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New AML identity verification solutions can aid UK problem gamblers

by Andrew Engledow

New identity verification solutions developed to prevent money laundering can also aid problem gamblers in the UK. How? The solutions’ identity resolution and identity intelligence capabilities help UK gaming operators determine if gamblers are betting more than they can afford.

Gambling is big business in the United Kingdom. In 2023, more than half of the adult population gambled.[1]

Wherever there is gambling there is a risk that some people will be harmed by gambling. The UK is no exception. But there’s hope. New identity verification solutions initially designed to detect and prevent money launderers may help ease the plight of problem gamblers and their families.

The consequences of problem gambling

While statistics about problem gambling are sometimes disputed, everyone accepts that too many people experience gambling-related harm. This harm affects gamblers, their spouses, children, and other loved ones.

Some problem gamblers commit crimes to fund their addiction. Problem gambling also has significant co-morbidity rates with alcohol use disorder, drug misuse, depression, anxiety, and other mental health problems. According to Public Health England, problem gamblers present a direct cost to the UK government of roughly £413 million annually.[2] (The UK also estimates that “intangible” costs to society push that figure to between £1.05 billion and £1.77 billion.[3]) Direct costs include, for example, the £114.2 million spent each year to treat the depression experienced by problem gamblers.[4]

Reducing the risk of problem gambling

While there is support available for people experiencing gambling-related harm, the aim of all concerned with gambling is to reduce the risks of problems arising in the first place. As more gambling takes place online, the risks to people change and new ways to protect them evolve.

Technology offers opportunities for improvements to know your customer (KYC) checks and information sharing. This new technology is a cutting-edge identity verification platform. Offered by a company called GamView in association with Napier compliance solutions (and deploying Babel Street Name Match for AI-powered name matching), the platform was designed to help operators meet recent guidance for reducing instances of money laundering in the gaming industry.

Service delivery

UK gaming operators should be able to develop profiles of a potential customer before he or she is allowed to bet. These profiles would determine who those potential gamblers are, how much money they have, and how much they can afford to spend.

But what if verification services were offered as a pay-as-you-need subscription utility? GamView technology makes this scenario possible. A centralized verification utility could enable operators to verify individuals and glean a single customer view across operators. This view would help operators better spot problem gamblers. This same utility could act as a centralized system for family members requesting support.

GamView, in association with Napier, would provide this utility as a multi-tenant cloud-based service, managing the ongoing technical needs of each operator account. The company would also curate verification data among gambling operators, with each operator maintaining control over its own client base. This single view would improve operators’ ability to spot and stop those outspending their profiles.

Read a previous post for more information on how GamView technology can support problem gamblers while concurrently better spotting money launderers.

End Notes 

1. Data Commons, “Place Explorer: United Kingdom,” accessed January 2024, 

2. Public Health England, “Gambling-Related Harms Evidence Review,” Public Health England, 11 January 2023,,to%2013%20years%20(9%25) 

3. Ibid 

4. Ibid  


All names, companies, and incidents portrayed in this document are fictitious. No identification with actual persons (living or deceased), places, companies, and products are intended or should be inferred. 

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