AI visibility statementFinance AI Visibility Study 2026Issued October 14, 2026

Account holder

FaceSign

facesign.ai

Fraud, identity and compliance Financial technology and data

Money20/20 attendee

Statement period: October 9 to 14, 2026; when the AI assistants were asked
Account no.: 1,782 of 2,219; its rank by overall score
Place in its category: 157th of 171 fraud and identity companies

Closing balance

Named in

0of 60, its tower is dark

by 0 of 4 assistants

Statement note

What this means for FaceSign

AI assistants do not name this fraud and identity company in any of their 60 answers, while the typical company in its sector is named in 1.7% of answers. Its overall score is 25 out of 100, which ranks 1,782nd of 2,219 companies in the study. Its website passes 1 of 14 technical checks for AI tool readiness.

We asked 15 unbranded questions about its market, so no question mentioned FaceSign by name. AI assistants named it in none of the 60 answers. Counting only how often it is named, it ranks 334th of 574 in its sector. The typical financial technology and data company is named in 1.7% 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

Visibility0
Citations0
Sentiment50
Site quality87
AI readiness7

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: 1/14; technical checks passed. Typical for its sector: 4
Rank in its sector: 486 of 574; by overall score, where the typical financial technology and data company scores 29

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Line items01

Every question, and where the company came up

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

01Liveness detection vs document-based verification for secure user authentication—what are the pros and cons?0/4
02What can cause false positives when detecting deepfakes with AI verification software?0/4
03Most effective approaches to prevent fraud using AI-based user authentication methods?0/4
04Are there affordable options for real-time human proofing in user authentication workflows?0/4
05What are the most reliable AI-driven identity verification platforms for online businesses?0/4
06How much do AI-enabled identity verification platforms typically cost for mid-sized businesses?0/4
07What are effective ways to implement multi-layered identity checks for online account logins?0/4
08Why might an AI identity verification system fail to confirm liveness during a video check?0/4
09Should small businesses switch from SMS and OTP authentication to real-time AI-based user verification?0/4
10Is investing in an AI-powered identity verification solution worth it for a call center handling sensitive transactions?0/4
11What are the best alternatives to traditional biometrics for ensuring proof of humanity in online verification?0/4
12How do real-time human verification systems differ from traditional biometric authentication?0/4
13How can financial institutions use AI-powered authentication to secure high-value wire transfers?0/4
14Which solutions offer secure identity verification without requiring physical documents or in-person checks?0/4
15Best tools to detect deepfakes during remote onboarding processes?0/4

Total named0/150/150/150/150/60

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 detail02

What OpenAI actually said

The company is not named in this answer

OpenAIdid not name the company

“Are there affordable options for real-time human proofing in user authentication workflows?”

Short answer: Yes — there are affordable ways to add real-time (or near‑real‑time) human proofing to authentication flows. The practical choices fall into three groups: (A) identity vendors that include 24/7 human/manual review as an add‑on, (B) lower‑cost specialist providers or “human review” marketplaces, and (C) hybrid / in‑house patterns that reduce how often humans are needed. Which is most cost‑effective depends on your verification volume, latency tolerance, and risk/compliance needs.
What “affordable” looks like (typical market signals)
Market per‑check averages (2024–2026 market r …

The AI’s answer as we received it, shortened and not checked for accuracy.

Payees03

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

01
Veriff
9
02
Jumio
8
03
Onfido
3
04
Socure
3

Share of mentions

CompanyShare

Veriff
36.4%
Jumio
30.3%
Onfido
18.2%
Socure
15.2%
FaceSign
0.0%
ID.me
0.0%

Referrers04

Websites the AI used as sources

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

01
realeyes.ai
9
02
arxiv.org
8
03
jumio.com
8
04
pingidentity.com
7
05
adaptivesecurity.com
7
06
vouched.id
6
07
ondato.com
6
08
didit.me
6
09
microblink.com
5
10
learn.g2.com
4

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

By assistant05

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 comparison06

How FaceSign 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

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

Citations

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

Sentiment

How positively AI describes the company

Site quality

How well built the website's own pages are

AI readiness

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 sector07

Compared with financial technology and data companies

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

Overall score

Ranks 486 of 574. Typical company: 29

Named in answers

0.0%

Ranks 334 of 574. Typical company: 1.7%

AI readiness

Ranks 533 of 574. Typical company: 29

Against its category08

Compared with fraud and identity companies

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

Overall score

Ranks 154 of 171. Typical company: 30

Named in answers

0.0%

Ranks 103 of 171. Typical company: 1.7%

AI readiness

Ranks 161 of 171. Typical company: 36

AI agents09

Ready for AI agents

What this website publishes for an AI agent to read, use and pay through, on a scale of six levels.

0Not yet agent-ready
1Basic web presence
2Bot-aware
3Agent-readable
4Agent-integrated
5Agent-native

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. FaceSign 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

0 of 100

AI bot rulesNot 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 0 of 100 · 97% of checks could run · checked on October 9, 2026 · www.facesign.ai · 2,200 companies scanned

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

AI readiness10

The checks behind the AI readiness score

1 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%
Not metHTTP 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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End of statement

All 2,219 companies How we measured this

FaceSign

What this means for FaceSign

Get the full report on FaceSign as a PDF

Every question, and where the company came up

What OpenAI actually said

Where the mentions went

Named instead

Share of mentions

Websites the AI used as sources

Which AI assistants named the company

How FaceSign compares with all 2,219 companies

What makes up the score

Compared with financial technology and data companies

Compared with fraud and identity companies

Ready for AI agents

The checks behind the AI readiness score

Discoverability

Content Accessibility

Bot Access Control

API / Auth / MCP

Get the full report on FaceSign as a PDF

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