How AI can help combat slavery and free 40 million victims

Despite legalised slavery being abolished in the UK in 1833 and the US fighting a Civil War that culminated in the Abolition Act of 1863, the practice has evolved to thrive all over the modern world. Today, organized criminal networks profit an estimated $150 billion a year from the indentured labour of as many as 40 million victims worldwide.

One in four of these victims are children. Three-quarters of them are woman and girls. Victims are often not even aware of their own victimhood, and reports outline that the COVID-19 pandemic has made the situation even worse.

According to the Global Slavery Index, slavery is most prevalent in countries in Africa, Asia and the Pacific, with 10 counties estimated to account for nearly 60% of all victims. However, it wrong to assume this is a far-away problem. In the UK, some estimates put the number of victims at 100,000 or more.

These victims, trafficked into wealthier countries from overseas, often find themselves deep in the supply chains on which modern economies and society rely – such as food production, manufacturing and producing the clothes we wear. For business, failing to comply with legislation such as The Modern Slavery Act (2015) can carry serious consequences.

Criminal gangs use an array of psychological, financial and physical techniques to maintain tight control. Trafficking individuals across borders traps victims, as many face financial debts to the gangs or language barriers. Criminals also often employ an ever-present threat of physical violence against victims and their families to ensure compliance, which makes detecting and disrupting this type of crime extremely difficult. It is believed that nearly 90% of this type of crime goes undetected.

New technologies can help reveal human trafficking, prosecute the traffickers and free those enslaved.

The evidential trail of modern slavery and the data that could reveal its international network sits over many organisational and geographical boundaries. Complex supply chains need to be unravelled so that organisations are not inadvertently part of this exploitation. Fortunately, technology can now provide some vital support to investigative authorities, companies, banks and governments.

Criminals are adept at using the latest technologies to evade detection, and the mainstreaming of trans-national crime has had a further impact on how national and international police organisations operate and have to disrupt complex crime. In areas such as cybersecurity, the impact of technology, complex communications platforms and the globalization of crime by default is leading to a dramatic fall in traditional outcomes.

This has driven the cybersecurity community to adopt technologies such as artificial intelligence (AI), but we need to take these new pioneering tactics and deploy them more widely.

Money paid to victims needs to be interdicted by the gangs, extracted and then laundered. This can be a weak point in which much is put on by governments and enterprises to detect abuse. Transaction analysis within banks designed to catch money laundering can miss small flows of money, taken from bank accounts in the victim’s name, often just with repeat visits to a local ATM.

Behavioural analytics are now able to look across the network of accounts, combining contextual risk factors with transaction data to more easily spot these crime typologies and flag suspicious activity to law enforcement.

Investigative authorities can face further challenges in bringing together disparate data streams from a multiple of sources to identify suspects, victims and infrastructure used in trafficking and exploitation of victims.

Natural language processing (NLP) and entity resolution combined with flexible link-analysis software mean investigators are able to build up a single, centralised knowledge graphs for a case or network of criminal gangs, as well as to connect the dots automatically between victims, suspects phone numbers, bank accounts, transactions, flight records or any other evidence collected during an investigation.

Modern slavery relies on significant deception in acquiring legitimate enabling assets such as bank accounts, identity documents, and tax details. Victims, who may not even speak the local language often lack the basic details that banks collect at on-boarding such as proof of residence address, phone number and email, details which criminal gangs provide on their behalf and open accounts which they are in control of. These legitimate identifiers allow criminals to control money without scrutiny.

Crucially, they can also often enable criminals to place victims in well-paying jobs in the supply chain; the perception that victims are mostly paid cash or off-the-books is largely false. With legitimate assets and tax codes, victims can unknowingly earn tens of thousands of pounds a year while only receiving a few pounds per week on top of their food and shelter.

Using analytics that can spot hidden connections between otherwise seemingly disconnected individuals means that next-generation know your customer (KYC) checks can more reliably flag the signs of deception and exploitation and escalate to law enforcement if necessary.

Employment agencies and supply chain partners such as factories and warehouses are now employing their own due diligence based on the details provided by workers. Entity resolution – AI that can uniquely identify individuals from ambiguous and sparse datasets – can detect the tell-tale red flags of exploitation such as unusual numbers of employees sharing the same address or bank details.

The application of AI is a key development in the fight against modern slavery, but it is only part of the solution. More work is needed to make these complex technologies much more accessible to where it is most needed. This technology can only go so far.

Bold leadership, social policies and control frameworks are now required to catch criminals and stop victims falling into the trap of modern slavery. Legislation such as the Modern Slavery Act (2015) and the EU’s upcoming 6th Anti-Money Laundering Directive have all made this crime a board-level issue, but questions remain who ultimately is responsible. Businesses, financial institutions, and government bodies must all work together to deploy technology to spot the red flags and end exploitation.