Mangopay has announced the launch of its new Fraud Prevention solution. Mangopay’s Fraud Prevention solution provides a fully integrated and payment processor-agnostic AI-driven cybersecurity solution to guard against an evolving range of threats. These threats include account takeover by both bots and humans, reseller fraud, payment fraud, chargebacks, and return abuse.

The customisable product offers enhanced protection for platforms to defend themselves from existing and emerging threats, including real-time fraud detection, darknet insights and device fingerprinting. Platforms can connect to the solution through the Mangopay product ecosystem, meaning they can easily protect themselves against fraud without any additional integration.

Platforms can also connect their existing payment processors through a seamless, easy-to-integrate API

Mangopay’s Fraud Prevention solution leverages an experienced and trusted fraud detection engine based on original Nethone technology, the fraud detection and prevention specialist Mangopay acquired last year. It benefits from years of first-hand darknet insights to help guard platforms against techniques and patterns used by the most advanced fraudsters.

Every transaction is screened using signals and trained on billions of data sets from across Mangopay’s vast merchant network, protecting platforms from similar attempted attacks. Via a user-friendly interface, clients remain in full control, with complete visibility of fraud prevention recommendations and actions, with the ability to add their own rules for greater protection.

Mangopay’s solution has been created to safeguard e-commerce, marketplace and fintech platforms while minimising friction for legitimate end users. Platforms can access real-time notifications on transaction recommendations and sort fraud inquiries to get granular data on transactional outcomes.

They can also leverage machine learning to analyse fraudulent techniques and suspicious user behaviour and benefit from device fingerprinting techniques to identify and track devices used at the checkout to help confirm end-customer identity.

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