World Day Against Trafficking in Persons: Can AI and quantum computing turn the tide?
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Marked on 30 July, International Human Trafficking Day, otherwise known as World Day Against Trafficking in Persons, was established in response to a request for the UN's Economic and Social Council (ECOSOC) to host a meeting to counter the buying and selling of fellow humans in 2006.
Fast forward to 2015, the 2030 Sustainable Development Agenda embraced the need for measures against human trafficking. Despite this goal being established a decade ago, human trafficking remains one of the most insidious crimes of our time. While hidden in plain sight, this form of organised crime continues to be embedded within global financial systems.
From 2020 to 2023, there were over 200,000 detected victims of human trafficking globally, according to the UN. Focusing on the word detected, the actual number is thought to be significantly higher, in the tens of millions across the world. The financial services industry has a responsibility and a clear opportunity to disrupt these networks, and in some cases, there are clear methods to do just that.
The WWF, for instance, released an environmental financial crime toolkit at COP16 in Cali, Colombia in October 2024 to help financial institutions minimise their exposure to this form of fraud. By reducing their risk exposure to illicit financial flows associated with land conversion, the financing and impact of this activity can also be decreased.
As the WWF states, 'environmental crime frequently converges with and often enables different financial crimes, including corruption and bribery, fraud, money laundering, tax evasion, and drugs, wildlife and human trafficking.'
The financial trail of exploitation
At the time of the WWF toolkit release, Celine Herweijer, group chief sustainability officer, HSBC, said: 'As a global trade bank, HSBC understands the complexities of global supply chains and the need to take a comprehensive approach to risk management in supporting our clients. The Environmental Crime Financial Toolkit is a practical way of helping financial institutions to improve their understanding of the risks related to the natural environment alongside financial crimes and secure nature-positive outcomes.'
To be clear, financial institutions are involved in human trafficking primarily through the laundering of money gained through trafficking activities. Banks are implicated when facilitating traffickers attempting to move and conceal their gains through prepaid cards and mobile payment applications, bank accounts and credit cards, remittance services and cryptocurrency. Funnel accounts may also be used to deposit illicit funds in one location and withdraw from another.
Alongside this, direct financial exploitation of victims through control over financial identities and banking products can also be considered implication, especially if they are coerced into opening accounts, taking out loans, or being forced to commit financial fraud.
Instead of being part of the problem, banks must strengthen their detection techniques and regularly report suspicious financial activity. Further, staff should be trained to recognise red flags.
Indicators of human trafficking
A third party controlling a customer's interactions or documents,
A lack of knowledge about their location,
Signs of poor health or abuse,
Frequent transactions in different locations,
Activity inconsistent with the customer's profile,
Frequent cash deposits without corresponding payments,
Use of prepaid cards and transactions linked to online commercial sex advertisements or foreign classified websites.
Traffickers rely on financial infrastructure to move money, pay accomplices, and launder profits. These transactions often appear ordinary - hotel bookings, transportation costs, small transfers - but when viewed through the right lens, they reveal patterns.
A Polaris Project 2018 report revealed that while 'there are certainly some completely un-banked traffickers, a significant portion of that overwhelming sum passes through legitimate financial services businesses. This happens through thousands of diffuse, small transactions. These intersection points offer ample – albeit not obvious or easy – opportunity for financial institutions to detect and disrupt human trafficking.'
Quantum computing: The next leap after AI
AI and machine learning are already being deployed to detect these anomalies. By analysing vast volumes of transactional data, AI can identify red flags such as unusual payment flows, repeated use of certain merchant categories, or geographic inconsistencies. Natural language processing (NLP) tools can also scan online platforms and dark web forums for trafficking-related language, helping banks and law enforcement stay ahead of evolving tactics.
Initiatives such as the Safe House Project, a nonprofit organisation working to increase identification of survivors, believe that Ai is becoming an 'essential weapon in the fight to protect vulnerable populations and dismantle trafficking networks.'
They go on to explain that AI is being used 'to track the untrackable. Traffickers often operate through subtle, coded language on social media, encrypted apps, and unindexed dark websites. AI tools can process millions of data points in real-time to detect suspicious activity, flag concerning language, and build predictive models that anticipate trafficking activity.'
However, the Safe House Project also explain that technology is 'not a solution by itself. When AI or data-driven models are deployed without survivor-informed oversight, they risk reinforcing harmful narrative or oversimplifying complex trauma. For example, automated systems that rely solely on keyword detection may flag false positives or miss nuanced cases, particularly in communities of color or with non-English-speaking survivors. This can lead to misidentification, retraumatization, or even criminalization of survivors.'
Technology should not be relied upon alone. Technology should be combined with training, trauma-informed practice, and direct survivor engagement. While AI is already making an impact, quantum computing holds promise for the next frontier. This technology enables advanced data analysis, pattern recognition, and could potentially provide the secure communication needed to surpass current classical computing methods and consider the sensitive aspect of this fraudulent behaviour.
Its ability to process and correlate massive, complex datasets at unprecedented speed could revolutionise how institutions detect trafficking networks. Quantum algorithms could simulate criminal financial ecosystems, optimise detection models, and enhance encryption protocols to protect victims' identities. Though still in its early stages, quantum computing offers a glimpse into a future where financial crime detection is not just reactive, but predictive.
Quantum algorithms are also being developed further to analyse social media for recruitment patterns and trace cryptocurrency transactions used by traffickers. Although, the use of advanced technologies like quantum computing in anti-trafficking efforts raises important concerns about data privacy, potential biases in algorithms, and the need for robust ethical guidelines and frameworks to ensure responsible use and protect human rights.
Why bank leaders must act
For financial institutions, this is not just a compliance issue, t's a moral imperative. Banks are uniquely positioned to intervene, but doing so requires more than technology. It demands cross-sector collaboration, ethical data use, and a commitment to putting human dignity first.
As digital transformation accelerates, so does the risk of traffickers exploiting new channels. But with that risk comes responsibility and opportunity. On this World Day Against Trafficking in Persons, we must reframe the role of financial services: not just as gatekeepers of capital, but as guardians of human freedom.
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