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.
737 of 2,219
its rank by overall score
Closing balance

Named in

4of 60 answers

by 4 of 4 assistants

Statement note

What this means for Onbe

AI assistants name this business payments provider in 6.7% of answers, more often than the typical company in its sector. Its overall score is 33 out of 100, ranking 737th of 2,219 companies. The website passes 5 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Onbe by name. AI assistants named it in 4 of the 60 answers. Counting only how often it is named, it ranks 90th of 375 in its sector. The typical cards and payments company is named in 0.0% of answers.

Overall score
33Overall score
  • Visibility15
  • Citations2
  • Sentiment63
  • Site quality73
  • AI readiness36
Summary of account
Named by AI in
6.7%
4 of 60 answers
Share of mentions
40.0%
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
109 of 375
by overall score, where the typical cards and payments company scores 27

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Line itemsSection 01

Every question, and where the company came up

Onbe came up on 2 of 15 questions. Open any window to read that answer.

  1. 01What are the best digital payout platforms for businesses to send consumer payments?1/4
  2. 02What factors influence the cost of using a consumer payouts platform for businesses?0/4
  3. 03How do payout platforms typically charge businesses for digital and physical payment options?0/4
  4. 04Which types of consumer disbursement methods can replace traditional bank transfers?0/4
  5. 05How do modern B2C payout platforms compare with traditional paper check disbursements?0/4
  6. 06What are the differences between digital wallet payouts and prepaid card payouts for businesses?0/4
  7. 07Which consumer payout solutions offer both virtual and physical payment options?3/4
  8. 08How can payment delays be minimized when sending B2C disbursements?0/4
  9. 09What are alternatives to using a dedicated B2C payouts platform for consumer payments?0/4
  10. 10What non-traditional payment rails are available for enterprise-level customer payouts?0/4
  11. 11Is investing in an integrated B2C payouts platform worth it for enterprise organizations?0/4
  12. 12What should a business do if a recipient doesn’t receive their digital payout?0/4
  13. 13How can insurance companies improve claim disbursements with modern payout technology?0/4
  14. 14Are automated payout solutions cost-effective for high-volume consumer payments?0/4
  15. 15What types of industries benefit most from using flexible B2C payout platforms?0/4
Total namedOpenAI: 1/15Claude: 1/15Perplexity: 1/15Gemini: 1/15All assistants: 4/60
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

“Which consumer payout solutions offer both virtual and physical payment options?”

Consumer payout solutions offering both virtual and physical payment options include:

Onbe — virtual and physical cards, plus ACH, PayPal, Venmo, and push-to-card payments.

Fiserv Digital Payouts and Disbursements — digital and physical Money Network prepaid cards, debit cards, checks, bank accounts, and social payments.

Usio Consumer Choice — virtual or physical branded prepaid Mastercard cards, ACH, push payments, and printed checks.

Choice Digital — instant virtual prepaid cards, physical prepaid cards, PayPal, Venmo, and physical checks.

Vis …

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
    Blackhawk Network
    1

Share of mentions

CompanyShare
  1. Onbe
    40.0%
  2. Tango
    20.0%
  3. Blackhawk Network
    20.0%
  4. Prepaid Technologies (now Dash Solutions)
    20.0%
  5. InComm Payments
    0.0%
  6. daVinci Payments
    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
    stripe.com
    24
  2. 02
    finix.com
    16
  3. 03
    whop.com
    11
  4. 04
    i-payout.com
    11
  5. 05
    onbe.com (its own website)
    9
  6. 06
    connectpay.com
    9
  7. 07
    tremendous.com
    7
  8. 08
    carat.fiserv.com
    7
  9. 09
    alacriti.com
    7
  10. 10
    usedots.com
    7

Onbe is in the study as a business payments provider.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

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

How Onbe 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
15

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
63

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 cards and payments companies

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

Overall score
33
Ranks 109 of 375. Typical company: 27
Named in answers
6.7%
Ranks 90 of 375. Typical company: 0.0%
AI readiness
36
Ranks 41 of 375. Typical company: 29
Against its categorySection 08

Compared with business payments providers

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

Overall score
33
Ranks 10 of 30. Typical company: 29
Named in answers
6.7%
Ranks 10 of 30. Typical company: 1.7%
AI readiness
36
Ranks 6 of 30. Typical company: 29
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. Onbe 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
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
32 of 100
  • AI bot rulesPartly met

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

    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 36 of 100 · 97% of checks could run · checked on October 9, 2026 · www.onbe.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%
  • 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%
  • 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 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

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Overall score 33 of 100 badge for Onbe

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<a href="https://aeo-audit.rezolve.com/us/finance/onbe.com"><img src="https://aeo-audit.rezolve.com/finance/badges/onbe.com.svg" alt="Overall score 33 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
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