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Anti-money Laundering Solutions Help UK Gaming Operators Meet Government Guidance

by Andrew Engledow

New guidance from the British government has gaming operators rethinking their anti-money laundering solutions.

Brits love to gamble. They visit High Street betting shops and glitzy gaming parlors. They bet in bingo halls and online. They play the slots, and the ponies. Even Queen Elizabeth II got into the act, owning a slew of racehorses. (The Buckingham Palace party line holds that while Elizabeth profited from the ownership of these horses, she never bet. Scuttlebutt has it otherwise.)[1] 

All this gambling coalesces into big business. In 2023, the UK reported a gross gambling yield of £15.1 billion, making it the largest gambling market in Europe.[2]

Wherever there’s gambling, money laundering follows. The United Kingdom’s National Crime Agency estimates that criminals launder anywhere between £36 billion and £90 annually in that country[3] — a significant percentage through gambling. To improve anti-money laundering (AML) efforts, the UK’s Department of Culture, Media & Sport has published a white paper called High Stakes: Gambling Reform for the Digital Age. It issues new guidance for gaming operators.

This article will examine the current state of gambling regulations in the UK; new guidance for operators; and how cutting-edge technology can help operators better comply with gaming laws.

The current landscape

Across operators and jurisdictions worldwide, the gambling environment makes money laundering easy. Cash in/cash out scams are popular: criminals exchange dirty money for playing chips, bet a hand or two, then convert the chips back into cash. This process disguises washed money as legitimate winnings. Sometimes, criminals collude: one player “loses” dirty money to a cohort. The cohort then appears to have legitimately won at the tables. Some money launderers wash their money by buying casino chips from gamblers at an inflated price (paying £1.25 for every £1 chip, for example). They cash out these chips and voila: dirty money is cleaned.

The United Kingdom understands the problem. Gaming laws, including the Gambling Act of 2005[4] and the Gambling (Licensing and Advertising) Act of 2014[5], establish AML guidelines that operators must follow. These laws apply to gaming operators based in the UK, and to foreign operators providing online gambling opportunities to persons residing in the UK. The laws list various conditions and codes of practice for gaming operators in the fields of AML, anti-terrorist financing, social responsibility, consumer fairness, and other topics.

To comply with these laws, UK operators now undertake significant customer verification processes. Before placing a bet, persons gambling in physical or virtual spaces must prove their age and identity via passports, drivers’ licenses, National Identity Cards, or similar government-issued IDs. Operators must then match these gamblers to existing entities in government and commercial databases, including electoral roles and credit agency listings. Operators examine the gambler’s bank statements; sources of wealth (evidence of inheritance, family support, dividends from sales of assets); sources of funds (pay stubs, bank statements, tax returns); and income patterns. Additional checks may be conducted before online gamers suspected of money laundering are allowed to withdraw money from their gaming accounts.

A note on problem gamblers

The United Kingdom estimates that 430,000 people in the country suffer from compulsive gambling. To help them, the UK has developed a multi-operator self-exclusion database called GAMSTOP. Problem gamblers can sign up to this database, essentially telling all land-based and virtual gaming parlors, “Do not allow me to gamble at your facility.” Operators are obligated to refuse service to those enrolled in the self-exclusion database. They must check the database as part of the customer-verification processes discussed under “The current landscape.”

From this information, operators develop a profile of each gambler, determining his or her spending threshold. These profiles should “demonstrate that the customer has personal funds from a reputable source to support [their] level of expenditure,” according to the UK Gambling Commission.[6] If operators determine that a prospective gambler earns £1,000 per week, has £8,000 in savings, £10,000 in available credit, and no additional history of wealth, he should simply not have the funds to gamble £15,000 every month. His attempt to gamble this much money may indicate an instance of money laundering.

Unfortunately, existing AML efforts aren’t always enough to keep gaming operators from running afoul of British law.

In 2023, the Gambling Commission penalized the William Hill Group with a record £19.2 million fine for failure to abide by AML and social responsibility regulations.[7] In 2022, the Entain Group received a £17 million fine for similar failures.[8] Earlier this year, the Commission fined Gamesys Operations Ltd. £6 million for insufficiently identifying risks of money laundering or problem gambling.[9]

New AML guidance

To curb instances of money laundering and better spot those who have self-excluded, the UK has issued new guidance. This guidance encourages UK gambling operators to curb money laundering by improving “the integrity and probity of the applicant and the applicant’s ability to conduct gambling in a solvent and responsible manner in compliance with law and regulation.”[10]

Key to meeting this guidance is improvement of gambler onboarding processes and the creation of a more holistic view of each customer.

Frictionless onboarding and an improved customer view

GamView, working in association with Napier (a leading compliance solutions provider), has developed an AI-powered identity verification platform to help gaming operators meet the UK’s recent guidance. When registering with GamView in person or online, the potential gambler provides the platform with his name and other pertinent information. GamView then provides an instant, one-click check of that information against credit databases, sanctions lists, anti-terrorist lists, industry exclusion lists, and self-exclusion lists. This fast, secure process helps operators quickly build gamer profiles in alignment with the UK’s AML mandates, while concurrently easing verification processes for new gamblers who want to start betting quickly.

GamView works via an application programming interface (API) that sits atop an operator’s existing customer identification systems. This helps operators avoid the need to replace expensive systems to improve identity-verification processes. Regular updates help operators meet evolving regulatory obligations. GamView is available via the operator’s deployment model of choice: on-premises or in the cloud.

