Incognia Becomes the Most Downloaded Fraud Prevention SDK in Europe
Growth reflects broader shift among European businesses toward privacy-first technologies that deliver fraud detection without requiring direct identifiers
As companies face growing pressure to collect less personal data, they are seeking solutions that meet these requirements while maintaining strong fraud detection performance. Incognia's approach addresses both by identifying trusted users and flagging suspicious behavior based on device signals, network context, and location behavior patterns, without requiring direct identifiers such as name, email, phone number, or government ID.
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Unlike traditional identity-based fraud systems that rely on direct identifiers (PII) to verify "who" a user is, Incognia evaluates whether an interaction is consistent with a device's typical behavior and location context without trying to establish a person's real-world identity. Incognia is designed around data minimization: it doesn't require direct identification data such as name, email, or government ID. Incognia focuses on signals that function as indirect identifiers, with technical controls that reduce identifiability.
"Every additional piece of personal data creates more regulatory burden, increases security exposure, and raises operational risk," added Ferraz. "European companies are leaning into GDPR-driven data minimization and rethinking whether collecting direct identifiers is necessary for trust. Incognia was designed from day one to help businesses prevent fraud without requiring direct identification data like name or email."
Incognia supports companies across financial services, marketplaces, food delivery, mobility, and digital commerce, helping prevent account takeover, fake account creation, mule account handovers, authorized push payments (APP), bonus abuse, and other forms of large-scale fraud while reducing friction for legitimate users.
Incognia is attending Money20/20
About Incognia
Incognia provides cross-device risk intelligence for companies that rely on trusted digital interactions. Its technology blends location behavior, device integrity, and behavioral analysis to create a risk signal that cannot be faked at scale and shows whether a user is trusted or risky. With real-time assessments and actionable data, Incognia helps organizations stop repeat and large-scale fraud while reducing friction for legitimate users.
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SOURCE Incognia
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