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Best AI to prevent fraud

Identify and block fraudulent accounts, applications, claims, or transactions. We reviewed 11 products from 8 companies on a 100-point evidence score. These 7 earned a place.

Updated Oct 20, 202611 products reviewed8 companies

Market noteScores reflect documented task fit, adoption evidence, product detail, pricing and market fit. Vendor claims remain unverified unless independently corroborated. Missing evidence indicates uncertainty, not poor product quality.

  1. 1

    Payment Protection

    by Sift

    Identifies fraudulent transactions and automates payment reviews into order decisions. Named Banxa and Paula’s Choice cases describe concrete product use, supporting adoption under the supplied provenance contract.

    Best for digital businesses automating payment-fraud screening and order decisions

    Task fit
    40/40
    Adoption
    10/20
    Evidence
    11/15
    Pricing
    0/15
    Market fit
    10/10
  2. 2

    Radar

    by Stripe

    Explicit machine-learning fraud prevention establishes direct task fit. Named Classy and Substack cases describe actual Radar use, qualifying for adoption credit under the supplied contract. Pricing specifies $0.08 per screened transaction but lacks full terms.

    Best for businesses seeking machine-learning fraud prevention for payment transactionsFrom $0.08

    Task fit
    30/40
    Adoption
    10/20
    Evidence
    8/15
    Pricing
    11/15
    Market fit
    8/10
  3. 3

    Pindrop® Protect

    by Pindrop

    Protect supplies per-call fraud scores across IVR and agent stages. Named customer cases describe actual fraud-detection use and prevention controls across financial and healthcare organizations, supporting business applicability and adoption without independently verifying reported outcomes.

    Best for business contact centers identifying suspicious callers and supporting fraud-prevention decisions

    Task fit
    30/40
    Adoption
    10/20
    Evidence
    11/15
    Pricing
    0/15
    Market fit
    10/10
  4. 4

    Liveness

    by Veriff

    AI-based facial analysis explicitly prevents spoofs and deepfakes from selfie submissions, supporting a defined fraud-prevention action for business onboarding.

    Best for businesses preventing selfie spoofs and deepfake impersonation during onboardingFree planFrom $0.80

    Task fit
    30/40
    Adoption
    5/20
    Evidence
    8/15
    Pricing
    11/15
    Market fit
    8/10
  5. 5

    Fraud Detection Suite

    by Checkr

    The AI suite explicitly detects hiring fraud and uses an internal blocklist to stop fraudulent candidates. Concrete capabilities and business use cases establish eligibility, but detailed input-to-decision workflows are not documented. Adoption credit is limited to company-scale proxies and supplied customer references.

    Best for businesses screening candidates for identity, résumé, and credential fraudFree plan

    Task fit
    30/40
    Adoption
    5/20
    Evidence
    8/15
    Pricing
    8/15
    Market fit
    8/10
  6. 6

    GeeTest Business Rule Engine

    by GeeTest

    Machine learning and rule-based real-time decisioning explicitly support several fraud-prevention actions for businesses. Concrete capabilities establish fit, while company-level customer references provide only limited adoption evidence for this product.

    Best for businesses seeking real-time decisioning for payment fraud, account takeover, and credential-stuffing preventionFree trial

    Task fit
    30/40
    Adoption
    5/20
    Evidence
    8/15
    Pricing
    8/15
    Market fit
    8/10
  7. 7

    Cequence Platform

    by Cequence Security, Inc.

    Behavioral intelligence and explicit fraud-prevention capabilities support business task fit. The attributable Hibbett case documents actual platform use, supporting adoption evidence without independently proving effectiveness.

    Best for businesses preventing bot-driven fraud and business-logic abuse across applications and APIs

    Task fit
    30/40
    Adoption
    10/20
    Evidence
    8/15
    Pricing
    0/15
    Market fit
    8/10

We reviewed 11 candidate products from 8 companies and published 7 positions. Totals include duplicate company entries and products removed during task, market and evidence review. Each company holds at most one position.