Guidance
The 2026 money laundering and terrorist financing risks within the British gambling industry
The Gambling Commission's money laundering and terrorist financing risk assessment of the British gambling industry for 2026.
6 - Casino (remote)
Sector rating
| Sector | Previous overall risk rating | Current overall risk rating |
|---|---|---|
| Casino (remote) | High | High |
The remote casino sector continues to be rated as high risk for money laundering.
Casino products with higher return to player ratios are at risk of being exploited for money laundering purposes, and peer-to-peer activity in poker carries higher ML and TF risk as it can facilitate the exchange of criminal funds between customers.
Remote casinos also have a high level of transactions. The gross gambling yield (GGY) for the sector in the period April 2024 to March 2025 was £5.0 billion, £4.2 billion of which was from slot games1.
The remote sector faces challenges as a result of customers not being present for verification purposes. This includes the use of fraudulent documentation to bypass customer due diligence (CDD) controls, as well as the risk of mule accounts being created. Developments in artificial intelligence (AI) tools create further challenges. The Gambling Commission is aware of an increase in the scale and sophistication of attempts to bypass CDD checks using false documentation, deepfake videos and face swaps generated by AI.
The remote sector is also exposed to financial flows from higher risk payment methods, including e-wallets, pre-paid methods and the presence of funds linked to cryptoassets. Further risks can be present when customers use multiple methods of payment, or an open-loop system is in operation.
Risks
| Vulnerability | Risk | Likelihood of event occurring | Impact of event occurring | Overall risk | Change in risk |
|---|---|---|---|---|---|
| Operator control | Operators failing to comply with prevention of money laundering and terrorist financing legislation and guidance | High (3) | High (3) | High (9) | No change |
| Operator control | Lack of competence of key personnel and licence holders which can be exploited by criminals seeking to launder the proceeds of crime | Medium (2) | High (3) | High (6) | No change |
| Operator control | Lack of adequate and relevant due diligence checks on customers who are not physically present for verification purposes | High (3) | High (3) | High (9) | New risk |
| Operator control | Lack of appropriate customer risk profiling and ongoing monitoring | Medium (2) | High (3) | High (6) | New risk |
| Operator control | Inappropriate AML thresholds - including thresholds that are not appropriate for the customer base or are predominantly loss based | High (3) | High (3) | High (9) | No change (new wording) |
| Operator control | High value customer schemes | Low (1) | High (3) | Medium (3) | Decrease in likelihood |
| Operator control | Lack of closed-loop system | Medium (2) | High (3) | High (6) | No change |
| Operator control | Failure to appropriately scrutinise source of funds documents | Medium (2) | High (3) | High (6) | New risk |
| Operator control | Training for staff is insufficient and is not appropriately tailored | Medium (2) | Medium (2) | Medium (4) | New risk |
| Operator control | Inappropriate controls relating to linked or duplicate accounts - this includes identifying linked accounts and, where multiple accounts are permitted, applying controls across accounts | High (3) | High (3) | High (9) | New risk |
| Operator control | Inadequate due diligence on white label partnerships | High(3) | High (3) | High (9) | No change (new wording) |
| Operator control | Inadequate due diligence checks on business-to-business relationships or business investors, resulting in receipt of illicit funds | Medium (2) | High (3) | High (6) | No change (new wording) |
| Customer | False or stolen identity documentation used to bypass controls to facilitate the laundering of criminal funds - this includes the use of AI tools to generate documents or videos | High (3) | High (3) | High (9) | No change (new wording) |
| Customer | Customer gambles with multiple remote operators to disguise the source of their funds | Medium (2) | High (3) | High (6) | Decrease in likelihood (new wording) |
| Customer | Customers who appear on financial sanctions lists laundering funds which are subject to an asset freeze | Low (1) | High (3) | Medium (3) | No change |
| Customer | Foreign politically exposed persons (PEPs) using casinos to launder criminal funds | Medium (2) | High (3) | High (6) | No change |
| Customer | Domestic PEPs using casinos to launder criminal funds | Low (1) | Medium (2) | Low (2) | No change |
| Customer | Customers making numerous low-level transactions to minimise suspicion and evade CDD requirements at the threshold (‘smurfing’) | Medium (2) | High (3) | High (6) | Decrease in likelihood |
