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Blog > How AI is turning the tide in the battle against modern slavery

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How AI is turning the tide in the battle against modern slavery

There is nothing modern about slavery. For as long as there has been a distinction between the powerful and the powerless, people have sought to take advantage of human labour, setting up the systematic exploitation of entire ethnic groups and vulnerable people. Despite hundreds of years of formalised abolition all over the world, slavery persists. It has adapted and evolved to survive – if not thrive – in the modern day. Today, organised criminal networks profit between $50-150Bn a year from the indentured labour of as many as 50 million victims worldwide.

This crime is closer than you think. 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 our daily supply chain – in our factories and farms, or for luxury items like flowers or fashion. As the current healthcare crisis evolves into an economic crisis, criminals are already seeking to take advantage and find new victims.

To profit from this flagrant abuse of basic human rights, criminal gangs use an array of psychological, financial, and physical techniques to maintain a tight control on those in their employ. Preying on often vulnerable groups including homeless or substance-dependent individuals often means victims are not even always aware of their own victimhood – their captors seen as simply helping them find work and shelter.

Trafficking individuals from overseas further traps victims to financial debt to the gangs, or by a language barrier, not able to communicate effectively with those around them at work or to the police. Finally, an ever-present threat of physical violence against victims and their families is used to ensure compliance.

Modern Slavery: a board-level issue

This all makes detecting and disrupting this type of crime extremely difficult. Cases reported to the Police (5,144 in 2019) and the National Referral Mechanism (6,985 in 2018) are rising, but perhaps more than 90% of this type of crime goes undetected.

This is not just a matter for the police. Businesses, financial institutions, and government bodies must all work together to spot the red flags that might hint to an underlying concern of exploitation. Legislation such as the 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 on the implementation, and who ultimately is responsible for its detection. Complex supply chains must be understood better, and organisations that inadvertently enable exploitation must all do their part if we are to hope to eradicate this type of crime for good.

Bold leadership, social policies and control frameworks will all be required to catch criminals and stop victims falling into the trap of modern slavery. A key enabler is being able to see the entire picture of a supply chain from all available data sources, but legacy technology and institutional stovepipes persist. The evidential trail of modern slavery, the data that could allow an elaborate international network to be completely unravelled often sits over many organisational boundaries. Enterprise analytics built to detect large scale money laundering and international sanctions evasion may not alert on the subtle, low-value payments made to a dozen migrant workers all sharing the same address. Fortunately, technology can now provide some vital support to companies, banks and governments in these areas.

The vital role of AI – 4 key areas

Artificial Intelligence is a breakthrough technology to help respond to the growing criminal threat. Advanced data analytics are now helping organisations automatically detect risk in their supply chain and customer base. It can scale their understanding of available data, joining the dots automatically to detect and prevent human trafficking and modern slavery. We are now seeing a step change in how entity resolution and natural language processing (NLP) are helping partners across the entire supply chain ecosystem make significant leaps forward in the detection of this pernicious and abhorrent crime.

We are seeing four key areas where our technology is now being deployed on the front lines of the fight against modern slavery:

Enhancing Due Diligence – Modern slavery relies on significant deception in acquiring legitimate enabling assets such as bank accounts, national insurance numbers and tax details. These allow money to be deposited, extracted and laundered, and having these legitimate identifiers avoids scrutiny by law enforcement and employers. Crucially, it enables criminals to place victims in well-paying jobs in the supply chain. Victims, who may not even speak the local language often lack the basic details that banks would be collected at on-boarding such as proof of residence address, phone number, email and other infrastructure – details which criminal gangs are happy to provide on their behalf and open accounts which they are in control of. Using analytics that can spot hidden connections between otherwise seemingly disconnected individuals means that next generation KYC checks can more reliably flag the signs of deception and exploitation and escalate to law enforcement if necessary.

Employment Vetting – placing vulnerable workers within legitimate employment is a key step in the modern slavery crime; 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. 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. 

Follow the money – The desire for wealth drives criminal behaviour. Money paid to victims needs to be interdicted by the gangs, extracted and then laundered so they can spend it on lavish lifestyles of cars, mansions and luxury goods. Transaction analysis within banks designed to catch money laundering often misses the small flows of money, taken from bank accounts in the victim’s name, often just with repeat visits to a local ATM. Banks provide the infrastructure from which modern slavery thrives. Behavioural analytics are now able to look across the network of accounts and their activities; combining contextual risk factors with transaction data to more easily spot these crime typologies and flag suspicious activity to law enforcement.

Complex Investigations  – police forces and other law enforcement agencies face an uphill struggle in piecing together data from a multitude of sources to identify suspects, victims and the infrastructure used in the trafficking and exploitation of victims. Data fusion technology, driven by platforms like Ripjar, are now allowing resource-constrained teams of intelligence analysts to more easily exploit data from any source – whether structured or unstructured. Natural language processing (NLP) and entity resolution combined with flexible link-analysis software mean investigators are able to build up a single, centralised knowledge graph for a case or network of criminal gangs – connecting the dots automatically between victims, suspects phone numbers, bank accounts, transactions, flight records or any other evidence collected during an investigation. 

Conclusion

The application of AI is a key development in the fight against modern slavery. It can automatically identify risks at any point in the client or employee lifecycle and help the entire ecosystem of employers, agencies, financial institutions and police forces understand the tell-tale signs of human trafficking and exploitation. Entity resolution, automatic prioritisation, natural language processing and data fusion all play a role in ensuring that relevant data is not missed and the links that criminals go to great lengths to hide are much more rapidly uncovered by compliance, risk and law enforcement analysts. Within a single platform, such as Ripjar, means these breakthroughs can all be harnessed while retaining full audit and accountability – bringing about a step-change in the way that modern slavery is detected and prevented.

David Balson
Director of Intelligence, Ripjar

www.ripjar.com