Presentation attacks
Detect attempts to bypass verification with photos, screens, masks, and other physical representations.
Screen edge
Detect fraud before it becomes a problem.
Catch forged documents, presentation attacks, injection fraud, and morphed faces before they reach your onboarding or payment flow.
What it detects
Designed to catch the signals fraud leaves behind.
Document manipulation
Detect altered or forged documents through inconsistencies in fields, portraits, layouts, and machine-readable data.
Two source faces
Injection attacks
Identify manipulated, virtual, or pre-recorded camera feeds designed to bypass the verification process.
Feed source mismatch
Morph detection
Identify facial images created by combining multiple identities to deceive biometric face matching.
Date of birth
How it works
Multiple signals. One risk decision
Capture
Documents, faces and session signals are captured securely and prepared for verification.
01Analyze
Each signal is analyzed independently to identify authenticity, quality and potential anomalies.
02Cross check
Identity signals are compared against each other to uncover inconsistencies and unexpected matches.
03Risk signals
Findings are combined to identify suspicious patterns and determine the overall level of risk
04Decision
The verification result is returned with a clear outcome approve, review or reject.
05Technology
Layered defence, not a single gate.
Each layer removes a different class of attack. What reaches the decision is a signal that has passed every one.
01Device & session integrity
02Injection detection
03Presentation attack detection
04Document forensics
05Morph & cross-signal checks
Trusted signal reaches decision
01Device & session integrity
02Injection detection
03Presentation attack detection
04Document forensics
05Morph & cross-signal checks
Trusted signal reaches decision
Use cases
Fraud prevention for high stakes moments.
Contact
Talk to us
Tell us what you’re trying to verify. We’ll show you how secuveri can fit your workflow.
