Following the Money: How Financial Institutions Can Detect and Disrupt Human Trafficking

Human trafficking generates an estimated USD 236 billion in annual profits globally, according to the International Labour Organization. These proceeds flow through the financial system — through banks, money service businesses, prepaid card networks, and increasingly through cryptocurrency channels. Yet the financial sector's ability to detect and disrupt trafficking-related financial flows remains profoundly underdeveloped. For an industry that processes trillions of dollars in daily transactions, the failure to systematically identify the financial footprint of one of the world's most serious crimes represents both a moral failing and a compliance gap.

The challenge is partly technical and partly structural. Trafficking-related financial flows often mimic legitimate business activity — payroll deposits, hospitality industry revenues, agricultural payments, and domestic remittances. Without specific typologies and detection scenarios designed around trafficking indicators, these transactions pass through conventional monitoring systems undetected.

But the opportunity is equally significant. Financial intelligence has proven to be one of the most effective tools for identifying trafficking networks, locating victims, and building prosecutable cases. Institutions that develop targeted capabilities are not only meeting regulatory expectations but contributing directly to the rescue of trafficking victims and the dismantlement of criminal enterprises.

Regulatory, Enforcement, and Market Context

FinCEN's advisories on human trafficking financial indicators, updated in 2024, provide a comprehensive set of red flags that financial institutions are expected to operationalise. These include patterns such as multiple individuals sharing a single address with disproportionate financial activity, frequent cash deposits followed by immediate wire transfers, and business accounts in high-risk industries showing revenue patterns inconsistent with their stated size and nature. AUSTRAC has issued parallel guidance for the Australian market, while the UK's Joint Money Laundering Intelligence Taskforce has published specific typologies for labour exploitation in sectors including agriculture, construction, and care work.

FATF's updated guidance on money laundering from human trafficking emphasises the need for a multi-agency approach, with financial intelligence units playing a central coordination role. The Egmont Group has facilitated cross-border intelligence exchanges that have directly contributed to trafficking prosecutions in multiple jurisdictions. Enforcement actions in 2025 included several cases where banks were cited for failing to file suspicious activity reports despite clear trafficking indicators in customer transaction patterns.

What the Data Is Showing

The ILO estimates that 27.6 million people are in forced labour globally, with forced labour in the private economy generating USD 236 billion in illegal profits annually. Financial sector data reveals that suspicious activity reports mentioning human trafficking indicators increased by 48% between 2023 and 2025, suggesting improved awareness but still representing a fraction of the likely true volume. Analysis by the Polaris Project found that financial indicators were present in over 85% of trafficking cases reviewed, yet fewer than 20% had been flagged by financial institutions prior to law enforcement intervention.

Network analysis is proving particularly valuable. Research by ACAMS and Themis found that trafficking operations typically show distinctive financial network patterns: a central controlling account receiving deposits from multiple personal accounts, with funds rapidly consolidated and transferred to property, vehicle, and business accounts controlled by the same network. These hub-and-spoke structures, when identified through entity resolution and network analytics, provide high-confidence indicators of trafficking activity.

Implications for Financial Institutions

Institutions must develop specific transaction monitoring scenarios targeting trafficking financial flows. This means going beyond generic suspicious activity patterns to incorporate the sector-specific, geographic, and behavioural indicators outlined in FinCEN, AUSTRAC, and FATF guidance. High-risk industry segments — including hospitality, agriculture, domestic services, nail salons, car washes, and construction — require tailored monitoring approaches that reflect the distinctive financial patterns of labour exploitation in each sector.

Training is essential. Front-line bank staff, particularly those in branches serving communities with high concentrations of vulnerable workers, need practical guidance on recognising the signs of trafficking in customer interactions. Indicators such as customers accompanied by controlling individuals, customers unable to answer basic questions about their own accounts, and patterns of third-party control over wages and finances should trigger enhanced scrutiny and, where appropriate, suspicious activity reporting.

Conclusion

The financial sector occupies a unique position in the fight against human trafficking. Every trafficking operation generates financial flows, and those flows must at some point touch the regulated financial system. Institutions that invest in targeted detection capabilities, staff training, and intelligence-sharing partnerships can transform their compliance infrastructure into a powerful tool for identifying victims and disrupting criminal networks. This is one area where doing the right thing and meeting regulatory expectations are entirely aligned.

Suggested Next Steps

• Implement specific transaction monitoring scenarios aligned with FinCEN, AUSTRAC, and FATF human trafficking financial indicators for your highest-risk industry segments.

• Deploy network analytics to identify hub-and-spoke financial structures characteristic of trafficking operations, particularly around payroll and cash-intensive businesses.

• Develop specialised training for branch and front-line staff on recognising behavioural indicators of trafficking during customer interactions.

• Establish partnerships with anti-trafficking organisations and law enforcement to participate in intelligence-sharing initiatives and contribute to victim identification efforts.

Sources: ILO, FinCEN, AUSTRAC, FATF, Egmont Group, Polaris Project, ACAMS, UNODC

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