Frictionless Mobile Payments
Fraud Detection

Paygilant observes bio markers to 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, and more.

Paygilant’s robust bio markers are just one of the several intelligence sets that make up the broader solution and is designed to augment the fraud/no-fraud decision that precedes any step-up authentication request.

Various attributes observed on the device can contribute to the detection of fraudulent behavior and to the derivation of a device ID. The Paygilant engine generates unique device identifiers using proprietary algorithms going beyond standard parameters and taking the accuracy of fingerprinting to the next level. Our methodology utilizes machine learning models to match the device ID and the user’s identity.

Intelligent, privacy preserving analysis of user data on the mobile device provides valuable insights into fraudulent activities. User data analysis is especially helpful in hard-to-analyze scenarios like new account origination, where there is no established history for the user/account. User data provides a snapshot of the mobile device environment, to distinguish a legitime user from a fraudster.

Paygilant employs propriety transaction behavioral maps. The behavioral maps represent the purchasing patterns/spending habits of a specific customer and are created using

Paygilant’s proprietary machine learning algorithms. Paygilant utilizes its depth of field (DOF) technology to create a multi-dimensional in-depth behavioral profile that provides a clear, high resolution picture of the different risk zones and is a key factor in determining the risk of a specific transaction.

The intelligence sets described above – transaction data, app interactions, bio markers, device attributes, user data and device ID – are the key to Paygilant’s distinctive ability to detect mobile fraud. While other vendors use a single layer to determine fraud, Paygilant weave of all six intelligence sets provides unmatched viability to the legitimacy of the transaction. At various stages of the users’ journey, Paygilant’s six intelligence sets operate as fraud-indicator building blocks providing insight immediately, once a user has downloaded the app.