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10/06/2026 10:42 pm
TL;DR: AI is increasingly used to predict fraud before it occurs, alongside market expansion, tighter regulation, and cryptocurrency adoption in the sector, according to SumSub’s iGaming podcast episode. The governance shift is bigger than fraud detection because it changes how identity, trust, and intervention are decided in real time.
NHIMG editorial — based on content published by SumSub: What The Fraud? episode on AI, regulation, and iGaming fraud prevention
Questions worth separating out
Q: How should iGaming teams use predictive fraud scoring without creating excessive customer friction?
A: Use predictive scoring to trigger graduated checks rather than automatic denial wherever possible.
Q: Why does cryptocurrency change fraud governance in iGaming?
A: Crypto changes the speed and finality of value movement, which reduces the time available to detect abuse and intervene.
Q: What do security teams get wrong about fraud prevention in iGaming?
A: Teams often treat fraud prevention as a detection problem when it is also a governance problem.
Practitioner guidance
- Map fraud interventions to explicit identity triggers Define which behavioural signals can trigger step-up verification, account hold, or manual review before the next transaction or withdrawal is completed.
- Separate transaction risk from login risk Extend monitoring beyond authentication success to include device changes, payout velocity, account linkage, and abnormal transfer behaviour.
- Document escalation ownership for disputed decisions Assign clear owners for overrides, appeals, and evidence review so fraud actions remain defensible under regulatory scrutiny.
What's in the full article
SumSub's full podcast episode covers the operational discussion this post intentionally leaves at the strategy level:
- The guest's applied perspective on how AI changes fraud mitigation before a user completes an action
- Discussion of market growth and regulatory pressure shaping iGaming control design
- Practical commentary on cryptocurrency-related fraud patterns and response choices
- Actionable advice for businesses and individuals on staying protected against fraud
👉 Read SumSub's podcast discussion on AI fraud prediction and iGaming risk →
AI fraud prediction in iGaming is reshaping fraud controls?
Explore further
11/06/2026 2:50 am
Predictive fraud controls are becoming identity controls. When a model is allowed to act before a fraud event occurs, the governance problem is no longer only detection quality. The programme now decides who is trusted, when, and under what evidence threshold, which puts identity assurance and fraud operations on the same control plane. Practitioners should treat these systems as policy-enforcing identity decision engines, not just analytics tools.
A few things that frame the scale:
- The average estimated time to remediate a leaked secret is 27 days, despite 75% of organisations expressing strong confidence in their secrets management capabilities, according to The State of Secrets in AppSec.
- Only 44% of developers are reported to follow security best practices for secrets management, exposing a significant developer behaviour gap.
A question worth separating out:
Q: Who should be accountable when an AI model blocks or allows a risky iGaming action?
A: Accountability should sit with the business and security owners who define the policy, not with the model itself. The model can recommend or trigger actions, but humans must own thresholds, review standards, and exception handling so decisions remain defensible under compliance review.
👉 Read our full editorial: AI fraud prediction in iGaming is reshaping identity controls