The importance of name matching

Name matching and entity resolution are important parts of the customer-verification process. GamView name matching is powered by Rosette® by Babel Street. Rosette is a best-in-class name-matching system that compares, matches, and coalesces names of people, places, and organizations.

The name-matching process can be tricky. You rarely find an exact match. And mismatches aren’t always obvious. High-velocity, high-stakes name matching in gaming and other industries requires AI-powered natural language processing capabilities that empower operators to set their own match thresholds and fine-tune match parameters in alignment with gambling use cases and tolerance for risk.

Resolving entities

Remember the mandated customer-verification processes discussed under “The current landscape?” The Rosette name-matching engine powering GamView helps operators determine whether the “Pete Smith” hoping to gamble is the lawful holder of the driver’s license issued to “Peter A. Smith.” Rosette also distinguishes the potential gambler “Pete Smith” from a sea of “Peter Smiths” and “Peter A. Smiths,” and “Pete Smythes,” some of whom might appear on sanctions lists or exclusions lists.

This process of finding the “right” Pete Smith is called entity resolution. It is accomplished in part by matching entities to other identifiers including dates of birth, places of birth, relatives, Twitter handles, and Facebook IDs. For gaming operators, entity resolution is a significant first step in creating a single customer view.

Current benefits

The benefits of frictionless onboarding, name matching, and entity resolution are myriad for operators, bettors, and regulators.

Frictionless onboarding enables qualified gamblers to be verified quickly, so they can start gaming in moments without being unduly burdened by the signup process. Slow verification processes may drive potential gamblers to different, faster operators. In worst case scenarios, those gamblers may be driven to offshore, unregulated markets.

Operators benefit when legitimate gamblers can start playing right away. They increase profits. But more than that, they know that they are obtaining these profits from legitimate gamblers, and that their gaming venues and sites are avoiding illegitimate revenue streams. They don’t have to worry about enabling money-launderers, running afoul of regulatory mandates, and risking fines. Because of the up-to-the-minute nature of GamView’s verification processes, they further avoid the risk of a customer saying, “I signed up for the self-exclusion list three days before I walked into your casino. You shouldn’t have let me gamble. I’m reporting you to the Gambling Commission.” With GamView, operators can also bypass the common scenario of starting off a questionable gambler with a minimal spending threshold — potentially missing out on revenue. Finally, since Rosette name matching dramatically reduces instances of false positives, operators benefit from a significant reduction in the amount of human investigative time needed to examine questionable gamblers.

Regulators also benefit. Too often, in their examination of operators, regulators lack a clear view of the technology deployed for AML efforts, its capabilities, and its alignment with regulatory mandates. Visualizations available through GamView’s single interface can help give regulators a better understanding of what information is being checked and when.

Possibilities, powered by AI

Clearly, there are significant benefits to implementing GamView technology now. The future looks even brighter.

In matching names and resolving entities, the GamView platform lays the groundwork for developing a single view of each customer. This is important because currently there is no central repository covering all gamers — rendering all identity-verification efforts inherently incomplete. If Operator A has created a profile determining that Gambler B should be betting no more than £1000 each month, there is nothing to keep that gambler from “outspending his profile” by simply registering with different operators. Doing this, he spends £1000 each month at Casino C, another £1000 at Casino D, and £2000 total at online gaming sites E and F. A cohesive, cross-operator customer view such as that powered by GamView would help operators more easily spot those who are outspending their profile, either for purposes of money laundering or because they have a gambling problem.

Right now, every operator must perform its own customer verifications, incomplete as they may be. This puts a significant cost burden on operators, for everything from buying, deploying, updating, and maintaining technology to employing staff and training them in appropriate investigative techniques.

But what if verification services were offered as a pay-as-you-need utility that all operators could buy into? New name-verification technologies such as GamView make this scenario possible. A centralized verification utility could provide frictionless onboarding while enabling operators to verify individuals, see spam profiles, and glean a single customer view across operators.

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. GamView would 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.

These capabilities, offered as a utility, would further ease onboarding processes — increasing profits for operators. Consumers would only have to sign up with one operator, rather than having to validate their identities with every operator they patronize.


Powered by Napier technologies and Rosette, GamView is uniquely capable of providing the seamless onboarding, naming matching, and entity resolution that can help stop money laundering and protect problem gamblers. It also has potential as a pay-as-you-need utility that all UK operators could subscribe to — providing them with a single customer view, and dramatically reducing the costs associated with AML compliance.


1. Brown, Tina, “The Diana Chronicles,” Doubleday, 2007

2., “GB Gambling Industry Statistics,” November 2023,

3. United Kingdom National Crime Agency, “Money Laundering and Illicit Finance,” accessed January 2024,

4., “Gambling Act 2005,” accessed January 2024,

5., “Gambling (Licensing and Advertising) Act 2014,” accessed January 2024,

6. United Kingdom Gambling Commission, “Gambling License Information, Guidance and Advice for Businesses and Individuals,” accessed January 2024,

7. United Kingdom Gambling Commission, “William Hill Group Business to Pay Record £19.2m for failures,” March 2023,

8. United Kingdom Gambling Commission, “Entain to Pay £17 Million for Regulatory Failures,” August 2022,

9. United Kingdom Gambling Commission, “£6m fine for online operator Gamesys,” January 2024,,Money%20Laundering%20(AML)%20failings

10. United Kingdom Department for Culture, Media & Sport, “High Stakes: Gambling Reform for the Digital Age,” April 2023,


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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