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.

Back to the study
AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026
Account holder
Statement period
October 9 and 10, 2026
when the AI assistants were asked
Account no.
1,559 of 2,219
its rank by overall score
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for Enformion

AI assistants do not name this fraud and identity company in any of their 60 answers. Its overall score is 26 out of 100, ranking 1,559th of 2,219, while the typical company in its sector scores 29. Its website passes 5 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Enformion by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 334th of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Named fewer than three times in total. Read this as a sign that AI assistants rarely bring this company up, not as an exact comparison with its peers.

Overall score
26Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality73
  • AI readiness36
Summary of account
Named by AI in
0.0%
0 of 60 answers
Share of mentions
0.0%
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
418 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

Enformion came up on 0 of 15 questions. Open any window to read that answer.

  1. 01Identity analytics platform vs manual data verification methods: which is more effective for organizations?0/4
  2. 02Other ways organizations can detect fraud besides using identity analytics software?0/4
  3. 03What’s the average cost for an enterprise-level identity analytics platform in the US?0/4
  4. 04Alternatives to AI-driven identity intelligence platforms for organizations on a budget0/4
  5. 05Top-rated identity analytics solutions for fraud detection in the US0/4
  6. 06How can financial institutions use identity intelligence to improve compliance and reduce risk?0/4
  7. 07How does identity intelligence differ from traditional background check tools?0/4
  8. 08Is investing in an AI-powered identity analytics solution worth it for midsize businesses?0/4
  9. 09Are there affordable identity intelligence solutions for small businesses?0/4
  10. 10Why isn’t my identity analytics platform detecting certain types of fraud?0/4
  11. 11Common issues faced when integrating identity intelligence tools with existing business systems0/4
  12. 12Best practices for using advanced analytics to spot synthetic identity fraud0/4
  13. 13What should companies consider before purchasing an identity intelligence platform for customer lifecycle management?0/4
  14. 14What are some non-digital methods for verifying customer identities in the United States?0/4
  15. 15What are the best platforms for identity intelligence and advanced analytics for risk management?0/4
Total namedOpenAI: 0/15Claude: 0/15Perplexity: 0/15Gemini: 0/15All assistants: 0/60
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 Claude actually said

The company is not named in this answer

Claudedid not name the company

“Top-rated identity analytics solutions for fraud detection in the US”

Based on recent industry analysis, here are the top-rated identity analytics solutions for fraud detection in the US:

Leading Solutions

LexisNexis ThreatMetrix

LexisNexis ThreatMetrix detects fraud using real-time data combined with AI-driven models, leveraging the LexisNexis Digital Identity Network, a contributory network that unifies digital identity and identity intelligence from thousands of global organizations.

Kount

Kount leverages decades of global data from both physical and digital interactions and applies advanced machine learning frameworks to detect threats like syn …

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.

Named instead

CompanyTimes named
  1. 01
    LexisNexis Risk Solutions
    4
  2. 02
    Experian Precise ID
    1

Share of mentions

CompanyShare
  1. LexisNexis Risk Solutions
    63.6%
  2. TransUnion TruValidate
    18.2%
  3. IDI Core (IDI, Inc.)
    9.1%
  4. Experian Precise ID
    9.1%
  5. Enformion
    0.0%
  6. TLOxp (TransUnion)
    0.0%
ReferrersSection 04

Websites the AI used as sources

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

  1. 01
    experian.com
    6
  2. 02
    pingidentity.com
    6
  3. 03
    avatier.com
    5
  4. 04
    shuftipro.com
    5
  5. 05
    risk.lexisnexis.com
    5
  6. 06
    gartner.com
    5
  7. 07
    microblink.com
    4
  8. 08
    startwithidentity.com
    4
  9. 09
    sailpoint.com
    4
  10. 10
    shadowdragon.io
    4

Enformion 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

Claude
0/15
Gemini
0/15
OpenAI
0/15
Perplexity
0/15
Market comparisonSection 06

How Enformion 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
0

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

Citations
0

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

Sentiment
50

How positively AI describes the company

Site quality
73

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
26
Ranks 418 of 574. Typical company: 29
Named in answers
0.0%
Ranks 334 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
26
Ranks 132 of 171. Typical company: 30
Named in answers
0.0%
Ranks 103 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. Enformion 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.txtNot present
  • WebMCPCould not check
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
0 of 100
  • Markdown negotiationNot met

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

    study: 6.2%
  • llms.txtNot met

    Publish an llms.txt with a short summary and the key links.

    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 32 of 100 · 97% of checks could run · checked on October 9, 2026 · www.enformion.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%
  • PassedHTTP Link headers (RFC 8288)study: 42.5%

Content Accessibility

  • Not metMarkdown content negotiationstudy: 7.4%
  • Not metllms.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 9 AI crawlers by name. All others follow its general rules.

Training AI

  • GPTBotpartly
  • ClaudeBotpartly
  • Anthropic-AIpartly
  • Google-Extended*allowed
  • Applebot-Extended*allowed
  • Meta-ExternalAgent*allowed
  • FacebookBot*allowed
  • Bytespiderpartly
  • CCBotpartly
  • Diffbotpartly
  • Omgilibotpartly

AI search

  • OAI-SearchBot*allowed
  • Claude-SearchBotpartly
  • PerplexityBotpartly
  • Applebot*allowed
  • 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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