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Euronet Worldwide

euronet.com · Finance · EEFT

Ranked 1,827 of 2,047 companies in the study

25Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality67
  • AI readiness36
What this means for Euronet Worldwide

AI assistants do not name Euronet Worldwide in any of their answers to questions about the finance sector. Its overall score is 25 out of 100, ranking 1,827th of 2,047 companies, while the typical company in its sector scores 29. Its website passes 5 of 14 technical checks for readiness with AI tools.

We asked 15 unbranded questions about the finance market: none named Euronet Worldwide. AI assistants named it in none of 60 answers. The typical finance company is named in 3.3% of answers. By how often it is named, Euronet Worldwide ranks 135 of 205 in its sector.

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 rivals.

Named by AI in
0.0%
0 of 60 answers
Share of mentions
0.0%
compared with 5 rivals
AI readiness
5/14
technical checks passed. Typical for its sector: 3
Rank in its sector
173 of 205
by overall score, where the typical finance company scores 29
How Euronet Worldwide compares with all 2,047 companies

Every dot is a company in the study. Hover one to see it; click to open its report.

This companySame sectorEvery other companyNever named

What makes up the score

Five parts, each scored out of 100.

Visibility
0

How often AI assistants name the company

Citations
0

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

Sentiment
50

How positively AI describes the company

Site quality
67

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.

Compared with finance

205 companies in this sector. The line on each bar is the typical company.

Overall score25
Ranks 173 of 205. Typical company: 29
Named in answers0%
Ranks 135 of 205. Typical company: 3%
AI readiness36
Ranks 7 of 205. Typical company: 21
Share of mentions

How the mentions in these answers were split between this company and its rivals

Euronet Worldwide
0.0%
Fiserv
0.0%
FIS (Fidelity National Information Services)
0.0%
ACI Worldwide
0.0%
Worldline
0.0%
Western Union Business Solutions (now Convera)
0.0%
Which AI assistants named the company

Answers naming it, out of answers received

Gemini
0/15
Perplexity
0/15
Claude
0/15
OpenAI
0/15
Ready for AI agents

What this website publishes for an AI agent to read, use and buy from, 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
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: 92.0%
  • SitemapPassed

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

    study: 86.8%
  • Link headersNot met

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

    study: 0.3%
  • DNS for AI DiscoveryNot present

    Advertise agent endpoints with SVCB records under _agents.

    study: 5.5%
Content accessibility
50 of 100
  • Markdown negotiationNot met

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

    study: 1.9%
  • llms.txtPassed

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

    study: 25.1%
Bot access control
32 of 100
  • AI bot rulesPartly met

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

    study: 93.4%
  • Content SignalsNot met

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

    study: 1.4%
  • Web Bot AuthNot present

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

    study: 0.2%
APIs, auth and MCP
0 of 100
  • API CatalogNot met

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

    study: 0.3%
  • OAuth discoveryNot met

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

    study: 11.8%
  • OAuth Protected ResourceNot met

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

    study: 10.3%
  • auth.mdNot met

    Publish an auth.md describing how agents sign in.

    study: 0.0%
  • MCP Server CardNot met

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

    study: 0.2%
  • A2A Agent CardNot met

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

    study: 0.1%
  • Agent SkillsNot met

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

    study: 0.2%
  • WebMCPCould not check

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

    study: 33.7%
  • ARD manifestNot met

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

    study: 0.1%

Score 36 of 100 · 97% of checks could run · checked on October 5, 2026 · www.euronet.com · 2,047 companies scanned

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

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: 85.0%
  • PassedXML sitemapstudy: 73.2%
  • PassedHTTP Link headers (RFC 8288)study: 29.0%
Content Accessibility
  • Not metMarkdown content negotiationstudy: 8.3%
  • Passedllms.txt publishedstudy: 21.7%
  • PassedToken budget (page weight)study: 95.2%
Bot Access Control
  • Not metExplicit AI bot rulesstudy: 13.0%
API / Auth / MCP
  • Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
  • Not metOAuth Authorization Server discoverystudy: 10.1%
  • Not metOAuth Protected Resource discoverystudy: 9.3%
  • Not metMCP Server Cardstudy: 0.0%
  • Not metA2A Agent Cardstudy: 0.0%
  • Not metWebMCP toolsstudy: 4.2%
  • Not metAgent Skills declaredstudy: 0.0%
What AI crawlers may read (robots.txt)

This website sets no rules for any AI crawler by name, like 84% of the websites whose rules we could read. Every AI crawler follows its general rules.

Training AI
  • GPTBotallowed
  • ClaudeBotallowed
  • Anthropic-AIallowed
  • Google-Extendedallowed
  • Applebot-Extendedallowed
  • Meta-ExternalAgentallowed
  • FacebookBotallowed
  • Bytespiderallowed
  • CCBotallowed
  • Diffbotallowed
  • Omgilibotallowed
AI search
  • OAI-SearchBotallowed
  • Claude-SearchBotallowed
  • PerplexityBotallowed
  • Applebotallowed
  • Amazonbotallowed
  • YouBotallowed
Answering questions
  • ChatGPT-Userallowed
  • Claude-Userallowed
  • Perplexity-Userallowed
  • DuckAssistBotallowed
  • MistralAI-Userallowed

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.

Websites the AI used as sources

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

airwallex.com
38
wise.com
38
stripe.com
37
jpmorgan.com
17
worldfirst.com
16
connectpay.com
14
ramp.com
13
papayaglobal.com
13
aciworldwide.com
11
bill.com
9

In the study as US-listed.

Every question, and where the company came up (0 of 15)
QuestionOpenAIClaudePerplexityGemini
  • Which global payments solutions are best for managing high-volume international payroll?
  • Is it worth investing in a dedicated global payments infrastructure for a mid-sized US business?
  • What factors affect transaction fees for international payment processing?
  • How is pricing structured for global payments and cross-border processing services in the US?
  • How do payments infrastructure providers enable real-time settlement for cross-border transactions?
  • What are the best global payments processing platforms for US businesses expanding internationally?
  • Cross-border payments processing vs traditional bank transfers for international business transactions – what are the key differences?
  • What are common issues US companies face when processing cross-border payments, and how can they be resolved?
  • Modern options for international business payments beyond wire transfers
  • What should businesses look for when choosing a cross-border transaction provider?
  • What are the advantages of digital payments infrastructure compared to standard wire services for global transactions?
  • What alternatives exist to legacy cross-border payment networks for business remittance?
  • How can payment processing platforms help US financial institutions serve multinational clients?
  • Why do some international transactions get delayed, and how can payment infrastructure help?
  • How do cross-border payments solutions support financial institutions in the US?
named the companyanswered without naming itdid not answer

Columns, left to right: OpenAI, Claude, Perplexity, Gemini. The AI assistants often disagree. Across the study, on 40% of the questions where a company is named, only one of the four names it.

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