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.
395 of 2,219
its rank by overall score
Closing balance

Named in

8of 60 answers

by 4 of 4 assistants

Statement note

What this means for Nova Credit

AI assistants name Nova Credit in 13.3% of answers, which is much more often than the typical company in its sector at 3.3%. It has an overall score of 38 out of 100, ranking 395th of 2,219 companies. Its website passes 2 out of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned Nova Credit by name. AI assistants named it in 8 of the 60 answers. Counting only how often it is named, it ranks 22nd of 93 in its sector. The typical lending and credit company is named in 3.3% of answers.

Overall score
38Overall score
  • Visibility14
  • Citations2
  • Sentiment88
  • Site quality87
  • AI readiness14
Summary of account
Named by AI in
13.3%
8 of 60 answers
Share of mentions
17.4%
of the mentions of it and its 5 peers
AI readiness
2/14
technical checks passed. Typical for its sector: 4
Rank in its sector
15 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

Nova Credit came up on 3 of 15 questions. Open any window to read that answer.

  1. 01Are there cost differences between pay-per-use and subscription models for credit analytics platforms?0/4
  2. 02How can financial institutions use alternative credit data to reach underbanked consumers?0/4
  3. 03Which credit analytics solutions help lenders assess applicants with thin or no traditional credit files?1/4
  4. 04What are some practical ways to integrate alternative data analytics into existing underwriting workflows?0/4
  5. 05Which financial data platforms support international credit histories for US-based lenders?4/4
  6. 06What should businesses expect to pay for access to alternative credit data infrastructure platforms?0/4
  7. 07Do alternative credit data providers offer improved underwriting capabilities compared to conventional methods?0/4
  8. 08Is investing in a unified credit data platform worth it for growing a lending business?0/4
  9. 09How do credit data infrastructure platforms compare to traditional credit bureau reports for risk assessment?0/4
  10. 10How can businesses resolve mismatched or incomplete data when analyzing alternative credit sources?0/4
  11. 11What are the best platforms for accessing unified alternative consumer credit data for underwriting?3/4
  12. 12What other options exist for lenders who want to supplement traditional credit scores with additional risk assessment tools?0/4
  13. 13Why might a credit data platform fail to pull current financial information from multiple sources?0/4
  14. 14Alternative credit data aggregators vs. manual document verification: which is more efficient for financial institutions?0/4
  15. 15What are some alternatives to using automated credit data infrastructure for assessing thin-file applicants?0/4
Total namedOpenAI: 2/15Claude: 2/15Perplexity: 3/15Gemini: 1/15All assistants: 8/60
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

An answer that names the company

OpenAInamed the company

“Which financial data platforms support international credit histories for US-based lenders?”

Short answer

Nova Credit (Credit Passport / Credit Passport API) is the primary U.S.-facing provider that explicitly packages and “translates” foreign consumer credit files into a U.S.-style report that U.S. lenders can consume. (novacredit.com)

Other options and approaches used by U.S. lenders

The large global bureaus (Equifax, Experian, TransUnion) can provide cross‑border solutions by relying on their local country operations or bureau partners. In practice these are country‑by‑country feeds (not a single global consumer file) and availabi …

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
    Plaid
    8
  2. 02
    Argyle
    1

Share of mentions

CompanyShare
  1. Experian (Experian Alternative Credit Data)
    30.4%
  2. Equifax (Equifax Alternative Data Solutions)
    19.6%
  3. Nova Credit
    17.4%
  4. Plaid
    17.4%
  5. TransUnion (TruVision Alternative Data)
    13.0%
  6. Argyle
    2.2%
ReferrersSection 04

Websites the AI used as sources

How many times each website was listed as a source in these answers

  1. 01
    credolab.com
    24
  2. 02
    experian.com
    23
  3. 03
    plaid.com
    17
  4. 04
    stripe.com
    14
  5. 05
    lendflow.com
    12
  6. 06
    equifax.com
    10
  7. 07
    novacredit.com (its own website)
    10
  8. 08
    federalreserve.gov
    8
  9. 09
    kansascityfed.org
    8
  10. 10
    crscreditapi.com
    7

Nova Credit is in the study as a credit bureau or scoring company.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

Perplexity
3/15
Claude
2/15
OpenAI
2/15
Gemini
1/15
Market comparisonSection 06

How Nova Credit 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
14

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
88

How positively AI describes the company

Site quality
87

How well built the website's own pages are

AI readiness
14

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
38
Ranks 15 of 93. Typical company: 31
Named in answers
13.3%
Ranks 22 of 93. Typical company: 3.3%
AI readiness
14
Ranks 76 of 93. Typical company: 29
Against its categorySection 08

Compared with credit bureaus and scoring companies

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

Overall score
38
Ranks 5 of 13. Typical company: 37
Named in answers
13.3%
Ranks 8 of 13. Typical company: 16.7%
AI readiness
14
Ranks 11 of 13. Typical company: 21
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. Nova Credit 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
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
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 25 of 100 · 97% of checks could run · checked on October 9, 2026 · www.novacredit.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

2 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%
  • Not metHTTP Link headers (RFC 8288)study: 42.5%

Content Accessibility

  • Not metMarkdown content negotiationstudy: 7.4%
  • Not metllms.txt publishedstudy: 28.1%
  • Not metToken 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

  • 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 38 of 100 badge for Nova Credit

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/novacredit.com"><img src="https://aeo-audit.rezolve.com/finance/badges/novacredit.com.svg" alt="Overall score 38 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
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