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An independent annual ranking of the providers that banks, payment, e-money and fintech firms buy to stop payment fraud, account takeover, fake sign-ups and scams. 13 providers, six criteria, nothing paid for.
Scores out of 100. Each segment weights the criteria differently; the method is below. Facts read on 26 October 2026 from the providers' own pages.
The mean of the 3 segment scores.
| Rank and provider | Score /100 | Status | Strongest for |
|---|---|---|---|
| 1. SEON | 77 | Fraud prevention and AML platform | Payment and fintech firms wanting a published monthly price and fast set-up |
| 2. Stripe Radar | 61 | Payment fraud prevention | Firms already processing card payments with Stripe |
| 3. Unit21 | 57 | Fraud and AML operations platform | US banks and fintechs needing fraud rules, investigations and SAR filing together |
| 4. Fingerprint | 56 | Device intelligence for fraud prevention | Fintechs wanting device recognition with clear self-serve prices |
| 5. Oscilar | 53 | Fraud, credit and AML decisioning platform | US fintechs and payment firms wanting backtesting and case management together |
| 6. Sardine | 53 | Fraud and AML platform | Fintechs and banks combining fraud, scams and AML in one system |
| 7. Feedzai | 52 | Fraud and financial crime platform for banks | Large banks needing scam prevention and onboarding risk on one platform |
| 8. DataVisor | 52 | Fraud and AML platform | Banks and credit unions wanting unsupervised machine learning and case tools |
| 9. BioCatch | 51 | Behavioural fraud and scam detection | Retail banks fighting scams, mule accounts and account takeover |
| 10. Ravelin | 45 | Payment fraud prevention | Payment providers and online merchants fighting card fraud and chargebacks |
| 11. Sift | 42 | Fraud prevention platform | Fintechs and marketplaces wanting a large shared data network |
| 12. SHIELD | 41 | Device intelligence for fraud prevention | Asian e-wallets and apps stopping fake accounts at sign-up and login |
| 13. Bureau | 32 | Fraud and identity risk platform | Indian lenders and marketplaces stopping fake applications at onboarding |
Weighted to coverage, detection signals and security: scams and account takeover at high volume, with investigators and auditors relying on every decision.
| Rank and provider | Score /100 | Status | Strongest for |
|---|---|---|---|
| 1. SEON | 76 | Fraud prevention and AML platform | Payment and fintech firms wanting a published monthly price and fast set-up |
| 2. Unit21 | 72 | Fraud and AML operations platform | US banks and fintechs needing fraud rules, investigations and SAR filing together |
| 3. Oscilar | 67 | Fraud, credit and AML decisioning platform | US fintechs and payment firms wanting backtesting and case management together |
| 4. Stripe Radar | 64 | Payment fraud prevention | Firms already processing card payments with Stripe |
| 5. BioCatch | 61 | Behavioural fraud and scam detection | Retail banks fighting scams, mule accounts and account takeover |
| 6. Sardine | 61 | Fraud and AML platform | Fintechs and banks combining fraud, scams and AML in one system |
| 7. Feedzai | 58 | Fraud and financial crime platform for banks | Large banks needing scam prevention and onboarding risk on one platform |
| 8. DataVisor | 58 | Fraud and AML platform | Banks and credit unions wanting unsupervised machine learning and case tools |
| 9. Ravelin | 49 | Payment fraud prevention | Payment providers and online merchants fighting card fraud and chargebacks |
| 10. Fingerprint | 46 | Device intelligence for fraud prevention | Fintechs wanting device recognition with clear self-serve prices |
| 11. Sift | 45 | Fraud prevention platform | Fintechs and marketplaces wanting a large shared data network |
| 12. SHIELD | 41 | Device intelligence for fraud prevention | Asian e-wallets and apps stopping fake accounts at sign-up and login |
| 13. Bureau | 38 | Fraud and identity risk platform | Indian lenders and marketplaces stopping fake applications at onboarding |
Weighted to coverage and detection signals: every payment checked in real time, at a cost the firm can plan for.
