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 to 14, 2026
when the AI assistants were asked
Account no.
622 of 2,219
its rank by overall score
Closing balance

Named in

7of 60 answers

by 4 of 4 assistants

Statement note

What this means for Casap

AI assistants name this fraud and identity company in 11.7% of answers, which is more often than the typical company in its sector at 1.7%. Its overall score is 35 out of 100, ranking 622nd of 2,219 companies. The website passes 2 of 14 technical checks for readiness with AI tools.

We asked 15 unbranded questions about its market, so no question mentioned Casap by name. AI assistants named it in 7 of the 60 answers. Counting only how often it is named, it ranks 100th of 574 in its sector. The typical financial technology and data company is named in 1.7% of answers.

Overall score
35Overall score
  • Visibility17
  • Citations1
  • Sentiment75
  • Site quality80
  • AI readiness14
Summary of account
Named by AI in
11.7%
7 of 60 answers
Share of mentions
31.8%
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
199 of 574
by overall score, where the typical financial technology and data company scores 29

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Line itemsSection 01

Every question, and where the company came up

Casap came up on 4 of 15 questions. Open any window to read that answer.

  1. 01What are the best AI-driven solutions for automating dispute management in financial institutions?1/4
  2. 02How can automated dispute management help financial institutions stay compliant with US regulations such as Reg-E or Reg-Z?0/4
  3. 03What are manual options for managing dispute and fraud claims in banks, and how do they compare to AI automation?0/4
  4. 04AI dispute automation platforms vs traditional workflow automation software—what's the difference for financial institutions?0/4
  5. 05Which platforms offer automated fraud and dispute resolution for credit unions and banks in the US?4/4
  6. 06How do manual dispute management processes compare to AI-powered automation tools?0/4
  7. 07What should banks consider before choosing an AI platform for dispute automation?0/4
  8. 08What are frequent challenges banks face when automating fraud resolution workflows with AI solutions?0/4
  9. 09What is the typical cost structure for AI-driven dispute automation platforms for fintech companies?1/4
  10. 10Alternatives to AI-based dispute automation for financial institutions looking to streamline resolution processes.0/4
  11. 11Is investing in an AI-based dispute management system worth it for a mid-sized credit union?1/4
  12. 12Are there affordable solutions for small banks seeking AI dispute and fraud management?0/4
  13. 13Examples of how AI-powered agents improve customer satisfaction during dispute resolution in banking.0/4
  14. 14Which features should banks look for in an automated dispute resolution platform to maximize efficiency and compliance?0/4
  15. 15How can financial institutions address common issues when integrating AI dispute resolution platforms?0/4
Total namedOpenAI: 2/15Claude: 2/15Perplexity: 1/15Gemini: 2/15All assistants: 7/60
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

An answer that names the company

Gemininamed the company

“Which platforms offer automated fraud and dispute resolution for credit unions and banks in the US?”

A number of platforms offer automated fraud and dispute resolution for credit unions and banks in the U.S., leveraging AI and machine learning to streamline processes and enhance detection capabilities. These platforms aim to reduce manual effort, improve efficiency, ensure regulatory compliance, and ultimately strengthen customer relationships.

Some of the prominent platforms and their offerings include:

Casap Casap offers an AI platform that automates payment disputes and prevents first-party fraud. It integrates with existing financial institution systems and supports various tran …

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
    Quavo
    5
  2. 02
    Chargebacks911
    3

Share of mentions

CompanyShare
  1. Quavo
    50.0%
  2. Casap
    31.8%
  3. Chargebacks911
    18.2%
  4. Fiserv (FraudNet & Dispute Solutions)
    0.0%
  5. Amount (formerly Accelitas Dispute IQ)
    0.0%
  6. VeriFacts Dispute Management
    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
    quavo.com
    22
  2. 02
    usefini.com
    19
  3. 03
    ey.com
    13
  4. 04
    backbase.com
    11
  5. 05
    guideflow.com
    9
  6. 06
    highradius.com
    8
  7. 07
    finboa.com
    6
  8. 08
    thefinancialbrand.com
    6
  9. 09
    lyzr.ai
    5
  10. 10
    slideshare.net
    5

Casap is in the study as a fraud and identity company.

By assistantSection 05

Which AI assistants named the company

Answers naming it, out of answers received

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

How Casap 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
17

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

Citations
1

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

Sentiment
75

How positively AI describes the company

Site quality
80

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 financial technology and data companies

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

Overall score
35
Ranks 199 of 574. Typical company: 29
Named in answers
11.7%
Ranks 100 of 574. Typical company: 1.7%
AI readiness
14
Ranks 504 of 574. Typical company: 29
Against its categorySection 08

Compared with fraud and identity companies

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

Overall score
35
Ranks 69 of 171. Typical company: 30
Named in answers
11.7%
Ranks 21 of 171. Typical company: 1.7%
AI readiness
14
Ranks 156 of 171. Typical company: 36
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 0: Not yet agent-ready. Agents struggle to find basic information about the site.

To reach level 1:
  • 2 of robots.txt, Sitemap, Link headers
Can an AI agent check out here?

Not by itself. Casap 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
0 of 100
  • robots.txtNot met

    Publish a valid robots.txt with crawl rules and a Sitemap line.

    study: 86.1%
  • SitemapNot 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 7 of 100 · 97% of checks could run · checked on October 9, 2026 · www.casaphq.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

  • Not metrobots.txt publishedstudy: 85.1%
  • Not metXML 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%
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ShareSection 11

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Overall score 35 of 100 badge for Casap

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/casaphq.com"><img src="https://aeo-audit.rezolve.com/finance/badges/casaphq.com.svg" alt="Overall score 35 of 100, Finance AI Visibility Study 2026" width="280" height="64"></a>
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