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

Paymend

paymend.com

Payment processors, acquirers and point of saleCards and payments

Money20/20 attendee

Statement period
October 9 to 14, 2026
when the AI assistants were asked
Account no.
1,468 of 2,219
its rank by overall score
Place in its category
117th of 203 payment processors
Closing balance

Named in

1of 60 answers

by 1 of 4 assistants

Statement note

What this means for Paymend

AI assistants rarely name this payment processor, appearing in 1 of 60 answers. In the same answer, Recurly and Checkout.com are also named. Its overall score is 26 out of 100, ranking 1,468th of 2,219 overall and 229th of 375 in its sector. The website passes 4 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Paymend by name. AI assistants named it in 1 of the 60 answers. Counting only how often it is named, it ranks 133rd 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
26Overall score
  • Visibility3
  • Citations2
  • Sentiment50
  • Site quality73
  • AI readiness29
Summary of account
Named by AI in
1.7%
1 of 60 answers
Share of mentions
7.7%
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
229 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

Paymend came up on 1 of 15 questions. Open any window to read that answer.

  1. 01Does using an AI-powered payment recovery engine help boost approval rates significantly for e-commerce stores?0/4
  2. 02What are low-tech options for improving approval rates on e-commerce payment transactions?0/4
  3. 03What are some manual methods to recover failed payments if you don’t use an automated platform?0/4
  4. 04What’s the typical pricing structure for AI-powered revenue recovery platforms used by online merchants?0/4
  5. 05AI-driven payment recovery platforms vs traditional payment retry methods—what’s more effective for reducing involuntary churn?0/4
  6. 06Why are my recurring payments failing even after using a payment recovery tool?0/4
  7. 07How do machine learning-based revenue recovery solutions compare to rule-based systems for failed transactions?0/4
  8. 08How can online merchants improve revenue recovery from declined transactions using automation?0/4
  9. 09What are the best AI-powered tools for recovering failed online payments for e-commerce businesses?0/4
  10. 10How do payment recovery platforms charge—flat fee, percentage of recovered revenue, or subscription?0/4
  11. 11How can businesses minimize customer churn caused by failed online payments?0/4
  12. 12What types of e-commerce businesses can benefit most from automated payment recovery technology?0/4
  13. 13Alternatives to AI-driven payment recovery engines for reducing failed transaction losses0/4
  14. 14Is investing in an automated payment recovery platform worth it for a small to midsize online retailer?0/4
  15. 15How do AI-powered payment solutions help reduce costs and recover lost sales for subscription-based sites?1/4
Total namedOpenAI: 0/15Claude: 0/15Perplexity: 0/15Gemini: 1/15All assistants: 1/60
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 Gemini actually said

An answer that names the company

Gemininamed the company

“How do AI-powered payment solutions help reduce costs and recover lost sales for subscription-based sites?”

… High Recovery Rates: AI-powered recovery engines can recapture a significant portion of failed payments, with some solutions recovering up to 75% of failed payments verslay.com and others demonstrating a 12.69% payment recovery rate, leading to millions in recovered revenue paymend.com.

3. Reducing Processing Costs:

Authorization Boost: Solutions like Stripe's Authorization Boost increase acceptance …

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
    Recurly
    4
  2. 02
    Checkout.com
    1

Share of mentions

CompanyShare
  1. Recurly
    53.8%
  2. Checkout.com
    38.5%
  3. Paymend
    7.7%
  4. dLocal Go
    0.0%
  5. BlueSnap
    0.0%
  6. Gr4vy
    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
    slickerhq.com
    50
  2. 02
    stripe.com
    8
  3. 03
    flycode.com
    8
  4. 04
    checkoutchamp.com
    6
  5. 05
    f6s.com
    6
  6. 06
    solidgate.com
    5
  7. 07
    bams.com
    5
  8. 08
    sourceforge.net
    5
  9. 09
    y.uno
    5
  10. 10
    reduxpayments.com
    5

Paymend is in the study as a payment processor.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

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

How Paymend 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
3

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
50

How positively AI describes the company

Site quality
73

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 cards and payments companies

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

Overall score
26
Ranks 229 of 375. Typical company: 27
Named in answers
1.7%
Ranks 133 of 375. Typical company: 0.0%
AI readiness
29
Ranks 106 of 375. Typical company: 29
Against its categorySection 08

Compared with payment processors

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

Overall score
26
Ranks 115 of 203. Typical company: 27
Named in answers
1.7%
Ranks 64 of 203. Typical company: 0.0%
AI readiness
29
Ranks 59 of 203. 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 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
Can an AI agent check out here?

Not by itself. Paymend 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
36 of 100
  • robots.txtNot met

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

    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
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 15 of 100 · 97% of checks could run · checked on October 9, 2026 · www.paymend.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%
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End of statement
All 2,219 companiesHow we measured this
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