Your IDV Stack is
Approving Fake Identities

The Blind Spot Audit Shows You Where

Rescan verified customers with Shufti’s Blind Spot Audit directly in your own cloud and see what your current controls missed.

Run Now On AWS Explore All Clouds

tick-img Runs entirely in your cloud

tick-img No PII Ever leaves

tick-img No integration or coding

Spot the Blind Spots in Your 2025 Customer Book

Deepfake ID attacks
in 12 months

Source: The Next Web025

$40B 40B-img

AI-enabled fraud
losses by 2027

Source: Deloitte CFS

$0B 2137-img

Regulatory fines for
weak KYC.

Source: Traders-Magzine

One Audit. Four Engines Your Data, Your Cloud

AI-driven forgeries are already sitting in your approved customers. One private audit, with four specialised engines, shows you where, without any PII leaving your cloud.

Challenge Your Current Controls

Rescan already-approved liveness, face and document checks with Shufti’s four engines to see where spoofs, deepfakes and forged IDs slipped past your existing stack.

No New Vendor Overhead

Deploy directly from your cloud marketplace into your own VPC. No data export, no new integrations, no long contracts, just audit-grade results with zero PII leaving your environment.

Focus on High-Risk Journeys

Start with 2025’s highest-value accounts, risky corridors and known fraud cases. Use the findings to harden KYC and P2P flows before the next regulatory review.

Deploy in Minutes. See the Gaps Straight Away

How the Blind Spot Audit Works

Step 1

Deploy in Your Cloud

Launch Shufti from your cloud marketplace into your own environment. All analysis runs inside your VPC, Shufti never sees or stores PII.

Step 2

Select Sessions to Re-Check

Point the audit at historic KYC, liveness and document sessions your stack already approved. No SDK changes, no new integrations, no customer-facing work.

Step 3

See the Blind Spots

See where deepfakes, spoofed liveness and forged documents slipped past your controls. Export clear evidence for rule tuning, model updates and regulator-ready reports.

Shufti Finds & Removes Your Weak Points

Four Blind Spots, Four Engines to Expose Them

Why Traditional IDV Misses Modern Deepfakes

Built for Yesterday’s Attacks

Missing Today’s Attacks

PINNING RELEASED: Next Section Content

Shufti Treats Every Frame and Pixel as Evidence

How Shufti Closes the Gap

Multi-Signal Media
Forensics

Shufti’s models analyse depth, motion, lighting, reflections and device artefacts together, not just face similarity to distinguish real presence from scripted or injected feeds.

Document-Level
Authenticity Checks

For documents, Shufti cross-checks printed fields, MRZ/barcodes, fonts and security elements against trusted designs to expose subtle edits, reused images and machine-drawn layouts.

Continuous Adversarial
Testing

Shufti’s research team routinely attacks its own models with new deepfake, replay and editing tools, shipping targeted updates so your audit reflects how fraudsters actually operate in 2025, not last year’s lab tests.

One Audit,
Every Team
Covered

Compliance Officers

Prove your KYC controls beat deepfakes with regulator-ready evidence from real traffic.

Fraud & Risk Operations

See exactly which sessions your stack missed and focus reviews where real loss is hiding.

Product & Engineering

Test vendors and tune flows safely in your own cloud before you ship or re-platform.

Run a Blind Spot Audit Where Failure Hurts Most

Shufti for High-Risk Industries

Digital Banks & Fintech

Re-test 2025 onboarding to find AI-forged IDs and spoofed liveness that opened mule and high-risk accounts before they show up in AML alerts or write-offs.

PSPs & Remittance

Audit merchant and consumer onboarding to uncover replayed sessions and forged documents used to set up fake pay-out routes and high-risk sender/receiver profiles.

Crypto & Web3

Check whether your current KYC would catch AI-assisted IDs, deepfake selfies and non-live sessions used to move funds anonymously across tokens and chains.

Online Lending & BNPL

Scan historic applications to identify hidden identity-fraud clusters – borrowers with manipulated IDs and non-live selfies that your credit models treat as ordinary risk.

Gaming & iGaming

Re-check age, jurisdiction and self-exclusion flows for spoofed liveness and forged IDs that allowed bonus abuse, multiple personas and restricted-region play.

Marketplace & Gig Economy

Validate that buyers, sellers and hosts were ever physically present at verification. Surface re-used IDs and spoofed faces behind repeat bans, chargebacks and safety incidents.

Accredited liveness, multi-layered fraud defences & global reach