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.
1,755 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 ARF Labs OU

AI assistants do not name this cross-border payments provider in any of the 60 answers, while they sometimes name companies like Airwallex and Nium. Its overall score is 25 out of 100, ranking 1,755th of 2,219, close to the typical company in its sector. Its website passes 6 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned ARF Labs OU by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 179th of 375 in its sector. The typical cards and payments company is named in 0.0% 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
25Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality67
  • AI readiness43
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
6/14
technical checks passed. Typical for its sector: 4
Rank in its sector
280 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

ARF Labs OU came up on 0 of 15 questions. Open any window to read that answer.

  1. 01What pricing models are available for accessing revolving capital for borderless transactions?0/4
  2. 02How can financial institutions ensure compliance when sourcing liquidity for cross-border payments?0/4
  3. 03What should payment companies look for when choosing a cross-border payment liquidity platform?0/4
  4. 04Revolving credit line vs traditional bank loan for cross-border payment liquidity: what's the difference?0/4
  5. 05Open banking vs. liquidity platforms: what are the alternatives for international payment settlement?0/4
  6. 06How do on-chain liquidity solutions compare to off-chain methods for international settlements?0/4
  7. 07What are alternatives to using a dedicated platform for managing cross-border payment liquidity?0/4
  8. 08Why might a cross-border transaction fail due to liquidity issues, and how can these be resolved?0/4
  9. 09How do financial institutions access receivable-backed liquidity for international transactions?0/4
  10. 10Is using a specialized cross-border liquidity provider worth it for payment service providers?0/4
  11. 11How are fees typically structured for platforms offering liquidity for international payments?0/4
  12. 12How can a payment provider benefit from real-time liquidity solutions for global transfers?0/4
  13. 13What are the best platforms for providing liquidity for cross-border payments?0/4
  14. 14What are typical use-cases for short-term, receivable-backed liquidity in cross-border remittance?0/4
  15. 15How can correspondent banking networks serve as an alternative for cross-border liquidity needs?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

“Open banking vs. liquidity platforms: what are the alternatives for international payment settlement?”

I'll search for information about international payment settlement alternatives, focusing on open banking and liquidity platforms.Based on current alternatives, international payment settlement has evolved significantly beyond traditional SWIFT. Here's a comprehensive overview:

Three Main Categories of Alternatives

Modern alternatives generally fall into three categories: regional real-time payment rails, fintech-led cross-border platforms, and blockchain and stablecoin settlement networks, each reducing reliance on correspondent banking in different ways.

Open Banking

Enabled by PSD …

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
    Airwallex
    7
  2. 02
    Nium
    2
  3. 03
    Currencycloud
    2

Share of mentions

CompanyShare
  1. Airwallex
    46.7%
  2. Ripple Liquidity Hub
    20.0%
  3. Currencycloud
    20.0%
  4. Nium
    13.3%
  5. ARF Labs OU
    0.0%
  6. Circle Treasury
    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
    thunes.com
    10
  2. 02
    bis.org
    10
  3. 03
    xtransfer.com
    7
  4. 04
    stripe.com
    7
  5. 05
    bvnk.com
    6
  6. 06
    sourceforge.net
    5
  7. 07
    dashdevs.com
    4
  8. 08
    opendue.com
    4
  9. 09
    jpmorgan.com
    4
  10. 10
    citigroup.com
    4

ARF Labs OU is in the study as a cross-border payments provider.

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 ARF Labs OU 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
67

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 cards and payments companies

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

Overall score
25
Ranks 280 of 375. Typical company: 27
Named in answers
0.0%
Ranks 179 of 375. Typical company: 0.0%
AI readiness
43
Ranks 15 of 375. Typical company: 29
Against its categorySection 08

Compared with cross-border payments providers

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

Overall score
25
Ranks 62 of 84. Typical company: 27
Named in answers
0.0%
Ranks 33 of 84. Typical company: 0.0%
AI readiness
43
Ranks 1 of 84. 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. ARF Labs OU 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
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
18 of 100
  • API CatalogNot met

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

    study: 1.3%
  • OAuth discoveryPartly 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 31 of 100 · 97% of checks could run · checked on October 9, 2026 · arf.one · 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%
  • PassedHTTP Link headers (RFC 8288)study: 42.5%

Content Accessibility

  • PassedMarkdown content negotiationstudy: 7.4%
  • Not metllms.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%
  • 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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