Incognia is an AI-driven device and browser fingerprinting platform for financial services, including banks and fintechs. It uses a model-based approach to device recognition combined with location-based behavioral biometrics to detect and prevent fraud. Core functionality includes recognizing returning users with high accuracy by building a stable, adaptive device fingerprint that evolves with the user population. Risk assessments are generated based on whether a device's current location matches a known address or established location behavior pattern associated with the account. High-risk signals include GPS spoofing, device rooting, emulator use, app tampering, and location spoofing. Low-risk signals confirm device recognition and trusted location patterns. The platform supports continuous background authentication, meaning it operates without requiring active user interaction at the point of login or transaction. Key use cases include: - Account takeover (ATO) prevention - Fake account creation reduction - Frictionless user authentication (reducing reliance on SMS/email OTP and facial biometrics) - Identity fraud prevention - Secure mobile transaction verification The platform is positioned as an alternative to static, cookie- or PII-dependent device fingerprinting approaches. It focuses on privacy-preserving signals and adapts to browser and OS privacy changes. Incognia claims a 99.9% user recognition accuracy, a 0.0013% false positive rate, and performance metrics including 22.4M ATO attacks prevented in 2023, 95% reduction in fake account creation, and 80% reduction in SMS/email OTP usage.