What_We_Do

ONE SINGLE RISK PLATFORM
FOR END-TO-END FRAUD PREVENTION

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Whether you are a bank, acquirer, merchant or any player in the commerce value chain, Feedzai is all you need to manage your entire payment risk. Online or offline, card or non-card, Feedzai offers an Any Data. Any Payment.™ risk engine that helps prevent fraud using machine learning.

Unblock Payment and Keep Commerce Moving

Resources

Webinar
Combating Account Opening Fraud using Machine Learning

Watch the Webinar

Watch Aite’s Julie Conroy and Feedzai’s Phong Q.Rock discuss how FIs can apply advanced analytics to the vast amount data at their disposal and turn it into intelligence,which can help to not only reduce fraud,but also remove friction.

Why orchestration of authentication is antidote to account takeover fraud?

Ebook
Choosing a Machine Learning Platform for Risk(Banking)

Get the Ebook

A Guide for Banks and Payment Processors

Download this report to peek into the future of fraud.Learn more about:
1)Explainable Whitebox AI
2)Precise segment-of-one profiling
3)Future-proof data ingestion and
4)Better enterprise fraud protection

aml

Ebook
Beyond AML Compliance – A guide for financial institutions

Get the Ebook

AML compliance costs the industry too much. Machine learning will reduce your exposure.

Learn from our research team and find out how you can take back control of your AML compliance efforts.

The Future is Feedzai

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We’ve built a powerful platform with foresight into next-generation fraud technology that gives real utility to data feeds that come from new and unexpected sources. Feedzai is looking at commerce transactions as an ecosystem model, and we’re disrupting the conventional thinking about risk and pioneering a new approach to risk management.

Ready to clean up your commerce stream?
Schedule a demo with us today.

Our Partners

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Schedule a Demo

With the ground truth of actual chargebacks and other fraudulent behavior as the benchmark, a head-to-head comparison of Feedzai’s detection performance using past transaction logs can demonstrate the value of our machine learning approach.