Efficient Compliance Techniques for Mitigating Trade Based Money Laundering Risks

Navaera Worldwide
4 min readJul 7, 2021

FATF defines trade-based money laundering or TBML as “the process of disguising the proceeds of crime and moving value through the use of trade transactions in an attempt to legitimise their illicit origins.” According to the International Narcotics Control Board, TBML is the third most used method for laundering money globally. Hundreds of billions of dollars are laundered every year through illicit trade-based financial transactions. As per a study by the Global Financial Integrity organization, illicit inflows and outflows to and from developing and emerging economies were between 14–24% of their total trade from 2005–2014 while trade-based transactional crimes may amount to as much as $2.2 trillion globally each year.

In trade-based money laundering, monies are usually laundered by misinterpreting the price of goods being traded or by manipulating the number of goods being imported or exported. Some common methods used are falsifying invoices, manipulating the shipment of goods, misusing trade chains, and circumventing trade laws to dodge the scrutiny of trade-centric documents. TBML techniques may vary in complexity and are often used in conjunction with money laundering methods to further obscure the money trail.

1 Key Techniques for Mitigating TBML Risks

Here are some techniques to help Financial Institutions identify TBML related risks and efficiently mitigate them-

1.1 Detection of Attempts to Overcome Trade Restrictions and Sanctions

Lack of relevant and substantial information can seriously impair FIs in identifying suspicious transactions especially those which involve detecting Ultimate Beneficiary Owners (UBOs) eventually receiving the traded commodities or items. “transfer of ownership” and the “disguise of the true nature of a transaction” are two very critical challenges that FIs struggle with. These challenges not only threaten global trade finance systems but also pose a much serious threat to society as these TBML methods may be used to finance terrorist activities across the globe.

Hence, financial institutions need to have an efficient AML/CTF compliance program that can scan transactions using global watch list options including OFAC, CAPTA Sanctions list, UN Act Compliance, etc. from around the world, including Global UBO registers. Identifying suspicious importers and exporters, or inter-connected trade parties and their UBOs, can greatly enhance AML/CTF programs and help Financial Institutions in checking and flagging malpractices carried out through TBML.

1.2 Commodity Price and Documents Verification

FIs usually find it difficult to ascertain the authenticity of various factors that govern a trading transaction as they often lack relevant information regarding the terms of business contracts such as discounts given on bulk purchases, the quality of goods being imported, etc. Most of the time, necessary documents are not available to see the full picture. This is a huge challenge as FIs have to invest a lot of manual time and effort in understanding a particular transaction to determine its authenticity.

This makes it extremely essential to implement pre-set industry-specific rules and scenarios that are ideal for anti-TBML monitoring processes like detection of over invoicing of shipments, identifying multiple invoicing, and discovering other red-flagged suspicious activities. Creating customised fraud matrices to determine the risk of potential transactions and applying tailored screening profiles appropriate to the customer or transaction risk can dramatically reduce the manual efforts FIs require to put to mitigate TBML risks.

1.3 Detection of Possible Collusion Between Buyers and Sellers

Analyzing business relationships and identifying UBOs of traded goods can be a huge challenge for financial institutions. Discrepancies and errors in investigative workflows are often discovered after several rounds of manual investigations. This can lead to significant losses not only to FIs but also to genuine trading parties. Also, it can be time-consuming and burdensome for FIs to manually monitor ongoing transactions in real-time, effectively verify documents, scan customers against various jurisdictional sanction lists, and properly manage human resources.

Therefore, FIs must use a multi-layered approach in finding relationships between the buyers and sellers. Implementing a unique solution to centralize data originating from various sources and detecting hidden relationships existing between entities and individuals can go a long way in identifying TBML transactions. It is crucial to track export/import transactions occurring between completely unrelated trading parties, especially when the transaction amount is very high, or when multiple transactions are carried out involving smaller amounts across the borders. Analyzing complex data sets offering a 360-degree view of relationships existing between transacting entities can provide a holistic overview of the entire financial transaction. This can greatly aid FIs in detecting spurious transactions related to trade.

2 Summary

FIs should consider implementing effective automated AML processes and actively engage with law enforcement agencies and government authorities to curb TBML. The wider the regulatory perspective on TBML, the more efficient it is for FIs to prevent it. AML and CTF guidelines issued by FATF and international authorities should also be stringently followed to detect and address trade-based transactions if TBML is to be effectively controlled. Also, FIs can contribute towards a safer society by educating their AML personnel in implementing proper anti-TBML policies and, in addition, raising awareness amongst the masses about the implications of risks imposed by TBML activities.

The author is associated with Navaera Worldwide, a global knowledge management company that works closely with the financial services industry globally assisting them in enhancing their regulatory compliance and customer engagement processes.

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