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Stripe launches antifraud AI tool

Thursday 19 April 2018 14:30 CET | News

Stripe has launched Radar for Fraud Teams, an expansion of its free AI-based Radar service that runs alongside Stripe’s core payments API to help identify and block fraudulent transactions.

The company plans to launch a private beta of a “dynamic authentication” that will bring in two-factor authentication. This is on top of Stripe’s first forays into using biometric factors in payments, made via partners like Apple and Google.

The new paid product comes alongside an update to the core, free product that Stripe is dubbing Radar 2.0. New features for the whole product (free and paid) will include being able to detect when a proxy VPN is being used (which fraudsters might use to appear like they are in one country when they are actually in another) and ingesting billions of data points to train its model, which is now being updated on a daily basis automatically.

The chief advantage of taking this product will be that teams will be able to customise how Radar works with their own transactions. This will include a more complete set of data for teams that review transactions, and a more granular set of tools to determine where and when sales are reviewed, for example based on usage patterns or the size of the transaction.

Users of Radar for Fraud Teams will be able to now use Radar to help with their overall management of how it handles fraud. This will include being able to keep lists of attributes, names and numbers that are scrutinised, and to check against them with analytics also created by Stripe to help identify trending issues, and to plan anti-fraud activities going forward

Also, teams will be able to determine the value at which a transaction needs to be flagged. This is the online equivalent of when certain purchases require or waive one to enter a PIN or provide a signature to seal the deal.


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Keywords: Stripe, artificial intelligence, fraud prevention, RADAR, authentication
Categories: Fraud & Financial Crime
Companies:
Countries: World
This article is part of category

Fraud & Financial Crime