| Rank and provider | Score /100 | Status | Strongest for |
|---|---|---|---|
| 1. SEON | 77 | Fraud prevention and AML platform | Payment and fintech firms wanting a published monthly price and fast set-up |
| 2. Stripe Radar | 62 | Payment fraud prevention | Firms already processing card payments with Stripe |
| 3. Fingerprint | 56 | Device intelligence for fraud prevention | Fintechs wanting device recognition with clear self-serve prices |
| 4. Unit21 | 55 | Fraud and AML operations platform | US banks and fintechs needing fraud rules, investigations and SAR filing together |
| 5. Feedzai | 54 | Fraud and financial crime platform for banks | Large banks needing scam prevention and onboarding risk on one platform |
| 6. DataVisor | 54 | Fraud and AML platform | Banks and credit unions wanting unsupervised machine learning and case tools |
| 7. Sardine | 53 | Fraud and AML platform | Fintechs and banks combining fraud, scams and AML in one system |
| 8. Oscilar | 52 | Fraud, credit and AML decisioning platform | US fintechs and payment firms wanting backtesting and case management together |
| 9. BioCatch | 50 | Behavioural fraud and scam detection | Retail banks fighting scams, mule accounts and account takeover |
| 10. Ravelin | 45 | Payment fraud prevention | Payment providers and online merchants fighting card fraud and chargebacks |
| 11. Sift | 44 | Fraud prevention platform | Fintechs and marketplaces wanting a large shared data network |
| 12. SHIELD | 43 | Device intelligence for fraud prevention | Asian e-wallets and apps stopping fake accounts at sign-up and login |
| 13. Bureau | 32 | Fraud and identity risk platform | Indian lenders and marketplaces stopping fake applications at onboarding |
Weighted to published pricing and integration: small teams that need to go live quickly and know what they will pay.
| Rank and provider | Score /100 | Status | Strongest for |
|---|---|---|---|
| 1. SEON | 78 | Fraud prevention and AML platform | Payment and fintech firms wanting a published monthly price and fast set-up |
| 2. Fingerprint | 65 | Device intelligence for fraud prevention | Fintechs wanting device recognition with clear self-serve prices |
| 3. Stripe Radar | 58 | Payment fraud prevention | Firms already processing card payments with Stripe |
| 4. Sardine | 45 | Fraud and AML platform | Fintechs and banks combining fraud, scams and AML in one system |
| 5. Feedzai | 44 | Fraud and financial crime platform for banks | Large banks needing scam prevention and onboarding risk on one platform |
| 6. DataVisor | 44 | Fraud and AML platform | Banks and credit unions wanting unsupervised machine learning and case tools |
| 7. Unit21 | 43 | Fraud and AML operations platform | US banks and fintechs needing fraud rules, investigations and SAR filing together |
| 8. BioCatch | 42 | Behavioural fraud and scam detection | Retail banks fighting scams, mule accounts and account takeover |
| 9. Oscilar | 41 | Fraud, credit and AML decisioning platform | US fintechs and payment firms wanting backtesting and case management together |
| 10. Ravelin | 41 | Payment fraud prevention | Payment providers and online merchants fighting card fraud and chargebacks |
| 11. SHIELD | 40 | Device intelligence for fraud prevention | Asian e-wallets and apps stopping fake accounts at sign-up and login |
| 12. Sift | 37 | Fraud prevention platform | Fintechs and marketplaces wanting a large shared data network |
| 13. Bureau | 25 | Fraud and identity risk platform | Indian lenders and marketplaces stopping fake applications at onboarding |
Each criterion is scored 0 to 5 against the best published offer in this edition. 0 means not offered or not published.
6 criteria, scored only from what each provider publishes.
Whether one provider publishes all five types: payment fraud, account takeover (a criminal getting into a real customer's account), new account and application fraud (sign-ups using stolen or invented identities), scams where a customer is tricked into sending money (often called authorised push payment fraud), and chargebacks (card payments reversed after a fraud claim).
Monthly or per-check prices with the volume included, on a pricing page. "From", "starting at" and promotional prices do not count.
Device intelligence (recognising the phone or computer used), behavioural biometrics (how a person types, swipes or moves the mouse), shared data from many clients, and machine learning that shows why a score was given.
Rules the client can write and change, testing rules on past data before use (backtesting), case management for investigators, and regulatory reports such as suspicious activity reports (SARs).
An API, web and mobile SDKs (code kits that collect signals inside the firm's website or app), self-serve sign-up or a free trial, and a stated time to go live.
