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Turning the tide: How AI can support the financial crime battle against modern slavery

As recently as 2020, the Centre for Social Justice estimated that there were 100,000 or more modern slaves in the UK. And estimates suggest that globally indentured labour generates between $50-150bn.

Criminal gangs use various sophisticated psychological, financial, and physical techniques to maintain control over their workforce. Often targeting vulnerable people who have nowhere to turn. An example is debt bondage – where people end up working for little or no wages in order to repay debt. One of the most common forms of modern slavery, according to the UN.

A woman sits alone on a bed... Consequences of Modern Slavery

A board-level issue

Detecting and disrupting modern slavery remains difficult, and the issue is only getting worse. Cases reported to the police are rising, yet despite this, up to 90% of slavery still goes undetected. This makes the crime as hidden as it is pervasive, deepening consequences for business, government and society which must work together to spot the red flags that hint to an underlying concern of exploitation.

Laws such as the EU’s 6 th  Anti-Money Laundering Directive & The Modern Slavery Act (2015) are raising the topic of modern slavery to board-level, but questions remain surrounding implementation and accountability.

It is not easy, but as a global community, we have the capacity to end slavery. Bold management, social policies and control frameworks will all be essential. Unfortunately, legacy technology and institutional structures both complicate the path ahead.

Organisations have a regulatory duty to identify anti-money laundering (AML) and enforce sanctions through strong customer due diligence. While successful detection of money laundering will ultimately identify many involved in human trafficking and modern slavery, we know that detection is limited. The UN estimates that $1.6T is laundered through the global financial system annually and only 1% of illicit financial flows are intercepted globally.

The types of payments used to commit human trafficking can be particularly hard to detect. Low-value payments made to a few dozen migrant workers all sharing a few addresses is unlikely to trigger a suspicion.
Fortunately, there is significantly enhanced awareness of the issues and technology can now provide some vital support to companies, banks and governments.

The role technology can play in stopping modern slavery
Modern Artificial Intelligence (AI) approaches, using Machine Learning to grapple with huge quantities of data to identify patterns, provide a new opportunity to tackle slavery and trafficking which were simply not practical manually. Even with an army of compliance staff. Advanced data analytics help companies automatically detect risk in their supply chain and among their customers. It can scale their understanding of available data, joining the dots automatically to detect and thwart human trafficking and modern slavery.

We are now seeing a step change in how entity resolution and natural language processing (NLP) are helping suppliers and partners across the entire supply chain network make substantial leaps forward in tackling this crime. Using AI to sift through vast amounts of data, technology is now being deployed on the front lines of the fight against modern slavery in the following ways:

Enhancing Due Diligence - Traffickers and criminal gangs have adopted strategies to avoid detection – such as acquiring legitimate enabling assets such as national insurance numbers, tax details and bank accounts.

This allows funds to be deposited, withdrawn, and laundered, and all the while avoiding scrutiny by the police and employers. Perhaps most importantly, this allows criminals to put victims in well-paying jobs in the supply chain. Criminal gangs also maintain control of victims’ earnings by opening bank accounts in their names but not in their control, providing the bank with the required onboarding documents, such as proof of address and utility statements.

Analytics can spot hidden connections between otherwise seemingly disconnected individuals, meaning that next generation KYC checks can more reliably monitor for deception or violations and involve the law, if necessary.

Screening can also identify those perpetrating slavery and trafficking. Banks and other organisations can get early warning of clients who have been associated with illicit activity before – either through exposure in the news media or through specialist watchlists. At the root of all criminal activity is profit. Making these crimes difficult or impossible to commit profitably will ultimately benefit the potential victims.

Employment Vetting - It is a widespread misconception to think that victims are mostly paid in cash or off-the-books. With legitimate assets and tax codes, victims can unwittingly earn tens of thousands of pounds a year while only receiving a small stipend on top of their food and accommodation. But times are a changing. Prompted by the Modern Slavery Act and Anti-Money Laundering Directives, employment agencies and supply chain partners such as factories and warehouses are increasingly looking at the details provided by workers, conducting their own due diligence. Sophisticated entity resolution – 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. 

Complex Investigations - Data fusion technologies are now helping 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 help investigators build up a single, centralised knowledge graph for a case or network of criminal gangs. The graph helps connect the dots automatically between victims, suspects phone numbers, bank accounts, transactions, flight records or any other evidence collected during an investigation. 

The application of AI, data fusion and other techniques is a key development in the fight against modern slavery and human trafficking. They can automatically isolate risks at any point in the client or employee lifecycle and help the entire ecosystem of businesses, agencies, financial institutions and authorities understand the tell-tale signs of human trafficking and exploitation.

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Gabriel Hopkins

Gabriel Hopkins

Chief Product Officer

Ripjar

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28 Oct 2021

Location

London

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This post is from a series of posts in the group:

RegTech

Regulatory technology, is a new technology that uses information technology to enhance regulatory processes. With its main application in the Financial sector, it is expanding into any regulated business with a particular appeal for the Consumer Goods Industry. Often regarded as a subcategory under FinTech, RegTech puts a particular emphasis on regulatory monitoring, reporting and compliance and is thus benefiting the finance industry.


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