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, 2026
when the AI assistants were asked
Account no.
1,099 of 2,219
its rank by overall score
Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for Bloom Credit

AI assistants do not name this credit bureau or scoring company in any of their 60 answers to everyday market questions. Its overall score is 28 out of 100, which ranks it 1,099th of 2,219 companies in the study. Its website passes 5 of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Bloom Credit 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
28Overall score
  • Visibility0
  • Citations0
  • Sentiment50
  • Site quality87
  • AI readiness36
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
5/14
technical checks passed. Typical for its sector: 4
Rank in its sector
52 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

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

  1. 01What can cause delays when integrating a new credit data infrastructure into existing systems?0/4
  2. 02How can financial institutions improve consumer-first credit decisions using modern credit data solutions?0/4
  3. 03What are the best credit data infrastructure platforms for powering real-time credit experiences in the US?0/4
  4. 04Which credit data solutions enable the fastest customer onboarding for digital lenders?0/4
  5. 05What are alternatives to using turnkey credit data infrastructure for real-time decisioning?0/4
  6. 06How does traditional credit data processing compare to real-time credit data infrastructure?0/4
  7. 07Credit data platforms vs. custom-built APIs: which is better for fintech companies?0/4
  8. 08What should I look for when choosing a credit data infrastructure solution for my fintech business?0/4
  9. 09Is investing in a modern credit data infrastructure platform worth it for a small lender?0/4
  10. 10How much do credit data infrastructure platforms typically cost for mid-sized financial institutions?0/4
  11. 11What factors impact the pricing tiers of modern credit data APIs?0/4
  12. 12How can credit data infrastructure help automate loan approval processes for financial institutions?0/4
  13. 13What options exist besides modern credit data platforms to access US consumer credit reports?0/4
  14. 14Why isn't my real-time consumer credit data syncing properly in my platform?0/4
  15. 15What are examples of using real-time credit data for risk assessment in consumer lending?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 Gemini actually said

The company is not named in this answer

Geminidid not name the company

“What are the best credit data infrastructure platforms for powering real-time credit experiences in the US?”

For powering real-time credit experiences in the US, several platforms offer robust credit data infrastructure and decisioning capabilities. These platforms typically focus on aggregating data, automating decisions with AI and machine learning, and ensuring compliance.

Some of the best credit data infrastructure platforms for real-time credit experiences in the US include:

Platforms specializing in Credit Decisioning and Automation:

HighRadius: This AI-powered platform automates credit decisioning, standardizes risk evaluation, and provides real-time visibility into customer expo …

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
    Nova Credit
    4
  2. 02
    Pinwheel
    1

Share of mentions

CompanyShare
  1. Nova Credit
    44.4%
  2. PrivoCorp / Credit API
    22.2%
  3. Yodlee Credit Accelerator
    22.2%
  4. Pinwheel
    11.1%
  5. Bloom Credit
    0.0%
  6. iSoftpull
    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
    lendflow.com
    25
  2. 02
    experian.com
    22
  3. 03
    crscreditapi.com
    17
  4. 04
    fintechspecs.com
    11
  5. 05
    plaid.com
    11
  6. 06
    credolab.com
    10
  7. 07
    stripe.com
    8
  8. 08
    creditbenchmark.com
    7
  9. 09
    hesfintech.com
    7
  10. 10
    highradius.com
    7

Bloom 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

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

How Bloom 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
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
87

How well built the website's own pages are

AI readiness
36

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
28
Ranks 52 of 93. Typical company: 31
Named in answers
0.0%
Ranks 56 of 93. Typical company: 3.3%
AI readiness
36
Ranks 9 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
28
Ranks 11 of 13. Typical company: 37
Named in answers
0.0%
Ranks 11 of 13. Typical company: 16.7%
AI readiness
36
Ranks 1 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. Bloom 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.txtPublished
  • WebMCPCould not check

The website runs on WooCommerce.

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
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 36 of 100 · 97% of checks could run · checked on October 9, 2026 · bloomcredit.io · 2,200 companies scanned

See how every company did, and how this was measured.

AI readinessSection 10

The checks behind the AI readiness score

5 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%
  • 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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