Security certifications such as ISO 27001, SOC 2 Type II and PCI DSS (the card industry's data security standard), and regulated banks, payment or e-money firms named as clients.
| Criterion | Banks and lenders | Payment and e-money firms | Fintechs and marketplaces |
|---|---|---|---|
| Fraud coverage | 25 | 25 | 20 |
| Published pricing | 5 | 15 | 25 |
| Detection signals | 25 | 20 | 15 |
| Rules and case management | 20 | 15 | 10 |
| Integration | 5 | 15 | 20 |
| Security and clients | 20 | 10 | 10 |
| Criterion | 5 | 3 | 0 |
|---|---|---|---|
| Fraud coverage | Payment fraud, account takeover, new account fraud, scams and chargebacks all published | Three of the five published | Not published |
| Published pricing | Monthly or per-check prices with included volume on a pricing page | One plan priced, or part of the product priced | Not published, or "from" prices only |
| Detection signals | Device intelligence, behavioural biometrics, shared client data and explained machine learning scores | Two of the four published | Not published |
| Rules and case management | Client-written rules, backtesting, case management and regulatory reporting | Two of the four published | Not published |
| Integration | API, web and mobile SDKs, self-serve sign-up or free trial and a stated time to go live | API with one other option | Not published |
| Security and clients | ISO 27001 and SOC 2 Type II with named regulated clients | One certification published | Not published |
Score out of 100 is the sum of each criterion score divided by five and multiplied by its weight. The overall ranking is the mean of the segment scores. Ties are broken by fraud coverage, then detection signals. A provider that does not publish a price is scored as though the price were high, because a business cannot plan on an unpublished price. Prices are scored on the standard published rate, never an introductory, promotional or "from" rate, and a figure counts only when it appears on a pricing, fee or terms page rather than in a marketing line. A provider that serves one country only is scored on access for that country, and the limitation is printed in its profile.
What each provider publishes, criterion by criterion, with the date read and the source.
A fraud and AML platform built on more than 1,100 device, digital footprint and behaviour signals, covering payment fraud, account takeover, new account fraud and chargebacks. It publishes a monthly starter price with included checks, an average 14-day go-live and three security standards. Scam detection is not published as a product.
| Coverage | Use cases include Account Takeover, Transaction Monitoring, Chargeback Management, Mule Account Detection and New Account Fraud; "Stop bonus abuse, synthetic identity fraud, account takeovers and chargebacks". |
| Pricing | Starter: "$699 per month" with "2,500 fraud checks / month", 10 users and 50 custom rules. Premium: "Custom pricing". Free trial on request. |
| Signals | "1,100+ first-party data signals"; device intelligence and behavioural analysis "that spots screen sharing, remote access tools"; network analysis across shared devices, IPs and emails; "See which of the 1,100+ signals drove the AI insights score". |
| Operations | "Fine-tune risk thresholds and build highly granular rules"; AI-written rules; case management that "auto-assigns alerts, summarizes findings and maintains a complete audit trail". |
| Integration | API-first with documentation and GitHub; "averaging 14 days from implementation to impact"; Shopify and AWS integrations; free trial. |
| Security and clients | Compliance badges: "GDPR, ISO 27001 Certified, CCPA, SOC 2, PCI DSS Compliant" (SOC 2 type not stated). Case study with tbi Bank; logos include Revolut and BNP Paribas. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: seon.io, seon.io, seon.io.
Stripe's fraud product, trained on data across the Stripe network, covering transaction fraud, account fraud, customer abuse and disputes. It publishes tiered plans with backtested custom rules and Stripe's PCI Level 1 certification. Its plan prices are published only as "starting at" figures.
| Coverage | Transaction fraud prevention, account fraud prevention for platforms, multi-account and free trial abuse, and dispute management with Smart Disputes. Scams not published. |
| Pricing | Radar Standard "Starting at $10 per month", Plus "Starting at $14 per month", Pro "Starting at $20 per month" (platform tiers start at $20, $44 and $70); pay-as-you-go option; enterprise "Contact sales". |
| Signals | "AI trained on more than 70 trillion data points across the Stripe network"; bot detection. |
| Operations | Radar Plus: "Write and backtest custom rules, choose your risk tolerance, and get advanced analytics"; fraud analytics and alerting. |
| Integration | "Get started with zero code thanks to Stripe's built-in fraud protection"; APIs and SDKs; "can be used independently of Stripe Payments" for enterprises. |
| Security and clients | "Certified us to PCI Service Provider Level 1". Customer stories name FreshBooks and Anthropic. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: stripe.com, stripe.com, docs.stripe.com.
