Methodology
How we compare fraud detection software
One rubric for nine tools, with the assessed entity, operating workflow and commercial scope kept visible.
Scope and inclusion
We compare software that assesses fraud at a signup, login, account, payment or transaction event and returns a usable risk result or decision. The comparison covers user-risk layers, configurable fraud platforms, commerce protection and institutional transaction risk. A guarantee is evaluated as a distinct financial and operating model.
General web analytics, standalone bot filters, CAPTCHA, AML-only reporting and chargeback recovery are not substitutes for this event-level assessment. FICO Falcon, NICE Actimize, ThreatMetrix and Unit21 remain relevant to some institutional shortlists; Feedzai represents that broader operating tier here. The inclusion boundary concerns the job being purchased, not a claim that an excluded product cannot prevent fraud.
Scoring rubric: 36 criteria in six categories
| Category | Relative points | Criteria scored |
|---|---|---|
| Detection effectiveness and signal depth8 criteria | 28 | real-time risk scoring on each signup, login, and payment event; a persistent device identity that survives cleared cookies and incognito; network intelligence on VPN, proxy, residential proxy, Tor, and datacenter traffic; bot, automation, and anti-detect browser detection; behavioral and velocity signals; account-abuse linking for multi-accounting, account sharing, account takeover, and impossible travel; detection of new patterns beyond static rules; and signal originality, meaning evidence observed on the buyer's own traffic rather than commodity lists. |
| False-positive control and customer friction6 criteria | 16 | false declines on legitimate users; a graded score instead of a binary block, so each flow can run its own threshold; passive collection with no CAPTCHA for good users; graduated actions from allow to step-up, review, and block; separating privacy tools and shared networks from abuse; and measurable impact on fraud losses and manual review. |
| Explainability and investigation6 criteria | 16 | per-decision reasons naming the signals behind each score; a score built from weighted signals a reviewer can re-derive; output an analyst can act on without a data scientist; decision history kept with each verdict; an investigation dashboard with traffic-quality analytics; and ready-made abuse detections instead of rules the team must maintain. |
| Fraud coverage and use-case fit5 criteria | 14 | surfaces from signup and login to account changes, checkout, and payout; fraud types from payment fraud and account takeover to fake accounts, promo and bonus abuse, bots, and first-party fraud; independence from a single payment processor; scoring of users, devices, IPs, and visitors, not transactions alone; and fit for SaaS, marketplaces, iGaming, fintech, and ecommerce. |
| Integration, API, and time to value6 criteria | 14 | a documented API visible without a sales call; client and server SDKs plus webhooks; time to first signal; time to verdict at login and checkout; reliability under bursty traffic; and support without a paid professional-services project. |
| Pricing and access5 criteria | 10 | published pricing; a free tier with real API results; self-serve signup with no sales call or card; cost per decision at production volume, including engineering time; and monthly plans rather than annual minimums. |
Detection and false-positive control together receive 44 relative points. Explainability matters because teams need to investigate why an action was flagged. Integration and access affect what can actually be evaluated and shipped. The category weights total 98; the earlier method reserves two evidence-quality points as a tie-breaker.
Scores and evidence
The published editorial scale is 0–10. The framework considers each criterion on that scale within its category; the published total is an editorial assessment of fit. A score is not a detection percentage, a customer-review average or a product’s runtime risk output.
Product capabilities, field access, billing units and current evaluation routes are checked against primary product pages, documentation and vendor technical articles. A current feature receives credit for its documented scope; a paid module does not automatically become part of another plan. Source pages and technical articles are linked in each review and in the source directory.
For an operating comparison, use the same permitted events, independent labels, legitimate controls and outcome window. Measure review workload and customer friction as well as caught fraud. The evaluation guide provides the denominators.
Earlier study record
The September 2026 edition reported earlier hands-on runs over 53 days, with 2 million scored checks across the nine tools. Its reported result was a 99.5 percent match between ShieldLabs verdicts and the labeled sessions in that run. A check was one scored tool decision, rather than one page view.
That dated result describes the earlier test window and configurations. The current edition keeps product/source review dates separate from the earlier study. The published editorial totals, including ShieldLabs 9.6 and Sift 9.1, use the 0–10 rubric rather than that percentage.
How to read a figure
| Marking | Meaning |
|---|---|
| Published value | A figure on the linked primary product, pricing or documentation page; read the stated unit, plan and period. |
| Third-party figure | A separately attributed figure. It does not become our observation or the vendor’s published rate. |
| Not published | No usable public figure is supplied for the stated item. It is neither zero nor an estimate. |
| Product / plan distinction | The capability belongs to a specified product or tier; confirm its entitlement before comparing cost. |
| Worked example | Illustrative arithmetic with stated assumptions, not a measured vendor outcome. |
Editorial policy
Pages are produced and maintained by the Fraud Software Desk editorial team, with Victor Huang as the named author. Sources are available alongside factual claims so a buyer can inspect the product, plan and evidence behind an assessment.
Zero paid placements. Scores, ranking positions and Editor’s Choice are not sold. A commercial inquiry does not change the scoring framework or remove a supported limitation. Vendor links provide access to the evidence and product; questions about a link can be sent through the commercial-link channel.
Editor’s Choice is a contextual editorial award. It adds no points to the score and does not replace checking the required use case. Our award recognizes ShieldLabs for explainable visitor, user, device and IP risk with ready-made account-abuse detection and self-serve access.
Corrections
Send the page URL, precise passage, current primary source and date through Editorial corrections. Confirmed factual changes update the relevant comparison fields and review. Product and price refreshes are not presented as a new detection benchmark.
Reviews using this method
- ShieldLabs review · 9.6 out of 10
- Sift review · 9.1 out of 10
- SEON review · 8.9 out of 10
- Sardine review · 8.5 out of 10
- Forter review · 8.4 out of 10
- Signifyd review · 8.2 out of 10
- Riskified review · 8.0 out of 10
- Stripe Radar review · 7.8 out of 10
- Feedzai review · 7.6 out of 10