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

Veriff

veriff.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.
235 of 2,219
its rank by overall score
Place in its category
25th of 171 fraud and identity companies
Closing balance

Named in

10of 60 answers

by 4 of 4 assistants

Statement note

What this means for Veriff

AI assistants name this fraud and identity company in 16.7% of answers, much more often than the typical company in its sector at 1.7%. Its overall score is 40 out of 100, ranking 235th of 2,219 overall and 73rd of 574 in its sector. The website passes 6 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Veriff by name. AI assistants named it in 10 of the 60 answers. Counting only how often it is named, it ranks 63rd of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Overall score
40Overall score
  • Visibility16
  • Citations2
  • Sentiment83
  • Site quality87
  • AI readiness43
Summary of account
Named by AI in
16.7%
10 of 60 answers
Share of mentions
16.7%
of the mentions of it and its 5 peers
AI readiness
6/14
technical checks passed. Typical for its sector: 4
Rank in its sector
73 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

Veriff came up on 6 of 15 questions. Open any window to read that answer.

  1. 01What should enterprises consider before purchasing identity verification software?0/4
  2. 02Do identity verification platforms offer volume discounts or custom pricing for large businesses?1/4
  3. 03What are common use cases for enterprise identity verification platforms beyond customer onboarding?0/4
  4. 04Is investing in advanced identity verification solutions worth it for enterprise-level fraud prevention?0/4
  5. 05How can financial institutions use identity verification technology to meet regulatory requirements?0/4
  6. 06What are some alternatives to dedicated identity verification software for enterprises?2/4
  7. 07How does biometric identity verification compare to document-based verification software for enterprises?0/4
  8. 08How do enterprise verification systems handle false positives or user verification errors?0/4
  9. 09What determines the pricing tiers for enterprise-level identity verification software in the US?0/4
  10. 10What are the differences between cloud-based and on-premises identity verification platforms for large organizations?0/4
  11. 11What are the best enterprise identity verification software options for large businesses?3/4
  12. 12Which identity verification systems support seamless integration with existing enterprise workflows?1/4
  13. 13Are there low-code or API-first solutions that serve as alternatives to traditional enterprise identity verification platforms?1/4
  14. 14Why might an identity verification attempt fail on enterprise platforms, and how can businesses address this?0/4
  15. 15Which identity verification tools offer real-time, global compliance for US enterprises?2/4
Total namedOpenAI: 2/15Claude: 1/15Perplexity: 3/15Gemini: 4/15All assistants: 10/60
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 Perplexity actually said

An answer that names the company

Perplexitynamed the company

“What are the best enterprise identity verification software options for large businesses?”

For large businesses, the strongest enterprise identity-verification options are Jumio, Entrust (formerly Onfido), Veriff, Persona, Sumsub, Trulioo, and 1Kosmos. The best choice depends on whether the priority is global document coverage, fraud prevention, workflow flexibility, compliance, or workforce identity assurance.

Platform · Best for · Notable strengths

Jumio · High-volume customer onboarding · AI document verification, biometrics, and large transaction scale; well suited to regulated enterprises.

Entrust / Onfido · Global enterprises …

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
    Trulioo
    13
  2. 02
    Jumio
    10
  3. 03
    Onfido
    8
  4. 04
    Socure
    6
  5. 05
    ID.me
    1

Share of mentions

CompanyShare
  1. Trulioo
    25.0%
  2. Jumio
    23.3%
  3. Onfido
    18.3%
  4. Veriff
    16.7%
  5. Socure
    15.0%
  6. ID.me
    1.7%
ReferrersSection 04

Websites the AI used as sources

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

  1. 01
    1kosmos.com
    11
  2. 02
    scandit.com
    9
  3. 03
    didit.me
    8
  4. 04
    regulaforensics.com
    8
  5. 05
    microblink.com
    8
  6. 06
    idenfy.com
    8
  7. 07
    ondato.com
    8
  8. 08
    shuftipro.com
    6
  9. 09
    entrust.com
    5
  10. 10
    learn.g2.com
    5

Veriff 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
Perplexity
3/15
OpenAI
2/15
Claude
1/15
Market comparisonSection 06

How Veriff 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
16

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

Citations
2

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
43

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
40
Ranks 73 of 574. Typical company: 29
Named in answers
16.7%
Ranks 63 of 574. Typical company: 1.7%
AI readiness
43
Ranks 29 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
40
Ranks 25 of 171. Typical company: 30
Named in answers
16.7%
Ranks 15 of 171. Typical company: 1.7%
AI readiness
43
Ranks 11 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 0: Not yet agent-ready. Agents struggle to find basic information about the site.

To reach level 1:
  • 2 of robots.txt, Sitemap, Link headers

Some checks could not run. With them, up to level 2 would be possible.

Can an AI agent check out here?

We could not tell. The website turned away our requests for the files an agent would read. An agent arriving by itself is turned away the same way.

Agent payment protocols
  • x402Not present
  • MPPNot present
  • AP2Not present
  • ACPNot present
  • UCPCould not check
Interfaces for AI agents
  • MCP Server CardNot present
  • A2A Agent CardNot present
  • Agent SkillsNot present
  • API CatalogNot present
  • llms.txtPublished
  • WebMCPCould not check
Show every check, for your technical team
Discoverability
52 of 100
  • robots.txtCould not check

    Publish a valid robots.txt with crawl rules and a Sitemap line.

    study: 86.1%
  • SitemapPartly met

    Serve an XML sitemap and reference it 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
25 of 100
  • Markdown negotiationNot met

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

    study: 6.2%
  • llms.txtPartly met

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

    study: 31.0%
Bot access control
  • AI bot rulesCould not check

    Add explicit robots.txt groups for the main AI crawlers.

    study: 92.7%
  • Content SignalsCould not check

    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
10 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 ResourcePassed

    Metadata telling agents which authorization server to use.

    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 23 of 100 · 67% of checks could run · checked on October 9, 2026 · www.veriff.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

6 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

  • Not metExplicit AI bot rulesstudy: 11.5%

API / Auth / MCP

  • Not metAPI Catalog (.well-known/api-catalog)study: 1.1%
  • PassedOAuth Authorization Server discoverystudy: 5.2%
  • PassedOAuth 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 no rules for any AI crawler by name, like 86% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI

  • GPTBotpartly
  • ClaudeBotpartly
  • Anthropic-AIpartly
  • Google-Extendedpartly
  • Applebot-Extendedpartly
  • Meta-ExternalAgentpartly
  • FacebookBotpartly
  • Bytespiderpartly
  • CCBotpartly
  • Diffbotpartly
  • Omgilibotpartly

AI search

  • OAI-SearchBotpartly
  • Claude-SearchBotpartly
  • PerplexityBotpartly
  • Applebotpartly
  • Amazonbotpartly
  • YouBotpartly

Answering questions

  • ChatGPT-Userpartly
  • Claude-Userpartly
  • Perplexity-Userpartly
  • 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 40 of 100 badge for Veriff

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/veriff.com"><img src="https://aeo-audit.rezolve.com/finance/badges/veriff.com.svg" alt="Overall score 40 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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