A fraud and AML platform that combines device and behaviour signals, a shared data network covering 80M+ US adults, configurable rules and case management through to regulatory filing. It publishes SOC 2 Type I and Type II and names regulated clients through logos. It publishes no prices or integration details on the pages read.
| Coverage | Fraud blocked "across RTP, FedNow, ACH, cards, crypto"; device risk score to stop "bots, account farms, and mule networks"; onboarding risk. Scams and chargebacks not published as products. |
| Pricing | Not published on the pages read. |
| Signals | Device Risk Score using "deep device and behavioral signals"; consortium "covering 80M+ adults in the U.S."; "explainable, fully auditable decisions". |
| Operations | "Configurable rules, behavioral models, and AI agents"; Case Management; AI agents "pre-populate SARs, STRs, CTRs, 314(a), and goAML filings". |
| Integration | Not detailed on the pages read. |
| Security and clients | SOC 2 Type I and Type II attested by Armanino; GDPR and CCPA compliant. Logos include Chime, Brex, Crypto.com, Sunrise Banks and Greendot Bank. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: www.unit21.ai, www.unit21.ai.
A device intelligence provider that recognises browsers and mobile devices to stop new account fraud, account takeover and payment fraud. It publishes clear self-serve prices, a free tier, SDKs and both main security certifications. It is a signal provider without rules or case management tools.
| Coverage | Use cases: "New Account Fraud", "Account Takeover", "Payment Fraud", "SMS Fraud" and bot detection. |
| Pricing | Free: "$0 /month", "up to 1,000 API calls per month". Pro Plus: "$99 per month which includes 20,000 API requests for web and iOS, as well as 500,000 API requests for Android"; "$4 per 1,000 additional API calls". |
| Signals | Device identification "even when VPN, incognito mode, or a tampered browser or device is used"; Smart Signals with "100+" attributes. |
| Operations | Not published; Fingerprint supplies signals to the client's own rules. |
| Integration | SDKs and libraries, documentation, GitHub; free sign-up; "14 day free trial with unlimited API calls". |
| Security and clients | "ISO 27001 certified" and "SOC 2 Type II compliant"; data in AWS data centres. "Trusted by 6000+ companies"; none named on the pages read. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: fingerprint.com, fingerprint.com, fingerprint.com.
A risk decisioning platform for fraud, credit, onboarding and AML, with device and behaviour signals, backtesting on historical data and case management. It shows ISO 27001 and SOC 2 badges and names regulated fintech and payment clients. It publishes no prices or integration details.
| Coverage | Detects "card testing, chargeback fraud", "suspicious logins" and abnormal sign-up behaviour; onboarding and AML. Scams not published. |
| Pricing | Not published on the page read. |
| Signals | "Next-generation device and behavioral intelligence"; device ID reuse checks; "Explainable decisions & full auditability". |
| Operations | "Easily create or modify workflows, and automatically backtest with historical data"; "context-rich case management"; AML transaction monitoring and sanctions screening. |
| Integration | Not detailed on the page read. |
| Security and clients | ISO 27001 and SOC 2 badges (SOC 2 type not stated). Named clients: dLocal, SoFi, Nuvei and Clara. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: oscilar.com.
A fraud and financial crime platform covering transaction fraud and scams, account takeover, onboarding and money mules, with device and behaviour signals and shared data across clients. It publishes a rules engine, case management and a SAR drafting agent. It publishes no prices, SDK details or go-live time, and the SOC 2 type is not stated.
| Coverage | "Protect every transaction from fraud and scams"; account takeover; onboarding; "money mule activity"; payments across "ACH, Wires, SEPA, RTP, FedNow, Zelle, Checks". Chargebacks not published. |
| Pricing | Not published on the pages read. |
| Signals | "Proprietary device and behavioral signals"; behaviour biometrics; "cross-industry fraud intelligence gives you the shared context your internal rules alone cannot deliver"; machine learning models. |
| Operations | "Rules engine and machine learning"; Case Management; "SAR Generation Agent"; Sardine Flow to "automate workflows without code". |
| Integration | Business and entity APIs referenced; no SDK, trial or go-live time on the pages read. |
| Security and clients | Security page refers to SOC2 documentation (type not stated). Logos include Nubank and First Federal Bank of Kansas City. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: www.sardine.ai, www.sardine.ai.
