Of 60 answers

The most named companies in the study, and S&P 500 financials, with how many of their 60 AI answers named them.

SWIFT47/60TRANSUNION46/60EXPERIAN42/60COINSTAR41/60NAVY FEDERAL CREDIT UNION41/60ZELLE41/60BLOOMBERG L.P.38/60TRADINGVIEW38/60BANCO POPULAR DE PUERTO RICO37/60PAYPAL37/60VENMO37/60CHEXSYSTEMS33/60EQUIFAX33/60MORNINGSTAR32/60S&P GLOBAL31/60ALPACA MARKETS30/60COINBASE30/60PINWHEEL29/60STRIPE29/60XERO29/60ACORNS28/60AFFIRM28/60PAYFAST (PAYGATE)28/60PAYONEER28/60INTERACTIVE BROKERS26/60CHARLES SCHWAB19/60THE HARTFORD9/60MOODY'S21/60CME GROUP19/60ACCENTURE11/60CHUBB10/60MORGAN STANLEY6/60AMERICAN EXPRESS14/60SYNCHRONY FINANCIAL12/60FACTSET20/60NASDAQ19/60ALLSTATE11/60WELLS FARGO18/60PAYCHEX10/60ARES MANAGEMENT3/60
Rezolve Ai
MethodDemo
Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder

Sift Science

sift.com

Fraud, identity and complianceFinancial technology and data

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
103 of 2,219
its rank by overall score
Place in its category
14th of 171 fraud and identity companies
Closing balance

Named in

12of 60 answers

by 4 of 4 assistants

Statement note

What this means for Sift Science

AI assistants name this fraud and identity company in 20% of answers, compared with 1.7% for the typical company in its sector. Its overall score is 43 out of 100, ranking 103rd of 2,219 companies, and 34th of 574 in its sector. Its website passes 5 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Sift Science by name. AI assistants named it in 12 of the 60 answers. Counting only how often it is named, it ranks 46th of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Overall score
43Overall score
  • Visibility24
  • Citations4
  • Sentiment83
  • Site quality87
  • AI readiness36
Summary of account
Named by AI in
20.0%
12 of 60 answers
Share of mentions
33.3%
of the mentions of it and its 5 peers
AI readiness
5/14
technical checks passed. Typical for its sector: 4
Rank in its sector
34 of 574
by overall score, where the typical financial technology and data company scores 29

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Line itemsSection 01

Every question, and where the company came up

Sift Science came up on 5 of 15 questions. Open any window to read that answer.

  1. 01Best fraud detection solutions to reduce account takeovers for digital platforms?3/4
  2. 02What should I look for in a digital risk management solution for my ecommerce site?0/4
  3. 03What factors influence the cost of a fraud prevention platform for online retailers?0/4
  4. 04Low-cost fraud detection options for startups in the US?2/4
  5. 05What are common fraud detection strategies for digital marketplaces?0/4
  6. 06What are some alternatives to real-time fraud prevention platforms for preventing online scams?0/4
  7. 07Top features to look for in a fraud prevention solution for customer trust and safety?0/4
  8. 08How do real-time risk scoring tools help prevent payment fraud on subscription services?1/4
  9. 09How much do AI-powered fraud detection services typically cost for small businesses?2/4
  10. 10How does machine learning-based fraud detection differ from rule-based systems?0/4
  11. 11How can I reduce false positives when using automated fraud prevention software?0/4
  12. 12Is investing in an automated fraud prevention platform worth it for a growing online marketplace?0/4
  13. 13Behavioral analytics vs device fingerprinting for ecommerce fraud prevention: which is better?0/4
  14. 14Why might a fraud detection system flag legitimate transactions as suspicious?0/4
  15. 15What are the most effective real-time fraud prevention tools for online businesses?4/4
Total namedOpenAI: 4/15Claude: 1/15Perplexity: 3/15Gemini: 4/15All assistants: 12/60
named the companyanswered without naming itdid not answer

Columns, left to right: OpenAI, Claude, Perplexity, Gemini. Across the study, on 50% of the questions where a company is named, only one AI assistant names it.

Transaction detailSection 02

What OpenAI actually said

An answer that names the company

OpenAInamed the company

“What are the most effective real-time fraud prevention tools for online businesses?”

