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

The Credit Union Data Exchange

cudx.com

Banking and fintech infrastructureFinancial technology and data

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
402 of 2,219
its rank by overall score
Place in its category
56th of 315 fintech infrastructure companies
Closing balance

Named in

7of 60 answers

by 3 of 4 assistants

Statement note

What this means for The Credit Union Data Exchange

AI assistants name The Credit Union Data Exchange in 11.7% of answers, which is more often than the typical company in its sector at 1.7%. Its overall score is 38 out of 100, ranking 402nd of 2,219 companies. The company's website passes 4 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned The Credit Union Data Exchange by name. AI assistants named it in 7 of the 60 answers. Counting only how often it is named, it ranks 100th of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Overall score
38Overall score
  • Visibility26
  • Citations4
  • Sentiment50
  • Site quality93
  • AI readiness29
Summary of account
Named by AI in
11.7%
7 of 60 answers
Share of mentions
70.0%
of the mentions of it and its 5 peers
AI readiness
4/14
technical checks passed. Typical for its sector: 4
Rank in its sector
127 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

The Credit Union Data Exchange came up on 5 of 15 questions. Open any window to read that answer.

  1. 01How do shared data networks help credit unions identify lending trends and member needs?1/4
  2. 02Are there ongoing fees or revenue-sharing models for participants in credit union data analytics networks?3/4
  3. 03What should credit unions consider before signing up for a cooperative data analytics platform?0/4
  4. 04Credit union data analytics networks vs traditional internal analytics approaches0/4
  5. 05Typical costs of joining a credit union cooperative data network in the United States0/4
  6. 06How can credit unions address privacy and compliance concerns in shared data environments?0/4
  7. 07Which credit union analytics network features are most important for maximizing data-driven innovation?0/4
  8. 08How does participation in a data-sharing consortium compare to using standalone analytics software for credit unions?0/4
  9. 09Best ways credit unions can leverage shared data for operational insights1/4
  10. 10Alternatives to joining a cooperative data analytics network for credit unions seeking advanced insights0/4
  11. 11What other data analytics options are available for credit unions besides collaborative networks?0/4
  12. 12Common challenges when contributing data to credit union analytics networks and how to resolve them0/4
  13. 13What are the benefits of joining a credit union data analytics network?1/4
  14. 14Is joining a credit union data analytics network worth it for small or midsize credit unions?0/4
  15. 15Innovative ways credit unions use shared analytics networks to create new revenue streams1/4
Total namedOpenAI: 1/15Claude: 5/15Perplexity: 1/15Gemini: 0/15All assistants: 7/60
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

An answer that names the company

Claudenamed the company

“Are there ongoing fees or revenue-sharing models for participants in credit union data analytics networks?”

I'll search for information about credit union data analytics networks and their fee structures.Based on the search results, I can provide you with information about fee and revenue-sharing models in credit union data analytics networks:

Revenue-Sharing Models

Credit unions that contribute data to CUDX (Credit Union Data Exchange) gain access to powerful analytics, benchmarking, and shared insights while earning non-interest income from monetizing anonymized data. This represents a cooperative data-sharing model where participants both contribute data and receive revenue benefits.

Pla …

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.

Share of mentions

CompanyShare
  1. The Credit Union Data Exchange
    70.0%
  2. OnApproach (now Trellance M360)
    30.0%
  3. CU*A (CU*Answers)
    0.0%
  4. CUSolutions Group Analytics Consulting Services
    0.0%
  5. ProcessUnity for Credit Unions (formerly SilverCloud)
    0.0%
  6. Jack Henry Credit Union Data Solutions
    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
    cucollaborate.com
    20
  2. 02
    creditunions.com
    16
  3. 03
    cuinsight.com
    14
  4. 04
    cu-2.com
    12
  5. 05
    filene.org
    11
  6. 06
    cudx.com (its own website)
    11
  7. 07
    cumanagement.com
    9
  8. 08
    cuanswers.com
    7
  9. 09
    cdn2.hubspot.net
    7
  10. 10
    visbanking.com
    6

The Credit Union Data Exchange is in the study as a fintech infrastructure company.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Claude
5/15
OpenAI
1/15
Perplexity
1/15
Gemini
0/15
Market comparisonSection 06

How The Credit Union Data Exchange 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
26

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

Citations
4

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

Sentiment
50

How positively AI describes the company

Site quality
93

How well built the website's own pages are

AI readiness
29

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
38
Ranks 127 of 574. Typical company: 29
Named in answers
11.7%
Ranks 100 of 574. Typical company: 1.7%
AI readiness
29
Ranks 224 of 574. Typical company: 29
Against its categorySection 08

Compared with fintech infrastructure companies

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

Overall score
38
Ranks 54 of 315. Typical company: 28
Named in answers
11.7%
Ranks 41 of 315. Typical company: 1.7%
AI readiness
29
Ranks 117 of 315. 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. The Credit Union Data Exchange 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
72 of 100
  • robots.txtPassed

    A valid robots.txt with crawl rules at the site root.

    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
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
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 24 of 100 · 97% of checks could run · checked on October 9, 2026 · cudx.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

4 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

  • 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

Share this result

Overall score 38 of 100 badge for The Credit Union Data Exchange

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/cudx.com"><img src="https://aeo-audit.rezolve.com/finance/badges/cudx.com.svg" alt="Overall score 38 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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