A fraud and financial crime platform used by banks, covering payment fraud, account monitoring, secure onboarding and scam prevention with behavioural biometrics and device intelligence. It publishes rule simulation before deployment and SAR handling. It publishes no prices, SDKs, certifications or named clients on the pages read.
| Coverage | Solutions include Secure Onboarding, Account Monitoring, transaction fraud and ScamPrevent to "Prevent authorized scam losses". Chargebacks not published. |
| Pricing | Not published on the pages read. |
| Signals | "Real-time behavioural and device intelligence"; scam detection "uses behavioral biometrics"; Feedzai IQ "actionable network intelligence"; "140 billion events processed per year". |
| Operations | "Take control of rules, alerts, and SARs"; "Perform rule simulation, model validation, and comparison in days" before deployment; "Craft score thresholds and workflows". |
| Integration | "Orchestrate any signal or data through a single API"; no SDK, trial or go-live time on the pages read. |
| Security and clients | No certification on the pages read. Clients described as "tier 1 bank" and "Major EU Bank"; none named. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: www.feedzai.com, www.feedzai.com, www.feedzai.com.
A fraud and AML platform covering account takeover, application fraud, scams and money mules, using device and behaviour signals, unsupervised machine learning and anonymised signals across industries. It publishes rules, case management and SAR narrative drafting. It publishes no prices, certifications or named clients.
| Coverage | "Account Takeover, Application & Onboarding Fraud, Identity Fraud, Scams & Social Engineering, Fraud Rings & Money Mules"; serves "banking, fintech, payments". Chargebacks not published. |
| Pricing | Not published on the pages read. |
| Signals | "Device & Behavioral Intelligence - dEdge"; "Unsupervised Machine Learning"; "anonymized signals across industries". |
| Operations | "Rules, Features, & Workflow Automations"; "Investigations & Case Management"; "Analytics & Reporting"; "SAR Narrative Generation". |
| Integration | Integration guide and API references published; testimonial: "deploy strategies in just 15 minutes". |
| Security and clients | States it meets "rigorous global standards for security, privacy, and compliance"; no certification named. No clients named on the page read. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: www.datavisor.com.
A behavioural intelligence provider used by retail banks to detect account opening fraud, account takeover, social engineering scams and mule accounts. It publishes both main security certifications and a wide bank client base. It publishes no prices, rules tools or integration details on the pages read.
| Coverage | BioCatch Connect detects "account opening fraud, account takeover, social engineering scams, and mule accounts" and assesses receiving accounts "before payments are completed". Chargebacks not published. |
| Pricing | Not published on the pages read. |
| Signals | Analyses "thousands of applications, behavioral, device, network, and transactional signals"; detects "hesitation, confusion, and external pressure"; "collaborative intelligence network that operates without sharing personally identifiable information". |
| Operations | "Real-time Decisioning" referenced; no rules, case management or reporting tools published on the pages read. |
| Integration | "Align SDK" named; no API documentation, trial or go-live time on the pages read. |
| Security and clients | "Fully compliant with GDPR, SOC 2 Type 2, and ISO 27001". "Trusted by 350+ of the world's most innovative, forward-thinking retail banks"; logos include Barclays, HSBC, NAB, Scotiabank and TSB. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: www.biocatch.com, www.biocatch.com, www.biocatch.com.
A payment fraud provider covering card fraud, chargebacks, account takeover and policy abuse, with a consortium database of more than 9 billion identity elements and its own 3D Secure server. It publishes ISO 27001:2022 and PCI 3DS certification. It publishes no prices or rules tools on the page read.
| Coverage | "Online payment fraud & chargebacks"; "Protect accounts from takeovers and stop multi-accounting"; returns and policy abuse. Scams not published. |
| Pricing | Not published on the page read. |
| Signals | "Network database of 9+ billion identity elements" from consortium data; "graph network link analysis"; machine learning models optimised per client. |
| Operations | Graph network for visual link analysis; no client rules, backtesting or case management published on the page read. |
| Integration | "APIs, integration, library & SDKs"; 3D Secure server SDKs. |
| Security and clients | "Assessed by British Assessment Bureau and deemed to comply with the requirements of ISO 27001:2022"; "certified as Payment Card Industry 3D Secure compliant". Logos include Elavon and Fiserv. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: www.ravelin.com.
A fraud platform covering payment fraud, account takeover, fake account creation and chargebacks, drawing on a network of more than 1 trillion events a year. It publishes visibility into the signals behind each decision and case management. It publishes no prices, certifications or regulated clients on the pages read.
| Coverage | "Payment fraud, account takeover, and account abuse"; "Fake account creation, bot signups"; "Chargeback Prevention". Scams not published as a product. |
| Pricing | Not published on the pages read. |
| Signals | "Global data network processing more than 1 trillion events annually" across "700+ brands"; machine learning; "visibility into the signals, models, and workflows behind every decision". |
| Operations | "Reporting, case management, and workflow analysis to reduce manual reviews". |
| Integration | Sift Score API with "API docs and tutorials"; no trial or go-live time on the pages read. |
| Security and clients | No certification on the pages read. Logos include Turo, Patreon and Kickstarter; no regulated clients named. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: sift.com, sift.com.