Short answer

Leading real‑time fraud‑prevention platforms (widely used in 2025–2026) are: Sift, Forter, Signifyd, Riskified, Stripe Radar, Kount (now Kount 360/Equifax), SEON and Accertify. Each offers sub‑second decisioning, ML risk‑scoring, device fingerprinting and varying levels of chargeback/guarantee products. (learn.g2.com)

What “most effective” means

Effectiveness depends on your business (volume, margins, product type), the fraud types you face and your tolerance for false declines. For many merchants “most effectiv …

The AI’s answer as we received it, shortened and not checked for accuracy.

PayeesSection 03

Where the mentions went

The companies these answers named, and how the mentions were split between this company and its peers.

Also named

CompanyTimes named
  1. 01
    Sift
    9
  2. 02
    Forter
    7
  3. 03
    Arkose Labs
    4
  4. 04
    Signifyd
    3

Share of mentions

CompanyShare
  1. Sift Science
    33.3%
  2. Kount (an Equifax Company)
    19.4%
  3. Forter
    19.4%
  4. Signifyd
    16.7%
  5. Arkose Labs
    8.3%
  6. Ekata (A Mastercard Company)
    2.8%
ReferrersSection 04

Websites the AI used as sources

How many times each website was listed as a source in these answers

  1. 01
    fraudio.com
    10
  2. 02
    fraud.net
    10
  3. 03
    sift.com (its own website)
    9
  4. 04
    fingerprint.com
    8
  5. 05
    stripe.com
    8
  6. 06
    corporate.visa.com
    7
  7. 07
    ustechautomations.com
    6
  8. 08
    topbusinesssoftware.com
    4
  9. 09
    learn.g2.com
    4
  10. 10
    expertinsights.com
    4

Sift Science is in the study as a fraud and identity company.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Gemini
4/15
OpenAI
4/15
Perplexity
3/15
Claude
1/15
Market comparisonSection 06

How Sift Science compares with all 2,219 companies

Every tower is a company in the study, taller for a higher overall score and lit where AI assistants named it. Its own group stays lit. Hover a tower to see it, and click to open it.

What makes up the score

Each part is scored out of 100.

Visibility
24

How often AI assistants name the company, and how that compares with its peers

Citations
4

How often AI uses the company's own website as a source

Sentiment
83

How positively AI describes the company

Site quality
87

How well built the website's own pages are

AI readiness
36

How easily AI tools can read and use the website

Visibility is calculated from the answers on this page. How the score is built.

Against its sectorSection 07

Compared with financial technology and data companies

574 companies in this sector. The gold tick on each bar is the typical company.

Overall score
43
Ranks 34 of 574. Typical company: 29
Named in answers
20.0%
Ranks 46 of 574. Typical company: 1.7%
AI readiness
36
Ranks 83 of 574. Typical company: 29
Against its categorySection 08

Compared with fraud and identity companies

171 companies in this category. The gold tick on each bar is the typical company.

Overall score
43
Ranks 12 of 171. Typical company: 30
Named in answers
20.0%
Ranks 7 of 171. Typical company: 1.7%
AI readiness
36
Ranks 35 of 171. Typical company: 36
AI agentsSection 09

Ready for AI agents

What this website publishes for an AI agent to read, use and pay through, on a scale of six levels.

  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5

Level 1: Basic web presence. Two of robots.txt, a sitemap and Link headers are in place.

To reach level 2:
  • Content Signals
Can an AI agent check out here?

Not by itself. Sift Science publishes none of the agent payment protocols we look for. An agent would have to click through the website like a person.

Agent payment protocols
  • x402Not present
  • MPPNot present
  • AP2Not present
  • ACPNot present
  • UCPNot present
Interfaces for AI agents
  • MCP Server CardNot present
  • A2A Agent CardNot present
  • Agent SkillsNot present
  • API CatalogNot present
  • llms.txtPublished
  • WebMCPCould not check

The website runs on WooCommerce.

