Compliance Intelligence · For compliance, MLRO and responsible gaming
A regulator will ask what you noticed, and when.
Compliance Intelligence is the GAMWIT layer that flags money laundering and player harm patterns early, and shows the signals behind every flag. GAMWIT supports the review. Your MLRO decides.
- 01Which players should we look at this week?Anti-Money Laundering
- 02Who is showing early signs of harm?Responsible Gaming
- 03Can we show why this was reviewed?Dashboards
- 04Did we notice it early enough?KPI Alerts
Each question is answered by one GAMWIT model
Why it matters
Compliance is judged on what you noticed, and how early.
A pattern that sat in the data for six weeks before anyone looked at it is a problem, whatever the final decision was. GAMWIT moves the signal earlier and keeps the reasoning on screen.
See the questions this team asks£17M
fine for a major UK operator in 2022 over social responsibility failures.
£6M
fine for a major gaming operator over AML breaches.
$14B
estimated yearly social cost of problem gambling in the US (Dec 2023).
Source: figures as cited on GAMWIT's Responsible Gaming and Anti-Money Laundering model pages.
The questions
What the compliance team asks
Which players should we look at this week?
GAMWIT gives the MLRO a ranked queue instead of a threshold list, so review time goes to the cases most likely to be real.
The likely cases first, with the evidence attached.
Answered byAnti-Money Laundering
Who is showing early signs of harm?
GAMWIT scores every player for risk of harmful play, No, Low, Medium or High, so your responsible gaming team can step in while a light-touch intervention is still enough.
Every player, every run, the same way.
Answered byResponsible Gaming
Can we show why this was reviewed?
The signals behind every flag are on the screen, which is what an audit trail needs. GAMWIT Dashboards hold the record.
The reasoning is visible, not reconstructed later.
Answered byDashboards
Did we notice it early enough?
GAMWIT Alerts fire when the pattern appears, not when the monthly report is put together.
Flagged the same day.
Answered byKPI Alerts
These are advisory models. They do not file a Suspicious Activity Report, freeze an account, or decide that a player is being harmed. They flag patterns worth a human review. Every regulatory decision stays with your MLRO and your responsible gaming team.
In a walkthrough, we answer these questions on your own players.
Book a walkthroughThe models
The models this team runs
Two models, both advisory. They change what your team sees and when. Your team still decides.
- Responsible GamingFlags players whose behavior shows early signs of gambling harm, so your responsible gaming team can step in while it still helps.See the model
- Anti-Money LaunderingFlags transaction and behavior patterns worth a compliance review, so the MLRO works from an earlier, clearer signal than a threshold rule gives.See the model
Delivery
How the answers reach the team
Predictions go into the CRM your team already runs. Everything else arrives three ways.
- The standing view
Dashboards
One screen per level of the business. An executive and a campaign manager on the same team see different numbers.
- The exceptions
Alerts
A metric crosses the limit you set, and the owner hears the same day, by email, app or SMS.
- The follow-up question
Self-Service BI
The team that has the question builds the answer, with drag and drop, without raising a ticket.
Try it yourself
Start a free trial. See your first predictions in about 15 minutes.
Sign up and build your first model yourself, no setup call needed. Prefer a guided tour? Book a walkthrough instead.
One layer, three departments
The same player data, read by another team
Recognized by the industry.
FinalistCompliance Innovator of the YearVixio · 2024
NominatedCompliance Technology ProviderEGR North America · 2024
NominatedData and AI PartnerEGR B2B · 2022 · 2023
See what GAMWIT would have flagged on your players.
The AML and Responsible Gaming models are already built. Connecting your data takes 2 to 4 weeks.