Despite global efforts, human trafficking continues to grow in 2025, an organized criminal industry built on exploitation and hidden financial flows. According to the International Labour Organization, an estimated 28 million people are trapped in forced labour, commercial sexual exploitation, or other forms of modern slavery. This global crime generates more than $236 billion annually. Behind that staggering number are countless lives that are manipulated, coerced, and sold, while the financial flows powering it quietly pass through the global financial system—mostly undetected.
As a citizen, as a father, and as CEO of a company on a mission to combat financial crime with AI, I find that unacceptable. But as we reflect on World Day Against Trafficking in Persons, I believe there’s reason for cautious optimism.
Why? Because for the first time, artificial intelligence is enabling financial institutions to detect the undetectable, and stop human trafficking where it hurts: the money flow.
The Financial Web Fueling Human Trafficking
Let’s be clear: Human trafficking is not only a humanitarian crisis. It’s a massive financial operation, with sophisticated networks that use legitimate banking and payment services to move, disguise, and profit from illicit earnings.
In a 2023 report, the United Nations Office on Drugs and Crime (UNODC) emphasized that human trafficking networks exploit gaps in financial oversight. Traffickers increasingly use small-value payments, cash-intensive methods, or seemingly innocuous businesses to mask illegal activity.
Traditional transaction monitoring systems, built on rigid rules and thresholds, were never designed to catch this. When someone deposits £37.98 every few days to advertise on an adult website, that doesn’t raise alarms in a legacy system. But it should.
When AI Stepped In: Lessons from Santander UK
On a recent episode of The Banker Exchange podcast, I had the opportunity to speak with Anita Hawser, about how AI can help banks combat human trafficking. Santander is one of the first major banks to deploy ThetaRay’s AI specifically to detect this hideous crime, and their results speak volumes.
Santander UK’s financial crime compliance team used ThetaRay’s AI to uncover a trafficking ring linked to a 34-year-old male customer. On the surface, his activity seemed innocuous: recurring payments to classified ad websites, small withdrawals from ATMs, flights to Romania, and mobile top-ups. But AI spotted what rule-based systems missed—the pattern behind the payments, the context across borders, and the subtle indicators of exploitation.
What made the difference? A shift from linear rules to dynamic pattern recognition. Rather than chasing red flags, ThetaRay’s Cognitive AI Transaction Monitoring solution identified what was not normal, then surfaced the case with precision. AI helped make the haystack smaller enabling the compliance team to find more needles.
AI’s Unique Strength: Detecting What Humans Alone Can’t See
Traditional compliance models rely on human-defined risk thresholds: alerts for transactions over $10,000, large cash deposits, or payments to flagged jurisdictions. But trafficking doesn’t follow rules, it avoids them.
Cognitive AI flips the paradigm. It learns what’s normal for each customer and each network, then highlights what deviates. It does this without bias, without fatigue, and at a scale no human team can match.
At ThetaRay, our models learn continuously from billions of transactions and global typologies. When deployed by our customers, those models adapt to local data environments, identifying risk factors unique to each geography and customer base.
And critically, our AI doesn’t just reduce false positives. It boosts true positives. In fact, in many deployments across Europe and North America, our customers are reporting increases up to 70% of productive alerts—those that lead to Suspicious Activity Reports (SARs).
Regulators Are Watching — And Encouraging Innovation
The move toward AI is no longer just a technological upgrade. It’s becoming a regulatory expectation.
The European Banking Authority (EBA), for example, recently issued guidelines requiring financial institutions to adopt proactive, risk-based approaches to sanctions and financial crime compliance. In the US, FinCEN has emphasized the importance of innovation in detecting and disrupting illicit finance, including trafficking.
More and more, regulators are signaling that “check-the-box” compliance won’t cut it. They expect banks and fintechs to take advantage of the tools available and that includes AI.
Beyond Detection: A New Role for Compliance
I believe we’re entering a new era, one where compliance teams move beyond gatekeepers to enablers.
When AI helps us pinpoint that 5% of truly suspicious activity, we can safely fast-track the 95% that’s legitimate. That means better customer experiences, faster onboarding, and expanded access to underserved regions, all without compromising on compliance or security.
Imagine a world where a payment from Africa to Latin America isn’t delayed out of fear because AI has already verified it as safe. That’s the real opportunity. As I said on the podcast: “Once we know what’s bad, we can confidently say yes to everything else.”
AI is not magic. It won’t stop human trafficking alone. But in the hands of banks, fintechs, payment service providers, regulators, and investigators it’s a powerful tool to tip the balance.
At ThetaRay, we’re committed to supporting financial institutions around the world in this mission. From London to Singapore, from Tier 1 banks to digital challengers, our partners are already proving that with AI you can detect the undetectable.
This World Day Against Trafficking in Persons, I invite every AML manager, Chief Compliance Officer, and Risk Executive reading this to ask a hard question:
Are we doing everything we can, with the tools we have, to stop human trafficking?
About the Author
See ThetaRay
in action
Request a Demo
