iGaming B2B
Headquarters
Cyprus

Frogo is a B2B SaaS company that provides AI-driven fraud detection and risk management specifically for the iGaming, sports betting, and online gaming sectors. Headquartered in Cyprus, the company offers an all-in-one platform combining machine learning, dynamic risk scoring, and real-time alerting to combat bonus abuse, account takeover, affiliate fraud, payment fraud, and multi-accounting. Frogo was named 'Anti-Fraud Solution of the Year' at a major industry awards ceremony and has rapidly gained recognition among licensed operators. The platform is built on deep domain expertise in gaming fraud and is also adaptable for adjacent verticals like e-commerce, banking, and Forex trading. By blending automated AI detection with human analyst oversight, Frogo helps operators turn potential fraud losses into profit while reducing operational overhead and improving compliance.

Detailed Review

Business Model

Frogo operates as a B2B SaaS provider, selling a modular suite of fraud detection tools that can be deployed individually or as a full stack. Its core value proposition is converting potential fraud losses into profit by stopping attacks in real time. Revenue is generated through subscription-based licensing, typically tied to transaction volume or platform usage, though exact pricing is not publicly disclosed.

History and Founding

Frogo was founded in Cyprus, likely around 2021–2022 based on its earliest industry mentions in 2024–2025. The company quickly established itself as a specialist in iGaming fraud, participating in events like SiGMA and building a client base among regulated operators. No public funding rounds or investor details have been announced, indicating either bootstrapped growth or private backing.

Products and Platform

Frogo’s main offering is the Frogo AI Fraud Detection Platform, which includes modules for gaming fraud analytics (betting pattern analysis), account takeover prevention (behavioral login analysis), bonus abuse detection (promo code duplication and multi-accounting), affiliate fraud prevention (CPA/RevShare cheating), payment fraud (chargebacks, BIN attacks), SMS fraud (fake registrations driving up costs), internal fraud (employee log anomalies), and a custom case builder. The core technology is a dynamic risk scoring engine that adapts to new fraud patterns through machine learning and human feedback.

Market Position and Competition

Frogo competes with legacy rule-based fraud systems and other AI-driven platforms in the iGaming space. It differentiates through deep domain expertise, hybrid human-AI detection, and seamless integration with existing workflows. The platform is certifications-ready for regulated markets and supports real-time APIs for low-latency environments. The company has not publicly identified specific competitors but positions itself as a cost-effective alternative to building in-house fraud teams.

Recognition and Growth

Frogo has been recognized in industry awards, winning 'Anti-Fraud Solution of the Year' at a major ceremony. It maintains an active presence at trade shows and publishes interviews and thought leadership content. While exact customer counts are undisclosed, its expanding client base among licensed operators indicates steady growth. The company is headquartered in Cyprus, a hub for iGaming technology firms, and likely employs a small to mid-sized team, though headcount is not publicly available.

Key Products

  • Frogo AI Fraud Detection Platform

    All-in-one suite covering gaming fraud, account takeover, bonus abuse, affiliate fraud, payment fraud, SMS fraud, multi-accounting, internal fraud, and custom cases. Uses AI risk scoring and real-time alerts.

  • Dynamic Risk Scoring Engine

    Core machine learning model that assigns risk scores to user actions and transactions, adapting to new fraud patterns.

  • Real-Time Alerting System

    Provides immediate notifications to fraud teams when suspicious activity is detected.

  • Custom Case Builder

    Allows operators to define their own fraud detection rules and use cases specific to their business logic.

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