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

Named in

23of 60 answers

by 4 of 4 assistants

Statement note

What this means for Plaid

AI assistants name this fintech infrastructure company in 38.3% of answers, much more often than the typical company in its sector at 1.7%. Its overall score is 41 out of 100, ranking 162nd of 2,219 companies. Its website passes 4 out of 14 technical checks for readiness for AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Plaid by name. AI assistants named it in 23 of the 60 answers. Counting only how often it is named, it ranks 13th of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Overall score
41Overall score
  • Visibility36
  • Citations4
  • Sentiment60
  • Site quality80
  • AI readiness29
Summary of account
Named by AI in
38.3%
23 of 60 answers
Share of mentions
35.9%
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
54 of 574
by overall score, where the typical financial technology and data company scores 29

Get the full report on Plaid as a PDF

Enter your work email to download it.

We’ll use your email to follow up about this report. Privacy policy

Line itemsSection 01

Every question, and where the company came up

Plaid came up on 10 of 15 questions. Open any window to read that answer.

  1. 01What’s the difference between open banking platforms and traditional data aggregation solutions?1/4
  2. 02Is using a financial data connectivity platform worth it for a small fintech startup?2/4
  3. 03What are alternatives to using a unified financial data API for connecting user accounts?3/4
  4. 04What should developers look for when choosing an API to access user financial data?0/4
  5. 05How do businesses connect user bank accounts to their fintech services?4/4
  6. 06What open source options exist for aggregating US bank account data securely?4/4
  7. 07Account aggregation APIs vs direct bank integrations: which is better for fintech products?2/4
  8. 08What are effective ways to use financial data APIs for fraud detection?0/4
  9. 09How can I handle missing transaction data when integrating a financial data API?1/4
  10. 10Are there usage-based pricing models for financial data APIs?0/4
  11. 11How can fintech companies build their own bank integrations without third-party platforms?0/4
  12. 12How can real-time banking data be used to improve credit underwriting for lenders?0/4
  13. 13Why do some bank connections fail during user onboarding in fintech apps?1/4
  14. 14How much do financial data connectivity services typically cost for US businesses?1/4
  15. 15What are the best financial data API platforms for building fintech apps in the US?4/4
Total namedOpenAI: 5/15Claude: 5/15Perplexity: 4/15Gemini: 9/15All assistants: 23/60
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

“What are alternatives to using a unified financial data API for connecting user accounts?”

Good question — a unified financial-data API (like Plaid, MX, TrueLayer, etc.) is convenient, but it’s not the only way to connect user accounts. Below are the main alternative approaches, with pros/cons and practical notes so you can pick what fits your product.

1. Direct bilateral integrations with individual institutions

What: Build one-off API integrations with each bank/credit-card issuer/financial provider you need.

Pros: Best data fidelity and control, custom features, direct SLA/security relationship, avoid third‑party vendor fees.

Cons: Very high engineering and maintenance cos …

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
    MX
    16
  2. 02
    Akoya
    4
  3. 03
    Flinks
    1
  4. 04
    Finicity
    1

Share of mentions

CompanyShare
  1. Plaid
    35.9%
  2. MX
    23.4%
  3. Finicity
    18.8%
  4. Yodlee (Envestnet | Yodlee)
    14.1%
  5. Akoya
    6.3%
  6. Flinks
    1.6%
ReferrersSection 04

Websites the AI used as sources

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

  1. 01
    plaid.com (its own website)
    18
  2. 02
    openbankingtracker.com
    18
  3. 03
    stripe.com
    15
  4. 04
    g2.com
    12
  5. 05
    apideck.com
    10
  6. 06
    github.com
    9
  7. 07
    mx.com
    6
  8. 08
    fintechspecs.com
    6
  9. 09
    fintegrationfs.com
    5
  10. 10
    mastercard.com
    5

Plaid 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

Gemini
9/15
Claude
5/15
OpenAI
5/15
Perplexity
4/15
Market comparisonSection 06

How Plaid 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
36

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

Citations
4

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

Sentiment
60

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 financial technology and data companies

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

Overall score
41
Ranks 54 of 574. Typical company: 29
Named in answers
38.3%
Ranks 13 of 574. Typical company: 1.7%
AI readiness
29
Ranks 224 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
41
Ranks 21 of 315. Typical company: 28
Named in answers
38.3%
Ranks 3 of 315. Typical company: 1.7%
AI readiness
29
Ranks 117 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 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. Plaid 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
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 · plaid.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%
  • Not metHTTP 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.

Take it with you

Get the full report on Plaid as a PDF

Every number on this page in a PDF you can keep and share with your team. Enter your work email to download it.

We’ll use your email to follow up about this report. Privacy policy

ShareSection 12

Share this result

Overall score 41 of 100 badge for Plaid

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/plaid.com"><img src="https://aeo-audit.rezolve.com/finance/badges/plaid.com.svg" alt="Overall score 41 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
Next step

Want AI assistants to name your company?

Book a 30-minute demo to see Rezolve Ai in action and what it can do for your business.

Request a demo