Show every check, for your technical team
Discoverability
77 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    study: 86.1%
  • SitemapPassed

    An XML sitemap listing the pages, ideally referenced from robots.txt.

    study: 87.9%
  • Link headersNot met

    Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.

    study: 1.5%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 4.3%
Content accessibility
50 of 100
  • Markdown negotiationNot met

    Return a markdown version when asked with Accept: text/markdown, for example at the CDN.

    study: 6.2%
  • llms.txtPassed

    An llms.txt that tells language models what the site offers.

    study: 31.0%
Bot access control
63 of 100
  • AI bot rulesPassed

    Explicit robots.txt rules for AI crawlers such as GPTBot, ClaudeBot and PerplexityBot.

    study: 92.7%
  • Content SignalsNot met

    Add a Content-Signal line for search, ai-input and ai-train to robots.txt.

    study: 2.3%
  • Web Bot AuthNot present

    Only relevant if you run your own agents or crawlers: publish a signing key directory.

    study: 0.3%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

    List public APIs in a linkset at /.well-known/api-catalog.

    study: 1.3%
  • OAuth discoveryNot met

    Publish OpenID Connect or OAuth server metadata under /.well-known.

    study: 6.3%
  • OAuth Protected ResourceNot met

    Serve protected resource metadata at /.well-known/oauth-protected-resource.

    study: 5.3%
  • auth.mdNot met

    Publish an auth.md describing how agents sign in.

    study: 0.2%
  • MCP Server CardNot met

    Offer an MCP server and publish its server card under /.well-known.

    study: 0.8%
  • A2A Agent CardNot met

    Publish an agent card at /.well-known/agent-card.json.

    study: 0.2%
  • Agent SkillsNot met

    Publish a skills index with the main tasks agents can do.

    study: 1.0%
  • WebMCPCould not check

    Register key actions such as search or cart as WebMCP tools.

    study: 0.0%
  • ARD manifestNot met

    Publish an ai-catalog.json listing every agent interface.

    study: 0.2%

Score 43 of 100 · 97% of checks could run · checked on October 9, 2026 · sift.com · 2,200 companies scanned

See how every company did, and how this was measured.

AI readinessSection 10

The checks behind the AI readiness score

5 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.

These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.

Show the 14 checks

Discoverability

  • Passedrobots.txt publishedstudy: 85.1%
  • PassedXML sitemapstudy: 79.4%
  • Not metHTTP Link headers (RFC 8288)study: 42.5%

Content Accessibility

  • Not metMarkdown content negotiationstudy: 7.4%
  • Passedllms.txt publishedstudy: 28.1%
  • PassedToken budget (page weight)study: 97.3%

Bot Access Control

  • PassedExplicit AI bot rulesstudy: 11.5%

API / Auth / MCP

  • Not metAPI Catalog (.well-known/api-catalog)study: 1.1%
  • Not metOAuth Authorization Server discoverystudy: 5.2%
  • Not metOAuth Protected Resource discoverystudy: 4.6%
  • Not metMCP Server Cardstudy: 0.2%
  • Not metA2A Agent Cardstudy: 0.0%
  • Not metWebMCP toolsstudy: 0.3%
  • Not metAgent Skills declaredstudy: 0.1%
AI crawlersSection 11

What AI crawlers may read (robots.txt)

This website sets rules for 11 AI crawlers by name. All others follow its general rules.

Training AI

  • GPTBot*allowed
  • ClaudeBot*allowed
  • Anthropic-AIpartly
  • Google-Extended*allowed
  • Applebot-Extended*allowed
  • Meta-ExternalAgentpartly
  • FacebookBotpartly
  • Bytespiderpartly
  • CCBot*allowed
  • Diffbotpartly
  • Omgilibotpartly

AI search

  • OAI-SearchBot*allowed
  • Claude-SearchBot*allowed
  • PerplexityBot*allowed
  • Applebotpartly
  • Amazonbotpartly
  • YouBotpartly

Answering questions

  • ChatGPT-User*allowed
  • Claude-User*allowed
  • Perplexity-User*allowed
  • DuckAssistBotpartly
  • MistralAI-Userpartly

Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.

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ShareSection 12

Share this result

Overall score 43 of 100 badge for Sift Science

A badge of this result that you can show on your own website. Copy the code below.

<a href="https://aeo-audit.rezolve.com/us/finance/sift.com"><img src="https://aeo-audit.rezolve.com/finance/badges/sift.com.svg" alt="Overall score 43 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
End of statement
All 2,219 companiesHow we measured this
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