NOT BUILT — PHASE 2

AI Identity Verification That Stops Synthetic Fraud at the Door

Iris Verma — Senior AI Identity Verification Specialist

Manual KYC takes 3-5 days. Half your applicants drop off before approval. Meanwhile, synthetic identity fraud is rising 40% year-over-year. Iris Verma verifies documents with 99.2% accuracy, detects liveness in real time, and screens against sanctions and PEP lists — all in under 3 seconds. Onboarding conversion improves by 60%.

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99.2%

Document Verification Accuracy

<3 sec

Verification to Approval Time

95%

Synthetic Identity Detection

60%

Faster Onboarding Conversion

30 days

Deployment Timeline

THE PROBLEM

The Problem Your Onboarding Team Faces Every Day

Your compliance team processes hundreds of identity verification requests daily. Manual KYC takes 3-5 business days — and according to Signicat's "The Battle to Onboard" report, 68% of customers abandon onboarding when the process takes too long.

Meanwhile, synthetic identity fraud is the fastest-growing financial
crime in the United States.

Conversion killer

Manual KYC takes 3-5 days. According to Signicat, 68% of applicants abandon onboarding before completion. Every day of delay costs you revenue and market share.

Synthetic identity surge

According to the Federal Reserve, synthetic identity fraud losses exceeded $6 billion annually in the US. Legacy verification systems cannot detect identities assembled from real and fabricated data elements. The fraud rate is rising 40% year-over-year.

Audit gap

Regulators under BSA/AML, FATF, eIDAS, and the EU AI Act demand explainable, auditable identity verification decisions. Manual processes produce inconsistent documentation that fails examination.

JOB DESCRIPTION

What Iris Verma Does — Job Description

Iris Verma is a Senior AI Identity Verification Specialist that operates inside your onboarding pipeline as a dedicated verification analyst.

IRIS VERMA

Senior AI Identity Verification Specialist | FF-CIM

Partial Build (Phase 1 Live)

Reports To

Your Head of Onboarding / Compliance

Works With

Existing KYC, core banking, and
onboarding systems

Deployed In

30 days (shadow mode first)

KEY RESPONSIBILITIES

Verify identity documents in real time using forensic analysis and AI-powered extraction

Perform liveness detection with anti-spoofing to confirm physical presence

Screen against sanctions, PEP, and watchlist databases with real-time matching

Detect synthetic identities by analyzing document metadata and identity element patterns

Produce audit-ready verification trails for every decision — immutable, tamper-evident

AUTONOMY MODEL

Low risk — Acts autonomously (approve, clear)

Medium risk — HITL by default (configurable)

High risk — ALWAYS human review (non-negotiable)

You configure the threshold per rule

Kill switch : Disable instantly

99.2%+

Document Verification Accuracy

across passport,license, ID

99.5%+

Liveness Detection Accuracy

with passive anti-spoofing

<3 seconds

Verification To Approval Time

end-to-end verification

95%

Synthetic Identity Detection

synthetic identities caught

60%

Onboarding Conversions Improvement

faster onboarding

<1 second

Watchlist Screening Speed

against sanctions/PEP databases

<0.5%

False Reject Rate

legitimate applicants wrongly rejected

100%

Audit Trail

every verification logged

HOW IT WORKS

How AI Identity Verification Works with Iris Verma

Iris Verma connects to your existing onboarding systems via API — no data migration, no core system changes. Here is how every verification flows:

Capture

Identity documents (passport, driver's license, national ID) and
a selfie or biometric sample are submitted via your onboarding
interface. Iris Verma receives document images, metadata, and
biometric data through API integration.

Verify

Documents are authenticated using forensic analysis — security
features, font consistency, metadata integrity, and photo manipulation detection. Liveness detection confirms the person is physically present using passive anti-spoofing that requires no user actions, reducing friction.

Screen

Verified identity data is cross-referenced in real time against
sanctions lists (OFAC, EU, UN), PEP databases, adverse media,
and configurable watchlist databases. Matches are flagged with confidence scores and evidence links.

Decide

Based on verification and screening results, Iris Verma takes action:
• Low risk → Approves autonomously (clean document + no watchlist hit)
• Medium risk → Flags for analyst review (configurable threshold)
• High risk → Escalates to human team (always)
Every decision produces a plain-English explanation with regulatory
mapping and an immutable audit trail your compliance team and
regulators can read directly.

BSA/AML

Customer identification program (CIP) requirements

FATF

Recommendations on customer due diligence and enhanced due diligence

eIDAS

Electronic identification and trust services regulation

NIST 800-63

Identity proofing levels (IAL1, IAL2, IAL3)

GDPR

Biometric data handling and consent requirements

EU AI Act

Explainable AI and high-risk system transparency

ROI — AI IDENTITY VERIFICATION vs HIRING vs LEGACY TOOLS

AI Customer Identity Management Cost Comparison — 2026

How does Iris Verma compare to hiring verification analysts or using legacy identity verification providers?

