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Trade-Based Money Laundering (TBML) has become one of the most complex and least understood threats to global trade and supply chains. It involves disguising illicit money by moving value through legitimate trade transactions.
With global merchandise trade reaching $24 trillion in 2023 (World Trade Organization) and estimated illicit financial flows from developing countries alone surpassing $1 trillion annually (Global Financial Integrity), TBML presents a growing risk to trade finance, AML compliance, and cross-border logistics.
This blog explores how trade-based money laundering works, how to identify its red flags, and most importantly, how businesses and financial institutions can prevent it effectively.
Trade-based money laundering refers to disguising the proceeds of crime by moving value through legitimate-looking trade transactions. Instead of routing money through banks, criminals manipulate trade documents such as invoices and bills of lading to hide illicit funds.
According to FATF, TBML is about making criminal proceeds appear clean using trade. Techniques include misinvoicing, fake shipments, and falsifying product descriptions or values.
Criminals use several TBML techniques to move illicit funds across borders. These include:
This involves misstating the value of goods on an invoice.
Example: An exporter invoices $100,000 worth of textiles as $20,000. The $80,000 difference is laundered through this under-declared trade.
Companies using workflow automation tools with built-in risk scoring can automatically flag such pricing discrepancies across invoices and documentation.
Issuing multiple invoices for the same shipment enables the seller to secure several payments for one consignment, often from different financial institutions. This creates artificial inflation of trade value and is a direct threat to financial crime compliance frameworks.
A buyer and seller may collude to create false shipping documentation. No physical goods are shipped, but payments are processed as if a transaction has taken place.
Fraudsters deliberately misclassify goods to avoid scrutiny. For example, precious metals could be labeled as scrap to avoid customs duties and inspections. Leveraging document classification systems powered by AI can help flag such inconsistencies.
Criminals set up complex corporate structures using shell companies and unrelated intermediaries across jurisdictions. This obscures the true origin and destination of goods and funds. Effective entity mapping is key to unmasking these networks.
TBML detection is notoriously difficult for several reasons:
High trade volumes: With millions of global transactions each day, manual checks are not scalable.
Document-based fraud: TBML often involves real-looking but falsified or manipulated trade documents.
Cross-border complexity: Trade involves multiple jurisdictions, each with different regulatory environments.
Siloed data systems: Customs, financial institutions, logistics firms, and compliance departments often operate on disconnected systems.
Knowledge gap: Trade professionals may lack expertise in money laundering, while financial compliance staff may not understand trade documentation.
According to a 2022 GAO report (GAO-22-447), one of the primary barriers in the U.S. is that no single agency is tasked with leading the national response to TBML, leading to coordination and intelligence-sharing issues.
Organizations can enhance TBML detection capabilities by recognizing the following red flags:
Mismatches between the commercial invoice and the packing list quantities or declared values
Use of ambiguous or generic product descriptions
Inconsistent or incorrect HS codes
Shipments routed through illogical or high-risk jurisdictions
Deploying tools with advanced data extraction capabilities can help uncover inconsistencies quickly.
Payments made by entities not party to the transaction
Use of shell or offshore entities with unclear business purposes
Unexplained multiple payments for a single shipment
Payments processed through high-risk countries
Significant variance from market pricing or trade norms
Repeated shipments of identical goods with the same documentation and patterns
Overuse of third-party brokers or agents
Frequent corrections or amendments to shipment and transaction records
The U.S. Immigration and Customs Enforcement (ICE) Trade Transparency Unit (TTU) reports that phantom shipments and false invoicing are two of the most common TBML tactics used today.
In a high-profile investigation, a company in Country A exported chemicals to a related shell company in Country B. These were then re-imported with inflated invoices to Country A. The circular trade route created an illusion of trade activity while laundering funds.
Latin American gold traders under-invoiced gold exports, declaring them as scrap and exporting to Dubai or Switzerland. Once there, the gold was reclassified and sold at market value, allowing laundered profits to be legitimized.
Global Financial Integrity (2023): An estimated $835 billion per year is lost to trade misinvoicing in developing countries alone.
UNODC (2022): Between 2% and 5% of global GDP, or around $2 trillion, is laundered annually through various means, including TBML.
U.S. ICE TTU (2019–2021): 444 TBML-related criminal arrests, $356 million in seizures.
GAO (2022): Identified coordination gaps among U.S. agencies and insufficient use of trade data for TBML detection.
Implement Advanced Trade Risk Screening Tools
Use platforms like Trademo TradeScreen to aggregate and analyze trade documentation, payment behavior, and logistics data.
AI-driven risk scoring for each transaction
Entity mapping and UBO (Ultimate Beneficial Owner) tracking
Automated compliance checks across invoice, shipping, and customs documents
Real-time alerts for anomalies or red flags
Document digitization, classification, and data extraction to convert paper-heavy trade workflows into structured, searchable data that can be cross-referenced across systems
These platforms can flag suspicious patterns like third-party payers, mismatched values, or circular trade, supporting efficient trade finance automation.
Expand KYC to KYT (Know Your Transaction) and KYCC (Know Your Customer’s Customer):
Verify beneficial ownership structures
Check for red flags in geographic risk indicators
Analyze trade history, credit behavior, and past shipping records
Validate that the customer has a physical footprint and legitimate operations
Integrating Letter of Credit scrutiny into this process can further ensure that financing instruments aren’t misused in TBML schemes.
Compare declared invoice values and quantities against historical trends and market data:
Leverage WTO, UN Comtrade, and national customs data for pricing benchmarks
Use bilateral trade data to identify value discrepancies
Cross-validate HS codes, shipping volumes, and declared values
Here, trade data digitization becomes crucial—enabling instant access to large data sets for pattern analysis.
Educate teams across procurement, finance, shipping, and compliance on:
The importance of TBML detection
How trade documents can be manipulated
What red flags look like and how to escalate them
Training programs aligned with ISBP 821 and UCP 600 standards help teams interpret and validate trade documents more effectively.
Join industry groups and working groups focused on AML compliance and trade transparency
Partner with trade transparency units and submit anomalies
Participate in public-private intelligence exchange forums
International cooperation and intelligence sharing often reveal hidden TBML networks that isolated compliance efforts cannot.
Governments and financial watchdogs are stepping up expectations around financial crime compliance and trade transparency:
FATF Recommendations 10, 13, and 20 emphasize TBML risk management.
AMLA 2020 (USA): Requires beneficial ownership checks and enhanced due diligence.
EU AML Package (2024): Includes trade-based money laundering risk as a key compliance domain.
Wolfsberg Group and Basel Committee also recommend AML compliance in trade finance.
Failure to comply may result in regulatory fines, reputational damage, and sanctions violations.
TBML is not a fringe issue; it is a systemic weakness in the architecture of international trade. With trillions in goods and money flowing across borders, the risk of abuse is real, growing, and sophisticated.
Combatting trade-based money laundering requires:
Intelligent, tech-driven platforms like Trademo TradeScreen
A collaborative compliance checks culture across teams and jurisdictions
Robust due diligence and document classification
Ongoing regulatory engagement and public-private partnerships
By taking these steps, businesses can reduce their risk exposure, fulfill AML compliance obligations, and protect the integrity of global trade.
It’s not just about compliance. It’s about leadership in securing the future of cross-border commerce.