Synthetic identity
A real-looking person who doesn't exist
Synthetic identities mix real and invented details. Each piece checks out on its own, so the file looks clean until the account is used for fraud.
BetaTrust and Identity squad
Iris Verma — Senior AI Identity Verification Specialist
AI identity verification that shows its evidence
Iris Verma — Senior AI Identity Verification SpecialistIris Verma is an AI agent that checks identity documents, selfies and liveness at onboarding and re-verification. She looks for tampered documents and synthetic identities, and flags documents near expiry so re-verification starts on time. Clear checks can complete with a recorded reason, only where you allow it. Everything else reaches your analyst with the evidence attached.
Iris Verma
Onboarding check #30592
IllustrativeSent to analyst
Identity risk 0.74 · high
Flag explained
“Font mismatch in date of birth, weak selfie match, liveness passed.”
Job description
What Iris Verma does Job description
Iris Verma is a Senior AI Identity Verification Specialist. She sits inside your onboarding and re-verification flows, checks each document, selfie and liveness result, and prepares the case for your analyst.
AI AGENT · TRUST AND IDENTITY SQUADBeta
IRIS VERMA
Senior AI Identity Verification Specialist
REPORTS TO
Your Head of Onboarding or MLRO
WORKS WITH
Your onboarding app, document capture vendor and KYC system
DEPLOYED
Shadow mode first, then the autonomy you set
KEY RESPONSIBILITIES
01Check identity documents for tampering, template mismatches and data that doesn't add up
02Compare the selfie with the document photo and review the liveness result
03Flag signs of synthetic identity, such as details shared across unrelated applicants
04Track document expiry and start re-verification before documents lapse
05Send unclear or risky cases to an analyst with the evidence attached, and record the reason for every outcome
AUTONOMY MODEL
LOWMEDIUMHIGH
Low risk
Can complete clear checks with a reason, if you allow it
Medium risk
Goes to an analyst by default
High risk
Always goes to an analyst
You set the threshold per rule.
Kill switch: Turn Iris off at any time
Options
How the options compare
| CRITERIA | Manual review | Point verification vendor | Iris Verma |
|---|---|---|---|
| Time to first results | A training cycle for new staff | Vendor integration | Shadow mode on your live applications |
| Who decides | Analyst | Vendor pass or fail, then analyst | Analyst, inside risk bands you set |
| Why a check failed | Analyst notes, varies by person | Vendor code or score | Plain-English reason with the checks behind it |
| Sees across applicants | Rarely | Usually one check at a time | Yes, shared details are flagged |
| Document expiry | Periodic review | Not usually tracked | Tracked, with re-verification started on time |
| Where it's weaker | Slow and inconsistent at volume | A pass or fail your examiner can't question | Only as good as the image and liveness capture it receives |
Works best with
AI agents that work best with Iris Verma
Iris's checks count for more when other agents carry the verified identity forward.
TRUST AND IDENTITY
Rhea Ledger
Senior AI KYC/AML Compliance Director
Takes the verified identity into sanctions and PEP screening and customer risk rating.
Meet RheaTRUST AND IDENTITY
Cian Gatekeeper
Lead AI Customer Identity Director
Links Iris's result to one identity record used across every channel.
Meet CianTHREAT
Aiden Flux
Senior AI Fraud Risk Analyst
Watches the new account's first transactions for fraud signs Iris couldn't see at onboarding.
Meet Aiden
Thoughts that matter
Insights on AI agents, financial crime and compliance
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Questions? We Have Answers
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Frequently Asked Questions
Still have questions?
Talk to the people who build the agents. We'll answer per capability, yes or no.
It checks identity documents, selfies and liveness results, looks for tampering and synthetic identities, and prepares each case for a person. Iris Verma attaches a plain-English reason to every outcome and routes cases by the risk bands your team sets. Your analyst makes the call on anything that isn't clearly low risk.
Your analyst does. Iris can complete clear checks on her own only in the bands you allow, each with a recorded reason. Medium risk goes to a person by default and high risk always does. A kill switch turns Iris off without touching your onboarding flow.
It depends on your setup. Iris can review the results your current vendor produces, add checks across applicants and track expiry. Many institutions will run her alongside the vendor they already have.
She looks for details shared across unrelated applicants, such as the same phone number, address or device, and for data on one application that doesn't fit together. Those links go to your analyst as a side-by-side view.
Iris checks your live applications and opens cases, but she doesn't complete or turn away any applicant. Your analysts keep working as they do today, and you compare Iris's calls with theirs. You decide whether, and where, to switch on any autonomy afterwards.
Document images, selfie and liveness results, and application data. Past analyst decisions help Iris learn what your team accepts. Expiry dates from your KYC system let her start re-verification on time.
FluxForce runs as SaaS, on-premise or hybrid, built on Microsoft Azure. We agree data residency and which components run inside your environment during deployment design, before any data moves.