| Customer | Third party use of customer accounts to obscure the source of funds and identity of the user, including the creation of mule accounts and the use of agents | High (3) | High (3) | High (9) | No change (new wording) |
| Customer | Customer linked to criminal activity | High (3) | High (3) | High (9) | New risk |
| Customer | Customer presents risks relating to their source of income - including access to third-party funds or funds originating from a cash intensive business | Medium (2) | Medium (2) | Medium (4) | New risk |
| Customer | Customer appears to be a disproportionate spender | Medium (2) | High (3) | High (6) | New risk |
| Customer | Customer uses a third-party payment method that is not in their name | Medium (2) | High (3) | High (6) | New risk |
| Customer | Customer displays suspicious or unusual wagering patterns - such as withdrawing after minimal play | High (3) | High (3) | High (9) | New risk |
| Geographic | Customers who are a resident of or are linked to high-risk jurisdictions using casino facilities to launder criminal funds | Medium (2) | High (3) | High (6) | No change (new wording) |
| Means of payment | Pre-paid methods including vouchers and cards - this payment method can make it difficult to identify the source of funds | Medium (2) | High (3) | High (6) | Decrease in likelihood |
| Means of payment | E-wallets - this payment method can make it difficult to identify the source of funds | Medium (2) | Medium (2) | Medium (4) | No change |
| Means of payment | Crypto asset transactions | Medium (2) | High (3) | High (6) | No change |
| Means of payment | Multiple methods of payment | Medium (2) | High (3) | High (6) | No change |
| Means of payment | Casinos acting as Money Service Businesses (MSBs) | High (3) | High (3) | High (9) | New risk |
| Product | Poker - peer-to-peer gaming presents risks of collusion and the potential transfer of funds between customers | High (3) | High (3) | High (9) | No change (new wording) |
| Product | High-stakes gambling on live casino games | Medium (2) | High (3) | High (6) | No change (new wording) |
Commission-controlled risks
| Vulnerability | Risk | Likelihood of event occurring | Impact of event occurring | Overall risk | Change in risk |
|---|---|---|---|---|---|
| Licensing and integrity | Gambling operations being acquired by organised crime to launder criminal proceeds or the ultimate beneficial ownership is linked to criminal activity | Low (1) | High (3) | Medium (3) | No change |
Case studies
Multiple accounts and false or stolen identity documents
A customer deposited approximately £40,000 over the course of 6 months, creating accounts using the details of 5 different individuals.
Circumvention of identity verification controls
A customer, whose account had previously been blocked due to suspicion of money laundering, was able to circumvent identity verification checks at sign-up and create a new account. Operator controls were insufficient to identify small discrepancies within customer sign up data fields.
Mule accounts and scrutiny of source of funds
A group of students were suspected of money mule activity. The operator’s controls identified that the students displayed similar wagering patterns with high returns. The operator’s subsequent investigations identified that the students had signed up on similar dates and their source of funds appeared to be the same.
An 18-year-old customer was suspected of gambling on behalf of third parties. A review of the customer’s source of funds information showed that they were gambling with multiple operators, their activity was funded by third parties, and their level of activity appeared disproportionate to their declared employment.
Customer linked to a high-risk jurisdiction
A customer was flagged for suspicious betting patterns and triggered enhanced customer due diligence controls. When asked to provide source of funds evidence, the customer advised this was not possible as their source of funds was cash brought to the UK from their home in a high-risk jurisdiction.
Pre-paid payment method
A customer made large deposits using a pre-paid card, and their gaming activity raised suspicion due to minimal wagering. The customer then proceeded to request withdrawals to different bank accounts. The risk in this case is that the customer may have been exploiting pre-paid methods, alongside open-loop systems, to move large volumes of funds while disguising their origin.
References
1 Industry Statistics - Annual report - Financial year April 2024 to March 2025 - Official statistics.
2026 money laundering and risks - Methodology Next section
2026 money laundering and risks - Casino (non-remote)
Last updated: 30 July 2026
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