the quantity of goods shipped relative to payments.
• Network (relationship) analysis of trade partners and ports. Enterprise analytics software tools can identify hidden relationships in data between trade partners and ports, and between other participants in the trade lifecycle. Such tools can also identify potential shell companies or determine outlier activity.
• International trade and country profiling analysis. An analysis of publicly available data may establish profiles of the types of goods that specific countries import and export, flagging outliers that might indicate TBML activity.
Download PwC’s “Goods gone bad: Addressing money-laundering risk in the trade finance system” [Registration required]