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Cybersecurity · head to head

Feedzai vs Quantexa

Feedzai logo

Feedzai

Cybersecurity

Real-time transaction fraud and financial crime detection for banks and payment processors

From
On request
Rated
-
Full reviewWebsite
Quantexa logo

Quantexa

Cybersecurity

Entity resolution and network analytics for financial crime investigation

From
On request
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Feedzai pricing is per transaction with an annual minimum, so a bank with seasonal or growing volume commits to a floor it may not use and pays overage above the band.; Quantexa pricing is never published and lands in the seven figure range annually for a tier one deployment, so it is out of reach for mid-sized institutions no matter how well the analytics would fit.
  • They diverge on capability: Feedzai covers Real-time scoring, Quantexa covers Entity resolution.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Feedzai and Quantexa actually diverge.

Attributes where Feedzai and Quantexa differ
AttributeFeedzaiQuantexa

Identical on both: starting price (On request), pricing model (quote), free tier (No), platforms (Web, Linux), user rating (Not yet rated), category (Cybersecurity).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Feedzai

  • Real-time scoring
  • Rule and model hybrid
  • Case manager
  • Behavioural biometrics
  • Model explainability
  • Deployment options

Only in Quantexa

  • Entity resolution
  • Network generation
  • Contextual monitoring
  • Investigation workspace
  • Data fusion
  • Deployment on customer cloud

What people use each for

The jobs each tool is most often brought in to do.

Feedzai

  • A bank joining an instant payments scheme where transfers are irrevocable and post-hoc recovery is impossiblenot Quantexa
  • A card issuer whose existing rules engine cannot be changed without a release, so fraud waves run for daysnot Quantexa
  • An acquirer needing per-merchant risk models rather than one portfolio-wide modelnot Quantexa
  • A bank required by its regulator to explain automated declines to customers, which rules out opaque scoringnot Quantexa

Quantexa

  • A bank whose AML alert backlog is dominated by false positives and wants network context to close them fasternot Feedzai
  • Sanctions investigation where the sanctioned party is not the account holder but a connected director or shareholdernot Feedzai
  • Merging customer records across retail, commercial and wealth divisions after an acquisition to see total exposurenot Feedzai
  • A tax or benefits agency looking for organised fraud rings rather than individual claimantsnot Feedzai

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Feedzai

  • Pricing is per transaction with an annual minimum, so a bank with seasonal or growing volume commits to a floor it may not use and pays overage above the band.
  • It sits in the authorisation path, which makes every upgrade a change-controlled event with rollback plans, and the operational burden falls on the bank rather than the vendor.
  • Out of the box models need months of the customer own labelled fraud history before they beat the rules they replace, so the value case starts late.
  • AML and fraud are licensed as separate modules, so institutions expecting one platform fee find the transaction monitoring capability is a second line item.
  • The buyer profile is large institutions, so smaller banks and fintechs face minimums that make per-transaction economics unattractive below significant scale.

Quantexa

  • Pricing is never published and lands in the seven figure range annually for a tier one deployment, so it is out of reach for mid-sized institutions no matter how well the analytics would fit.
  • Output quality is bounded by input data quality, and organisations without governed customer data spend the first phase of the programme fixing feeds rather than catching criminals.
  • Implementation typically requires a systems integrator and runs into quarters rather than weeks, so the business case has to survive a long period with no operational benefit.
  • The platform augments rather than replaces existing transaction monitoring, so you keep paying for the incumbent system alongside it and total compliance technology spend rises before it falls.
  • Skills are scarce; the platform needs people who understand both Spark scale data engineering and financial crime typologies, and those people are hard to recruit and easy to lose.

Pricing, plan by plan

Feedzai

On request
  • Feedzai Financial Crime Platform$undefined/year
    • Priced by transaction volume with annual minimum commitment
    • Modules for fraud, AML and account opening licensed separately
    • Cloud, private cloud and on-premises deployment

Quantexa

On request
  • Quantexa Platform$undefined/year
    • Entity resolution and network generation
    • Deployed in customer cloud tenancy
    • Priced by data volume and use case count

Which should you pick?

Choose Feedzai if

  • You need real-time scoring.
  • You work on Web, Linux.
  • You also want rule and model hybrid.
Feedzai review

Choose Quantexa if

  • You need entity resolution.
  • You work on Web, Linux.
  • You also want network generation.
Quantexa review

Questions people ask

Is Feedzai or Quantexa better?
Neither clearly leads. Feedzai starts at On request and Quantexa at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Feedzai or Quantexa?
Feedzai starts at On request and Quantexa at On request.
Does Feedzai or Quantexa run on more platforms?
Both run on Web, Linux, so platform support will not decide this one for you.
What is Feedzai best used for?
Feedzai is most often used for a bank joining an instant payments scheme where transfers are irrevocable and post-hoc recovery is impossible, a card issuer whose existing rules engine cannot be changed without a release, so fraud waves run for days, an acquirer needing per-merchant risk models rather than one portfolio-wide model, a bank required by its regulator to explain automated declines to customers, which rules out opaque scoring. Of those, a bank joining an instant payments scheme where transfers are irrevocable and post-hoc recovery is impossible and a card issuer whose existing rules engine cannot be changed without a release, so fraud waves run for days are not what Quantexa is typically brought in for.
What can Feedzai do that Quantexa cannot?
Feedzai covers Real-time scoring, Rule and model hybrid, Case manager, Behavioural biometrics. Quantexa covers Entity resolution, Network generation, Contextual monitoring, Investigation workspace.

Answered from the vendors’ own pages

Feedzai: Can Feedzai run on-premises?

Yes. On-premises and private cloud deployments are supported, which is why it appears in markets where transaction data cannot legally leave the country.

Quantexa: Does Quantexa replace our transaction monitoring system?

No. It usually sits alongside it, adding network context to the alerts that system generates and to investigations.

Feedzai: Does it cover AML as well as fraud?

It does, but transaction monitoring is a separately licensed module. Assume two line items if you want both.

Quantexa: Where does our data go?

Into your own cloud tenancy in the normal deployment model. Quantexa does not require you to send customer data to a shared multi-tenant service.

Feedzai: How fast are decisions?

Designed for the authorisation window, typically tens of milliseconds. This is the constraint that rules out batch scoring architectures.

Quantexa: How is it priced?

Not publicly. Expect an annual subscription scaled by data volume and number of use cases, plus separate implementation cost.

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