What lies beneath a highly precise fraud risk assessment?
Learn how location behavior and device intelligence power Incognia's risk assessment model
Smartphones today are powerful computing devices with a number of sensors that generate valuable behavioral and device recognition signals that are extremely useful for mobile authentication and fraud prevention. However, most traditional fraud prevention solutions are not maximizing the value of these signals. For example, fraud prevention solutions based solely on GPS, are now routinely spoofed by fraudsters using off-the-shelf GPS spoofing tools.
Incognia’s mobile-native fraud prevention solution based on advanced location technology leverages today’s smartphone device sensors to deliver highly precise fraud risk assessments. Recently, Incognia released an ebook to explain how each risk score is built from evidence-based on location and device intelligence, and how this approach goes far beyond relying solely on GPS.
Whenever a user tries to log in or perform a sensitive transaction via a mobile app using Incognia, from a new or existing device, Incognia provides a fraud risk assessment through the Incognia APIs, together with supporting evidence.
Incognia’s fraud risk assessment combines evidence from the following:
- Location behavior
- Location sensors
- Device reputation
- Device integrity
- Address verification
and other key elements to accurately differentiate legitimate users and fraudsters. And when we say that the supporting evidence leverages device intelligence, included in the analysis of detailed device data, to determine if any of the following conditions are present to indicate increased risk such as:
- Compromised software configuration
- Presence of VPNs, proxies, GPS spoofing apps
- Use of root or jailbreak
- Use of mobile emulators
- App installation from unofficial app stores.
In addition to the major role of location and device intelligence evidence in delivering a highly precise risk assessment, there is also a strong role played by the Incognia network effect. With data gathered from over 150 million devices with Incognia deployed, this network effect enables Incognia to provide an accurate risk signal with extremely low false-positive rates. Incognia maintains an up-to-date watchlist that indicates when devices or users have been associated with previous fraudulent events based on feedback from customers. In combination, the location and device intelligence and watchlists enable Incognia to deliver highly accurate actionable intelligence that can be used either as standalone fraud detection or integrated into any risk engine or IAM flow.
Interested in learning more about how Incognia delivers superior account security through its unique fraud risk assessments?
Download the latest ebook in our How-To Series: Understanding Incognia’s Risk-Assessments and Evidence.