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.
1,647 of 2,219
its rank by overall score
Place in its category
42nd of 62 consumer lenders
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for PayJoy

AI assistants do not name this consumer lender in any of their 60 answers, while they often mention others such as Affirm and Snap Finance. Its overall score is 26 out of 100, ranking it 1,647th of 2,219 companies. The website passes 4 of 14 technical checks showing some readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned PayJoy by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 56th of 93 in its sector. The typical lending and credit company is named in 3.3% 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
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality80
  • AI readiness29
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
4/14
technical checks passed. Typical for its sector: 4
Rank in its sector
65 of 93
by overall score, where the typical lending and credit company scores 31

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Line itemsSection 01

Every question, and where the company came up

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

  1. 01Average monthly payments for phone financing with minimal credit requirements0/4
  2. 02What should I know before applying for alternative credit solutions for phones?0/4
  3. 03Best phone financing options for people with no credit history0/4
  4. 04Why was I asked for additional documents when seeking phone financing?0/4
  5. 05Phone financing vs traditional personal loans for credit-invisible consumers0/4
  6. 06What to do if your phone financing application is denied due to no credit0/4
  7. 07How to get a smartphone with limited credit in the US0/4
  8. 08Alternatives to phone financing for people without traditional credit0/4
  9. 09Are there extra fees when using credit solutions for smartphones with no credit check?0/4
  10. 10How to access fast small cash loans without a credit report0/4
  11. 11Installment plans compared to lease-to-own for new smartphones0/4
  12. 12Is phone financing worth it for someone with limited credit?0/4
  13. 13What are some non-credit-based ways to buy a smartphone in the US?0/4
  14. 14How to use alternative credit providers to build credit for future purchases0/4
  15. 15Options for upgrading to a new phone if you have no credit history0/4
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 Gemini actually said

The company is not named in this answer

Geminidid not name the company

“Average monthly payments for phone financing with minimal credit requirements”

Many options exist for phone financing with minimal credit requirements, often through lease-to-own programs, prepaid plans, or specific carrier programs. The average monthly payments can vary significantly based on the chosen phone, plan, and provider.

Here's a breakdown of what you can expect:

1. Lease-to-Own Programs:

Companies like Abunda, SmartPay, and Progressive Leasing offer lease-to-own options that often require no credit check or welcome those with bad credit.

Abunda shows examples of monthly payments as low as $12, $16, or $21 for unlocked cell phones.

These progr …

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
    Affirm
    10
  2. 02
    Acima
    2
  3. 03
    Snap Finance
    1

Share of mentions

CompanyShare
  1. Affirm
    45.2%
  2. Progressive Leasing (Progressive Mobile Solutions)
    28.6%
  3. Acima
    21.4%
  4. Snap Finance
    4.8%
  5. PayJoy
    0.0%
  6. SmartPay Lease
    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
    thecreditpeople.com
    17
  2. 02
    whistleout.com
    12
  3. 03
    finder.com
    10
  4. 04
    1firstcashadvance.org
    9
  5. 05
    opploans.com
    8
  6. 06
    alibaba.com
    8
  7. 07
    apple.com
    8
  8. 08
    experian.com
    7
  9. 09
    moneylion.com
    6
  10. 10
    meetava.com
    6

PayJoy is in the study as a consumer lender.

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 PayJoy 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
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 lending and credit companies

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

Overall score
26
Ranks 65 of 93. Typical company: 31
Named in answers
0.0%
Ranks 56 of 93. Typical company: 3.3%
AI readiness
29
Ranks 24 of 93. Typical company: 29
Against its categorySection 08

Compared with consumer lenders

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

Overall score
26
Ranks 39 of 62. Typical company: 28
Named in answers
0.0%
Ranks 34 of 62. Typical company: 1.7%
AI readiness
29
Ranks 16 of 62. 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. PayJoy 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 · www.payjoy.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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