attributes

Device Attributes Various attributes observed on the device can contribute to the detection of fraudulent behavior and to the derivation of a device ID. Device model, screen, memory, UUID, OS, IP, geolocation, app permissions, and more are observed. Geolocation is...

transaction

Transaction Data Paygilant employs propriety transaction behavioral maps. The Behavioral Maps represent the purchasing patterns/behavior of a specific customer and her nearest neighbors and are created using Paygilant’s proprietary machine learning algorithms....

dna

Device DNA Various attributes observed on the device can contribute to the detection of fraudulent behavior and to the derivation of a device ID. Device model, screen, memory, UUID, OS, IP, geolocation, app permissions, and more are observed. Geolocation is probably...

bio

Bio Markers Paygilant observes bio markers to passively identify the user behind the transaction. Common bio markers Paygilant observes include touch time, time between touches, size of touch inputs, finger velocity, scrolling pace and drag length, typing biometrics,...

app

App Interactions Paygilant looks at how the user interacts with the mobile application to determine if the interactions are consistent with a legitimate user. For example, if a user navigates directly to a high-ticket item and immediately proceeds to check-out, then...