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Following the Money in Human Trafficking: Financial Crime as a Lever Against Modern Slavery

  • Writer: TrustSphere Network
    TrustSphere Network
  • Jun 11
  • 3 min read

Human trafficking and forced labour generate hundreds of billions of dollars annually, according to ILO and UN UNODC estimates. And yet, of every dollar laundered through trafficking networks, only a tiny fraction is detected by the financial system. The disparity between the scale of trafficking and the scale of financial-sector detection has become difficult to justify, and pressure is mounting on institutions to close that gap.


For financial institutions, this is not a peripheral issue. Trafficking proceeds flow through mainstream banks, and the reputational consequences of being visibly linked to a trafficking case are severe. The challenge is that trafficking typologies often look superficially like legitimate labour-intensive businesses, and without specific calibration, even well-functioning monitoring programmes miss them entirely.


The good news is that trafficking typologies are increasingly well-documented. The bad news is that translating typologies into operational detection remains a significant gap for most institutions. Closing that gap requires a combination of dedicated typology work, targeted training, and sharper integration with law enforcement.


Regulatory, Enforcement, and Market Context


FATF has published multiple reports on money laundering from human trafficking, and the Egmont Group continues to facilitate financial intelligence unit cooperation on the theme. Polaris, Stop the Traffik, and the Thomson Reuters Foundation have produced detailed typology papers that are widely used by compliance teams. FIUs in multiple jurisdictions have also signalled that they will prioritise feedback on trafficking-related SARs, which gives institutions a stronger incentive to invest in the quality of those reports.


In the UK and Australia, modern slavery legislation has broadened corporate obligations and pulled the issue into supplier due diligence. Regulators in the US, UK, and Asia-Pacific have repeatedly signalled that trafficking-linked SARs are a priority. Regulators in the US, UK, and Asia-Pacific have increasingly linked modern slavery legislation to financial crime obligations, creating a broader accountability envelope than the AML regime alone.


OFAC and comparable authorities have sanctioned individuals and networks tied to trafficking operations, reinforcing the intersection with sanctions compliance. The combined effect is that trafficking is moving from a niche topic within AML to a top-ten priority, and institutions should plan programme investment accordingly.


What the Data Is Showing


ILO estimates place the number of forced-labour victims at roughly 28 million globally. UN UNODC has documented significant cross-border flows of proceeds, with particular concentration in labour trafficking corridors across Asia, the Middle East, and parts of Europe. The scale of these flows — set against the low volume of detected trafficking SARs globally — illustrates how much upside there is in better calibration, even within existing monitoring architectures.


Chainalysis and Reuters have both highlighted the growing use of digital payment rails and informal value transfer systems to move trafficking proceeds, often alongside the legitimate remittance economy. Recent ILO and UN UNODC reporting also shows that forced-labour proceeds increasingly flow through formal financial institutions rather than purely through cash, which means that the opportunity to detect is genuinely there.


Implications for Financial Institutions


Detection requires dedicated typologies: unusual remittance patterns, wage-account irregularities, concentration of labour-intensive SMEs, and specific red flags around personal-identity documents. Generic AML rules rarely catch trafficking without this calibration. Institutions should also consider partnerships with specialist NGOs such as Polaris and Stop the Traffik, whose typology expertise can meaningfully improve detection quality without requiring large internal investment.


The quality of SAR narratives matters. Financial intelligence units rely on precise trafficking indicators to connect scattered reports across institutions. Weak narratives effectively break the chain. Where possible, trafficking-related cases should be handled by teams with specific training rather than generic fraud or AML investigators, because the narrative patterns and red flags are distinct.


Institutions should also integrate modern slavery risk into supplier and correspondent due diligence, so that exposure is identified beyond retail accounts alone. Finally, the link between trafficking and modern-slavery obligations means that institutions should coordinate responses across AML, procurement, and ESG functions, which most do not yet do well.


Conclusion


Trafficking is a global atrocity with a financial footprint — and that footprint is visible to institutions willing to look. Building trafficking-specific typologies, training frontline staff, and writing precise SARs are concrete steps that, over time, contribute meaningfully to disrupting these networks. Banks are not the primary actors against trafficking, but they are uniquely positioned to see patterns no one else can — and acting on that information can change outcomes in ways few other interventions can match.


Suggested Next Steps


  • Adopt trafficking-specific typologies within transaction monitoring and case review.

  • Train frontline staff on behavioural indicators in branch and customer-service interactions.

  • Strengthen SAR narrative quality with explicit trafficking red flags.

  • Integrate modern slavery risk into supplier and correspondent due diligence.


Sources: FATF typology reports, ILO global estimates, UN UNODC, Polaris, Stop the Traffik, Thomson Reuters Foundation, OFAC designations, Chainalysis, Egmont Group.


TrustSphere helps financial institutions design and deploy intelligent fraud and financial crime detection solutions. Visit www.trustsphere.ai

 
 
 

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