Fraud Detection
Know the bad actor before the bonus does.
Fraud Detection scores players, payments, and play in real time — bonus abuse, multi-accounting, collusion, chargebacks, and account takeover — and puts every decision in front of an analyst with the reason attached. Legitimate players never notice it. The others meet it at the door.
What it does
iGaming fraud is industrialised. Bonus terms are arbitraged by networks of accounts opened from the same device farm. Poker tables are worked by colluding players sharing hole cards on a side channel. Stolen cards are cycled through deposits and cashed out before the chargeback lands. Accounts with real balances are taken over with credentials bought in bulk. Each scheme is individually small and collectively one of the largest costs an operator carries — and the usual defence, blunt rules that decline anything unusual, turns away the good players along with the bad.
Fraud Detection replaces the blunt rules with scoring. Every registration, login, deposit, wager, and withdrawal is evaluated in milliseconds against device, behaviour, network, and payment signals, and against the patterns that connect accounts to each other. Low-risk actions pass without friction. High-risk actions are held, stepped up, or declined, and each one lands in a case queue with the evidence laid out. Analysts spend their time on decisions, not on discovering the fraud in a spreadsheet after the money has gone.
Capabilities
Device and behavioural fingerprinting
Devices, browsers, networks, and interaction patterns are profiled so the same actor is recognised across accounts, sessions, and IP changes without relying on cookies or self-declared identity.
Multi-account and collusion detection
Graph analysis links accounts through shared devices, payment instruments, addresses, and play patterns. Coordinated play at the same tables or against the same promotions is surfaced as a network, not as isolated flags.
Bonus-abuse and arbitrage patterns
Wagering behaviour is compared against the mathematics of each promotion so risk-free arbitrage, minimum-wager churn, and cross-account bonus farming are caught before the bonus converts to cash.
Payment risk and chargeback prediction
Deposits and withdrawals are scored against card, wallet, velocity, and geography signals, with chargeback likelihood estimated at deposit time — when a hold still costs nothing.
Account takeover and session anomalies
Logins and in-session behaviour that break a player's own pattern — new device, impossible travel, changed betting style, rapid withdrawal to a new destination — trigger step-up verification before funds move.
Case management for analysts
Every held or declined action opens a case with the signals, the linked accounts, and the timeline in one view. Analysts approve, decline, or escalate, and their decisions feed back into the models.
Frameworks we work against
Detection is designed to satisfy the payment, anti-money-laundering, and data-protection obligations operators carry in every regulated market.
- PSD2 / Strong Customer Authentication
- Risk-based step-up that meets European payment authentication requirements without adding friction to every transaction.
- PCI DSS
- Card data is handled inside a compliant boundary, with fraud scoring operating on tokens rather than raw card numbers.
- EU Anti-Money Laundering Directives
- Transaction monitoring, suspicious-activity flagging, and record-keeping aligned with AMLD5 and AMLD6 obligations.
- FATF Recommendations
- The international standard behind risk-based customer due diligence and monitoring that the scoring model is structured around.
- ISO/IEC 27001
- Information security controls for a system that holds device, payment, and behavioural data on every player.
- GDPR
- Profiling with a documented lawful basis, data minimisation, and the ability to explain any automated decision to the player it affected.
Why operators choose it
— Scores in milliseconds, decisions in context
The score arrives before the page finishes loading, but it never stands alone. Every decision carries the signals that produced it, so a hold can be understood and, if needed, reversed.
— Fewer false declines, fewer real losses
Blunt rules block good players and miss coordinated bad ones. Scoring against behaviour and networks does the opposite — conversion goes up while fraud losses and chargeback ratios go down.
— Every block has a reason an analyst can read
No black-box declines. Support can explain to a player why a withdrawal was held, compliance can show a regulator why an account was closed, and the model learns from every override.
Part of the iGaming suite
Games
Certified game engines, RNG, and content integration.
Crypto Payment API
Deposits and payouts across chains, one integration.
KYC
Identity verification that clears players in minutes.
Game Licensing
Regulatory approvals and certification across markets.
Player Account Management (PAM)
Wallets, sessions, limits, and bonuses in one player hub.
Run it against last quarter's chargebacks.
Give us an anonymised export of recent transactions and known fraud outcomes. We will show you what would have been caught, what would have passed, and where the false declines were.