A device intelligence provider used by e-wallets and apps in Asia to stop fake accounts and fraud at sign-up, login and transaction. It publishes adjustable signal sensitivity and integration "in minutes". It publishes no prices or certifications on the page read.
| Coverage | "Add device-powered detection at signup, login, transaction, and more"; identifies "fake accounts". Scams and chargebacks not published. |
| Pricing | Not published; pricing link leads to a demo request. |
| Signals | "Real-time device intelligence"; "Watch device behavior in real-time to flag when a good user turns bad"; "Fine-tune the sensitivity of 20+ fraud signals". |
| Operations | "Customize fraud policies that factor in behavior across the entire user journey". |
| Integration | "Integrate across web, mobile, and server-side environments in minutes, not weeks. Stream alerts via API and monitor everything in a unified dashboard." |
| Security and clients | No certification on the page read. Testimonial from Maya; logos include TrueMoney, Razer and Alibaba. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: shield.com.
A risk platform that combines device, behaviour, identity, network and transaction signals for onboarding, authentication and payments. It names lending and marketplace clients. It publishes no prices, rules tools, integration details or certifications on the page read.
| Coverage | "Real-time risk decisions across every digital touchpoint, onboarding, authentication, and payments"; client quote: "we identified 20% more fake applications". Scams and chargebacks not published. |
| Pricing | Not published on the page read. |
| Signals | "Combine device, behavior, identity, network, and transaction data"; "highly accurate device fingerprinting". |
| Operations | "Unified Risk Decisioning Platform" with workflows; no rules, case management or reporting detail. |
| Integration | Not detailed on the page read. |
| Security and clients | No certification on the page read. Named clients include Aditya Birla Capital and Rapido. |
| Date read | Read 26 October 2026 |
Facts read on 26 October 2026 from: bureau.id.
The index is paid for by nobody.
No provider pays to be assessed, listed or ranked, and there are no sponsored places. Providers do not apply: BCC selects the providers a business is likely to consider and scores them from their own pages. Any provider may ask to be assessed; the request changes nothing about the score.
Every figure is read from the provider's own pricing, product, legal or help page on the date shown. Providers may send corrections to [email protected]; a correction changes the page only where the provider's own page supports it. Every provider is re-read monthly and a new edition is published each October.
Identity verification platforms whose main product is checking identity documents are ranked in the Identity Verification and Transaction Monitoring Index, and providers whose main product is sanctions screening are ranked in the Sanctions and Adverse Media Screening Index. Chargeback guarantee services sold mainly to online shops, such as Signifyd and Forter, card scheme tools, and consumer security apps are left out. Featurespace and Hawk are not assessed in this edition because their product pages could not be read. Large credit bureaus and enterprise suites, including LexisNexis Risk Solutions and NICE Actimize, are not assessed in this edition.
Ranked providers may show the index badge on their own site.
The badge is free. The one condition is that it links to this page, so that a reader can check the score and the method behind it. It is withdrawn if the link is removed or the provider leaves the index.
Embed: <a href="https://www.buckinghamcapitalconsulting.com/fraud-prevention-index"><img src="https://www.buckinghamcapitalconsulting.com/assets/bcc-fraud-prevention-index-2026.svg" alt="Ranked in the Buckingham Capital Consulting Fraud Prevention Index 2026" width="300"></a>
Nobody. No provider pays to be assessed, listed or ranked.
In payment fraud a criminal uses someone else's card or account. In a scam the real customer sends the money themselves after being deceived, so the payment looks normal. Catching scams needs different signals, such as signs that the customer is on a call with a stranger, and in the UK banks and payment firms now have to repay most scam victims.
It is the measurement of how a person uses a device: typing speed, how they hold the phone, how they move the mouse. It can show that a session is being run by a criminal or by a customer under pressure, even when the password and device are correct.
A "from" or "starting at" price is the lowest price for the smallest plan and does not tell a firm what it will pay. Only a published monthly or per-check price with its volume counts.
No. The firm stays responsible for its own fraud controls, customer refunds and reporting under its regulator's rules. A provider supplies scores and tools; the firm's policies and people decide what to block and what to report.
Every provider is re-read monthly and a new edition is published every October.
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