Skip to content
Solution · Fraud Prevention

Fraud Prevention

Real people.No deepfakes.No takeovers.

Fraudsters use synthetic identities, deepfakes, injected camera feeds and stolen logins. Layer registry-backed verification, server-verified liveness, device intelligence and a living trust score — so an attacker has to defeat every layer at once, at sign-up and every day after.

How it works

One flow,end to end.

Layered fraud defense — identity, biometrics, device signals and a living trust score, across the whole lifecycle.

  1. 1

    Verify a real, unique person

    Registry lookups plus document + biometric verification confirm a real person — and duplicate-identity and device-reuse signals catch the same actor returning under a new name.

  2. 2

    Defeat deepfakes & injection

    Liveness is re-verified server-side on the recorded video — the client's own verdict is never trusted — and capture-integrity checks flag virtual cameras and injected feeds.

  3. 3

    Watch for takeover, then step up

    A living trust score tracks every device, login and behavioural signal. When account-takeover signals fire, the platform can automatically challenge the user to re-verify instead of guessing.

What powers it

The layersunder the hood.

Deepfake & injection defense

Active liveness is re-scored server-side against the recorded video — a tampered client verdict, a replay or an injected feed can't fake a flash sequence that never happened.

Device & IP intelligence

Multi-accounting, emulator, datacenter-IP and velocity signals surface coordinated fraud and the same actor returning under a new identity.

Account-takeover detection

Send us the login and session events your app already sees. A device the user has never used and a country hop too fast to be travel score out of the box; richer takeover sequences compose from your own signals — takeover shows up as a pattern, not a single event.

Step up, don't just block

When risk spikes, mint a hosted re-verification challenge instead of blocking a good customer. Passing it restores their trust score; failing it is a hard signal.

A living trust score

Every signal — verification, biometrics, device, screening, behaviour — folds into an explainable fraud-risk and identity-confidence score that decays over time and moves as the customer does.

Frequently asked

Fraud Preventionquestions.

By requiring an attacker to defeat several independent layers at once — source-direct registry verification, facial comparison, active liveness, and device/IP signals — which a synthetic identity can't do.

Fraud Prevention,solved.

Sandbox-ready in minutes. Usage-based pricing, no sales call.