Criteria	Hire 3 Analysts	Legacy IDV Provider	Iris Verma
Annual cost	$360K-$720K (salary + benefits)	$150K-$500K (per-verification fees)	Contact for pricing
Deployment time	3-6 months (recruit + train)	2-4 months (integration)	30 days
Verification speed	3-5 days per applicant	30-60 seconds	<3 seconds
Synthetic identity detection	Inconsistent (human judgment)	Limited pattern matching	95% detection accuracy
Onboarding conversion	Low (slow process)	Moderate	60% improvement
Explainability	Verbal, inconsistent notes	Limited logs	Plain-English + regulatory mapping
Audit trail	Manual, scattered	Partial	100% automated, immutable
Scales with volume	Hire more ($$)	Per-verification cost increases	Auto-scales
Available 24/7	No (shifts needed)	Yes	Yes (continuous)
Learns from feedback	Yes (slowly)	No	Yes (continuous)

Key insight : According to McKinsey, banks spend an average of $15-$25 per manual KYC verification. At 10,000 verifications per month, that is $150K-$250K annually in verification costs alone. Iris Verma handles the volume at higher accuracy with 60% faster conversion. Contact our team for a tailored quote.

Rhea Ledger

Senior AI KYC/AML Compliance Director

Automates sanctions/PEP screening and SAR filing for the identities Iris verifies

Learn now

Aiden Flux

Senior AI Fraud Risk Analyst

Scores every transaction from verified identities Iris Verma has confirmed

Learn now

Cian Gatekeeper

Lead AI Customer Identity Director

Manages the full customer identity lifecycle after Iris Verma completes initial verification

Learn now

TRUST BUILDERS

Built for Security Teams at Regulated Financial Institutions

Configurable Autonomy

Low risk: Iris acts autonomously (clean documents, no watchlist hits).
Medium risk: HITL by default (configurable).
High risk: Always human review. You set the threshold per document type, per jurisdiction, per risk category.

Kill Switch

Disable Iris Verma instantly. No system impact. No downtime.One click.

Shadow Mode

Run Iris Verma on your live onboarding data for 30 days. Observation only — no blocking, no action. Validate accuracy before going live.

Explainability

Every verification decision includes plain-English reasoning explaining what was checked, what passed, what failed, and why. Your compliance team and regulators can read it directly.

Audit Trail

Every verification logged with immutable, tamper-evident evidence chain. Document → biometric → screening → decision → outcome.

No Migration

API integration. Iris Verma connects to your existing onboarding flow. Your core systems stay untouched.

Thoughts That Matter

Insights on AI Security,Compliance
& Financial Automation

Keep up with the latest AI trends, insights, and conversations.

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AML transaction monitoring: how AI cuts false positives by 60%

Questions? We Have Answers

Frequently Asked
Questions

AI identity verification in banking works by analyzing identity documents, biometric data, and watchlist databases in real time. Systems like Iris Verma by FluxForce extract data from government-issued IDs, verify document authenticity using forensic analysis, perform liveness detection to confirm physical presence, and cross-reference against sanctions and PEP lists - all in under 3 seconds with 99.2% document accuracy.

Synthetic identity fraud involves combining real and fabricated identity elements to create a fictitious identity. According to the Federal Reserve, synthetic identity fraud is the fastest-growing type of financial crime in the US, with losses exceeding $6 billion annually. AI detects it by analyzing document metadata inconsistencies, biometric mismatches, and cross-referencing identity elements against known fraud patterns. Iris Verma achieves 95% synthetic identity detection.

Manual KYC identity verification typically takes 3-5 business days. AI identity verification with Iris Verma completes the entire process - document verification, liveness detection, sanctions screening, and approval - in under 3 seconds. According to Signicat, 68% of customers abandon onboarding when the process takes too long. Iris Verma improves onboarding conversion by 60%.

Yes. Iris Verma maps every verification decision to applicable frameworks including BSA/AML, FATF recommendations, eIDAS, NIST 800-63 identity proofing levels, GDPR biometric data handling, and the EU AI Act explainability requirements. Each decision produces an audit-ready trail with full evidence chain documentation.

Yes. Iris Verma uses passive liveness detection with anti-spoofing analysis to detect presentation attacks including printed photos, video replays, 3D masks, and deepfake attempts. According to NIST, liveness detection is a critical component of identity proofing at IAL2 and above. The system works without requiring users to perform specific actions, maintaining a frictionless onboarding experience.

Iris Verma supports passports, national identity cards, driver's licenses, and residence permits from 195+ countries. Document forensic analysis checks security features including holograms, microprinting, UV elements, and machine-readable zones. New document types are added through configuration - no code changes required.

AI Identity Verification That Stops Synthetic Fraud at the Door

Cian Gatekeeper

99.2%

<3 sec

95%

60%

30 days

The Problem Your Onboarding Team Faces Every Day

Conversion killer

Synthetic identity surge

Audit gap

What Iris Verma Does — Job Description

IRIS VERMA

Target Performance — Design Specifications

How AI Identity Verification Works with Iris Verma

Capture

Verify

Screen

Decide

Want to See This on Your Onboarding Data?

Regulatory Frameworks Supported

BSA/AML

FATF

eIDAS

NIST 800-63

GDPR

EU AI Act

What Your Identity Operations Team Sees

AI Customer Identity Management Cost Comparison — 2026

Agents That Work Best with AI Identity Verification

Rhea Ledger

Aiden Flux

Cian Gatekeeper

Built for Security Teams at Regulated Financial Institutions

Configurable Autonomy

Kill Switch

Shadow Mode

Explainability

Audit Trail

No Migration

Insights on AI Security,Compliance & Financial Automation

DORA compliance for banks: 7 ICT risk requirements to meet now

Zero Trust banking: how CISOs secure core systems in 2026

AML transaction monitoring: how AI cuts false positives by 60%

Frequently Asked Questions

Insights on AI Security,Compliance
& Financial Automation

Frequently Asked
Questions