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

ChargeAfter

chargeafter.com

Buy now, pay laterCards and payments

Money20/20 attendee

Statement period
October 9 and 10, 2026
when the AI assistants were asked
Account no.
158 of 2,219
its rank by overall score
Place in its category
2nd of 15 buy now, pay later providers
Closing balance

Named in

4of 60 answers

by 4 of 4 assistants

Statement note

What this means for ChargeAfter

AI assistants name this buy now, pay later provider in 6.7% of answers. This is higher than the typical company in its sector, which is named in 0% of answers. It has an overall score of 42 out of 100, ranking 158th of 2,219 companies. The website passes 7 out of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned ChargeAfter by name. AI assistants named it in 4 of the 60 answers. Counting only how often it is named, it ranks 90th of 375 in its sector. The typical cards and payments company is named in 0.0% of answers.

Overall score
42Overall score
  • Visibility10
  • Citations12
  • Sentiment88
  • Site quality87
  • AI readiness50
Summary of account
Named by AI in
6.7%
4 of 60 answers
Share of mentions
19.0%
of the mentions of it and its 5 peers
AI readiness
7/14
technical checks passed. Typical for its sector: 4
Rank in its sector
23 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

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

  1. 01How can merchants increase approval rates for embedded lending at the point of sale?0/4
  2. 02How can financial institutions enable point-of-sale lending solutions for their merchant partners?0/4
  3. 03Are there non-lending ways for merchants to provide flexible payment options at checkout?0/4
  4. 04What features should enterprises look for in a turnkey point-of-sale consumer financing platform?0/4
  5. 05How do embedded lending platforms improve customer experience for large merchants?0/4
  6. 06How does embedded consumer lending compare to traditional consumer credit options at checkout?0/4
  7. 07What are common industries using embedded point-of-sale lending platforms to boost sales?0/4
  8. 08Point-of-sale financing platform vs. buy now pay later providers — what are the main differences?0/4
  9. 09What are the best embedded consumer lending platforms for enterprise merchants looking to offer point-of-sale financing?4/4
  10. 10Is implementing a multi-lender embedded financing platform worth it for large online retailers?0/4
  11. 11Do enterprise merchants benefit more from offering in-store or online point-of-sale consumer finance solutions?0/4
  12. 12What typical fees or costs should merchants expect with embedded consumer finance solutions?0/4
  13. 13How do multi-lender POS financing platforms structure their pricing tiers for enterprise clients?0/4
  14. 14Why might a consumer application for point-of-sale financing get declined at checkout?0/4
  15. 15What are alternatives to embedded lending solutions for merchants wanting to offer promotional financing?0/4
Total namedOpenAI: 1/15Claude: 1/15Perplexity: 1/15Gemini: 1/15All assistants: 4/60
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 Perplexity actually said

An answer that names the company

Perplexitynamed the company

“What are the best embedded consumer lending platforms for enterprise merchants looking to offer point-of-sale financing?”

For enterprise merchants, the strongest shortlist is ChargeAfter, Affirm, Klarna, Synchrony, Bread Pay, and FinMkt. The best choice depends on whether the priority is lender orchestration, a branded single-lender program, broad consumer reach, or control over underwriting and servicing.

Platform · Best for · Why enterprise merchants consider it

ChargeAfter · Multi-lender POS financing · Connects merchants to a network of lenders, supports personalized offers, and is designed for omnichannel retail financing.

Affirm · Premium, high-ticket purchases …

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
    Affirm
    12
  2. 02
    FinMkt
    5
  3. 03
    Bread Financial
    2

Share of mentions

CompanyShare
  1. Affirm
    47.6%
  2. FinMkt
    23.8%
  3. ChargeAfter
    19.0%
  4. Bread Financial
    9.5%
  5. Crest Financial
    0.0%
  6. ChargeItSpot (POS Financing by GreenSky)
    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
    chargeafter.com (its own website)
    46
  2. 02
    finmkt.io
    17
  3. 03
    shopify.com
    12
  4. 04
    lendflow.com
    10
  5. 05
    lendfoundry.com
    9
  6. 06
    finastra.com
    8
  7. 07
    jifiti.com
    7
  8. 08
    ezbob.com
    7
  9. 09
    turnkey-lender.com
    6
  10. 10
    mckinsey.com
    5

ChargeAfter is in the study as a buy now, pay later provider.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

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

How ChargeAfter 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
10

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

Citations
12

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

Sentiment
88

How positively AI describes the company

Site quality
87

How well built the website's own pages are

AI readiness
50

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
42
Ranks 23 of 375. Typical company: 27
Named in answers
6.7%
Ranks 90 of 375. Typical company: 0.0%
AI readiness
50
Ranks 7 of 375. Typical company: 29
Against its categorySection 08

Compared with buy now, pay later providers

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

Overall score
42
Ranks 2 of 15. Typical company: 37
Named in answers
6.7%
Ranks 9 of 15. Typical company: 16.7%
AI readiness
50
Ranks 2 of 15. 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. ChargeAfter 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.txtPublished
  • 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
50 of 100
  • Markdown negotiationNot met

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

    study: 6.2%
  • llms.txtPassed

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

    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 42 of 100 · 97% of checks could run · checked on October 9, 2026 · chargeafter.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

7 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%
  • 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

  • Not metAPI 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

  • 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.

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ShareSection 12

Share this result

Overall score 42 of 100 badge for ChargeAfter

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/chargeafter.com"><img src="https://aeo-audit.rezolve.com/finance/badges/chargeafter.com.svg" alt="Overall score 42 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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