Risk-based Authentication

Advanced fraud detection for mobile

Incognia changes the game for fraud detection on mobile. Requiring no additional action by users, Incognia works silently in the background, to identify anomalies in user behavior that indicate high risk logins and attempts at ATO and SIM Swap fraud.

Incognia location behavioral biometrics and device intelligence offer the strongest signals for risk-based authentication on mobile, improving recognition of trusted users, without adding friction to the user experience.

The results speak for themselves.

Case Study

Fintech reduces ATO on mobile wallet by 53%

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79%

of users seamlessly authenticated
53%

reduction in account takeovers
0.5%

false positive rate
2.6x

ROI

Enhancing risk-based authentication

Incognia location identity for mobile apps provides a new and highly effective defense against fraudsters. Using in-depth user location behavior and device intelligence Incognia offers enhanced risk assessment for mobile user logins. For low-risk logins, Incognia enables a friction-free login experience. For high-risk, additional authentication steps can be required of users.

Prevent Account Takeover
Incognia checks user’s real-time location with user location behavior history and delivers a risk score.
- Detect discrepancies in user behavior
- Recognize trusted customers
- Detect fraudsters
- Reduce account takeover rate
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Continuous Address Verification
Incognia detects changes in behavior indicating changes in home address and delivers fraud risk alert
- Detect changes in user location behavior
- Detect changes in home location
- Trigger user re-authentication
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Detect Device spoofing, SIM swap
Incognia detects emulated, spoofed and fraudulent devices
- Detect changes in user location behavior
- Recognize devices with bad reputation
- Detect fraud farms
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Designed for developers

Fast SDK integration & easy-to-use APIs

We provide a lightweight mobile SDK and intuitive APIs to make it easy for you to add location and device intelligence to risk assessments throughout the user journey.