Frogo’s Platform Protects Margin Without Harming Real Players Booth 1G30 Frogo
Frogo's platform analyses player behaviour patterns, Device Fingerprints, and multi-accounting, builds graph connections between accounts and devices, and applies AI models that reduce undetected fraud without increasing False Positives.
From $21 to $1,095+ is what a single missed fraud case can cost in iGaming. Tis is how it usually unfolds. An account passes registration and bonus checks without raising any red flags. It makes a deposit, receives a welcome offer, and starts playing like a normal user. No alerts, nothing suspicious. A few days later, similar accounts appear. Teir behaviour follows the same patterns, the same logic, often even the same devices. Tey also pass all checks, receive bonuses, and continue playing as usual.
Te system treats them as legitimate users. Bonuses are spent. Deposits made with stolen cards are not recovered. Support processes tickets, but sees no clear signs of fraud. Reports remain clean - no chargebacks, no system errors. Weeks later, the team starts to notice a drop in margin. ROI falls below expectations, LTV no longer aligns, and the bonus economy begins to leak. By that point, the source of the problem is no longer obvious, because fraud looked like normal activity all along. Tis is a False Negative (FN) — at scale.
Tat’s how a loss in the range from $21 to $1,095+ per missed case is formed. It’s not a single event, but a chain of them: stolen deposits, bonuses and promotions that immediately go into the red, operational costs for manual reviews and support, and - most importantly - lost
margin and distorted ROI and LTV metrics. Te key issue is that undetected fraud is rarely an isolated incident. If one account gets through, others will follow. Two. Ten. Fifty or more. All without alerts or chargebacks showing up in reports. Losses accumulate quietly, but consistently.
Tis is why missed fraud often hits the business harder than chargebacks. A chargeback is a fixed and visible loss - unpleasant, but predictable. Fraud that slips through detection, on the other hand, simultaneously damages promo economics, payments, bonus strategy, and traffic quality analytics. It doesn’t look like an error until it turns into a systemic problem.
In this environment, anti-fraud is no longer about rigid rules or mass blocking. Te real task is to protect margin without harming real players. Tis is the logic behind Frogo. Te platform analyses player behaviour patterns, Device Fingerprints, and multi-accounting, builds graph connections between accounts and devices, and applies AI models that reduce undetected fraud without increasing False Positives. Everything works in real time and adapts to each brand, GEO, and traffic type.
Traffic is becoming more complex. Fraud is getting quieter and more systematic. And when these hidden losses are not under control, the business pays for them every day - directly from margin.
If FN is relevant for you, meet the Frogo team offline at ICE Barcelona January 19-21, Booth 1G30.
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