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

Fintoc

fintoc.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.
898 of 2,219
its rank by overall score
Place in its category
124th of 315 fintech infrastructure companies
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for Fintoc

AI assistants do not name this fintech infrastructure company in any of the 60 answers, instead mentioning companies like Stripe, Square, and Adyen. Its overall score is 30 out of 100, ranking 898th of 2,219 in the study and 253rd of 574 in its sector. Its website passes 9 of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Fintoc by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 334th of 574 in its sector. The typical financial technology and data company is named in 1.7% 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
30Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality80
  • AI readiness64
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
9/14
technical checks passed. Typical for its sector: 4
Rank in its sector
253 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

Fintoc came up on 0 of 15 questions. Open any window to read that answer.

  1. 01Hosted checkout vs. embedded payment forms for small businesses: pros and cons?0/4
  2. 02ACH transfers vs. credit card processing: which is better for minimizing fees?0/4
  3. 03Options for automating payment flows without using a third-party API?0/4
  4. 04Are advanced analytics and dashboard features essential when choosing a payment API for my business?0/4
  5. 05How can I resolve issues with delayed deposit settlements in my payment operations?0/4
  6. 06How can a payment platform improve acceptance rates and reduce failed transactions for ecommerce stores?0/4
  7. 07How do payment APIs help automate subscription billing for digital businesses?0/4
  8. 08Why do online payments sometimes fail even when customers have sufficient funds?0/4
  9. 09What are some alternatives to ACH for accepting business-to-business payments online?0/4
  10. 10What are typical transaction fees for payment processing platforms in the United States?0/4
  11. 11Is it worth switching to an all-in-one payment management platform for handling high transaction volumes?0/4
  12. 12Which platforms support both one-time and recurring digital payments for US-based businesses?0/4
  13. 13What are common ways SaaS companies use payment APIs to manage recurring payments?0/4
  14. 14How do payment gateway subscription costs compare for startups vs. enterprise businesses?0/4
  15. 15What are the best payment processing platforms for online businesses in the US?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 OpenAI actually said

The company is not named in this answer

OpenAIdid not name the company

“ACH transfers vs. credit card processing: which is better for minimizing fees?”

Short answer

ACH is almost always cheaper per dollar than credit cards for U.S. payments. Use ACH when minimizing fees is your main goal and you can tolerate slower settlement. (stripe.com)

Why (summary of the cost tradeoffs)

Typical credit-card merchant costs: ~1.5%–3.5% of the transaction plus a small fixed cents component (e.g., 2.9% + $0.30 is common for online retail). That rate includes interchange (card‑issuer) + network + processor markup. These percentage fees make cards expensive for large-dollar transaction …

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
    Stripe
    13
  2. 02
    Square
    9
  3. 03
    Adyen
    6
  4. 04
    Authorize.Net
    2

Share of mentions

CompanyShare
  1. Stripe
    38.9%
  2. Adyen
    22.2%
  3. Square
    18.5%
  4. Authorize.Net
    11.1%
  5. Braintree (a PayPal service)
    9.3%
  6. Fintoc
    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
    17
  2. 02
    airwallex.com
    10
  3. 03
    wise.com
    9
  4. 04
    solidgate.com
    7
  5. 05
    cashfree.com
    7
  6. 06
    connectpay.com
    5
  7. 07
    bams.com
    5
  8. 08
    helcim.com
    4
  9. 09
    whop.com
    4
  10. 10
    squareup.com
    4

Fintoc 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
0/15
Gemini
0/15
OpenAI
0/15
Perplexity
0/15
Market comparisonSection 06

How Fintoc 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
80

How well built the website's own pages are

AI readiness
64

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
30
Ranks 253 of 574. Typical company: 29
Named in answers
0.0%
Ranks 334 of 574. Typical company: 1.7%
AI readiness
64
Ranks 3 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
30
Ranks 117 of 315. Typical company: 28
Named in answers
0.0%
Ranks 168 of 315. Typical company: 1.7%
AI readiness
64
Ranks 2 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 4: Agent-integrated. At least one of an MCP card, A2A card, skills index or API catalog is published.

To reach level 5:
  • Web Bot Auth
  • 4 of MCP Server Card, A2A Agent Card, Agent Skills, API Catalog
Can an AI agent check out here?

Not by itself. Fintoc 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 CardPublished
  • A2A Agent CardNot present
  • Agent SkillsNot present
  • API CatalogPublished
  • llms.txtPublished
  • WebMCPCould not check
Show every check, for your technical team
Discoverability
100 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 headersPassed

    HTTP Link headers on the homepage that point agents at machine readable resources.

    study: 1.5%
  • DNS for AI DiscoveryPassed

    SVCB or HTTPS records under _agents that advertise agent endpoints.

    study: 4.3%
Content accessibility
100 of 100
  • Markdown negotiationPassed

    Requests sent with Accept: text/markdown receive a markdown version of the page.

    study: 6.2%
  • llms.txtPassed

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

    study: 31.0%
Bot access control
68 of 100
  • AI bot rulesPartly met

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

    study: 92.7%
  • Content SignalsPassed

    Content-Signal lines in robots.txt declaring search, AI input and AI training preferences.

    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
52 of 100
  • API CatalogPassed

    A linkset at /.well-known/api-catalog listing APIs, specs and docs.

    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 CardPartly 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 78 of 100 · 97% of checks could run · checked on October 9, 2026 · www.fintoc.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

9 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%
  • 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

  • PassedAPI Catalog (.well-known/api-catalog)study: 1.1%
  • PassedOAuth 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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End of statement
All 2,219 companiesHow we measured this
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