An exclusive article by Fred Kahn
Trade-based money laundering (TBML) remains one of the most complex and resource-intensive challenges for AML professionals. Unlike wire fraud or cash smuggling, TBML exploits the vastness and opacity of global trade—turning invoices, shipping documents, and commodity flows into vehicles for moving illicit funds. As supply chains digitize and regulators close gaps in traditional banking, criminals have responded with more sophisticated TBML schemes. In response, compliance teams are deploying innovative detection techniques, including the use of satellite imagery and advanced analytics. Understanding how TBML is evolving and where new risks are emerging is critical for any financial institution engaged in trade finance, commodities, or international payments.
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Trade-based money laundering: evolving typologies and new red flags
The focus keyword, trade-based money laundering, refers to the process of disguising the proceeds of crime and moving value using trade transactions. TBML can involve over- or under-invoicing, phantom shipments, falsified documentation, or manipulating trade terms to obscure the true nature and value of goods. Unlike traditional money laundering, TBML operates across borders and industries, making detection highly challenging for both banks and authorities.
Recent typologies have leveraged new loopholes in customs, shipping, and supply chain documentation. Criminal networks now routinely use related-party trades, circular shipping routes, and layered intermediaries to hide beneficial ownership and the true origin or destination of goods. Some schemes rely on collusion with freight forwarders, customs brokers, or warehouse operators to facilitate the movement of illicit value through otherwise legitimate supply chains.
Regulators are also tracking the rise of “third-country invoicing,” where goods are shipped via multiple jurisdictions, often with shell companies acting as intermediaries. This approach obscures the link between buyer and seller, creating opportunities for over- or under-valuation and the misreporting of trade statistics. AML professionals must be attuned to these patterns and conduct rigorous due diligence on counterparties, trade documents, and payment flows.
Red flags in TBML include discrepancies between shipping documents and physical cargo, mismatches between invoice values and market prices, and frequent changes in counterparties or trade routes. Unusual patterns in trade finance, such as rapid turnover of goods, inconsistent commodity codes, or use of high-risk ports, may indicate a TBML scheme at work. Financial institutions are now expected to supplement transaction monitoring with trade data analysis and cross-checks against shipping, customs, and open-source intelligence.
Satellite data, invoice fraud, and analytics in detection
One of the most significant advances in TBML mitigation has been the use of satellite imagery and geospatial analytics. By monitoring global shipping lanes, port activity, and the physical movement of goods, compliance teams can validate the existence and trajectory of shipments, spot “ghost” vessels, and detect anomalies in declared cargo. These tools allow for near real-time verification, which is essential in fast-moving trade finance transactions.
Invoice fraud remains at the heart of many TBML schemes. Criminals routinely generate fake invoices for non-existent goods or manipulate prices to justify illicit transfers. Modern compliance programs deploy AI-driven analytics to compare invoice values against historical and real-time market data, flagging discrepancies for further review. Machine learning algorithms can also spot patterns in counterparties, trade routes, and payment timing that deviate from normal business practices.
The integration of customs and shipping data into transaction monitoring systems is now a best practice for institutions exposed to trade finance risk. By linking payments with bills of lading, inspection certificates, and customs declarations, banks can establish a complete picture of the transaction’s legitimacy. This approach helps identify forged or duplicated documents, abnormal trade corridors, and unusual commodity flows that often signal TBML.
International regulators have begun to publish TBML typologies, red flag indicators, and case studies to help the industry improve detection. Collaboration with customs authorities, port operators, and logistics companies has also intensified, with joint initiatives aimed at sharing intelligence and standardizing document checks. Technology vendors now offer trade data aggregation, sanctions screening, and anomaly detection as integrated modules within broader AML platforms.
Building effective defenses in trade finance compliance
For financial institutions, building effective TBML defenses starts with a risk-based approach. This includes thorough customer due diligence, assessment of country and sector risks, and tailored controls for high-risk trade corridors. Ongoing training and typology updates are essential to ensure that front-line staff recognize the latest red flags and escalation protocols.
Data integration remains a persistent challenge. Trade finance operations are often siloed, with limited connectivity between payment systems, document management, and risk analytics. Investments in centralized case management, API-driven data aggregation, and cloud-based analytics platforms are transforming how banks connect the dots across transactions, documents, and counterparties.
Collaboration with external partners is increasingly important. Banks are now working more closely with logistics firms, shipping companies, and technology providers to share insights and enhance detection capabilities. Industry initiatives, such as trade-based information sharing partnerships and public-private typology exchanges, provide valuable intelligence that can be built into internal monitoring and escalation procedures.
Effective governance and escalation are also critical. TBML risk should be on the agenda of risk committees and executive boards, with clear accountability for identifying, managing, and reporting suspicious activity. Regular scenario testing, audits, and independent reviews help ensure that controls are fit for purpose and adapt to changing criminal tactics.
Conclusion: The future of TBML mitigation
TBML will remain a core AML risk as global trade continues to expand and diversify. The complexity of supply chains and the ingenuity of criminal networks ensure that detection will always require a mix of human expertise and advanced technology. Financial institutions that invest in data integration, geospatial analytics, and collaborative intelligence are best positioned to identify and disrupt TBML schemes before they escalate.
For AML professionals, ongoing education, scenario planning, and cross-sector collaboration are essential. The lessons of recent enforcement actions and evolving typologies must inform daily practice and strategic planning. By staying ahead of new schemes and embracing a holistic, technology-driven approach, compliance teams can transform TBML from an opaque risk into a manageable, transparent threat.
Related Links
- FATF Trade-Based Money Laundering Typologies Report (2020)
- FATF Red Flag Indicators for Trade-Based Money Laundering
- Egmont Group – Trade-Based Money Laundering Cases
- US Department of the Treasury: National Money Laundering Risk Assessment (see TBML section)
- European Banking Authority – Guidelines on ML/TF Risk Factors in Trade Finance
Other FinCrime Central Articles About TBML and Technology
- Why Good KYC Alone Can’t Stop Trade-Based Money Laundering
- AI and Blockchain in TBML Detection Deliver Promising Results
- TBML Enablers: Under‑Regulated Brokers and Free Trade Zones
- Game-Changer for AML: Satellite Data Reveals Undetected TBML Schemes
Some of FinCrime Central’s articles may have been enriched or edited with the help of AI tools. It may contain unintentional errors.
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