Feedzai
Machine learning for financial crime — fraud and risk scoring at the scale large banks and processors run at.
Highlights
- End-to-End Protection: Comprehensive protection from fraud and financial crime across all channels.
- Dynamic Customer Risk Profiling: Evolving risk profiles from onboarding through ongoing activity.
- Watchlist Screening: Automated screening using the latest global watchlists.
- AML Transaction Monitoring: Detect complex money laundering typologies and visualize hidden transaction relationships.
- Digital Trust: Detect user anomalies and protect against credential theft and impersonation.
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About Feedzai
What it is
Feedzai provides machine learning for financial risk: scoring transactions, account openings and payments for fraud and money laundering in real time, across the volumes the world's largest banks, merchants and payment processors handle. Its RiskOps platform covers detection, case management and the investigation workflow around them.
Why it's different
Fraud detection is one of the oldest genuinely successful applications of machine learning, and the difficulty is not the model but the constraints around it: a decision in milliseconds, at enormous volume, where a false positive declines a real customer's card and a false negative is a loss. Feedzai operates at that tier, which is the argument for it and also the reason it is irrelevant to most readers — this is sold to institutions, priced accordingly, and implemented over months. Worth noting too that fraud models make consequential automated decisions about individuals, which brings explainability and fairness obligations that are increasingly regulatory rather than optional.
How people use it
It is used by banks, acquirers and large merchants for transaction fraud, account takeover and anti-money-laundering screening. The part institutions care most about in practice is the balance between catch rate and false positives, because declining good customers is a measurable revenue loss that competes directly with fraud reduction. Case management matters as much as detection, since a flagged transaction still ends up with a human.
Written by the n3os team. We are not affiliated with Feedzai.
This listing was written from public information, without Feedzai’s involvement. If you own it and something here is wrong — or you would rather not be listed at all — email us and we will correct or remove it.
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