>
Now with Graph Neural Network detection

Stop Fraud Before It Happens

Real-time AI Fraud Detection API for Fintech & Banks. Sub-100ms latency. Bank-grade security. Zero-trust architecture.

Try Live Demo Open Dashboard
< 100ms latency
99.9% uptime SLA
Global edge network

Why FraudShield AI?

Complete fraud detection stack, not just ML

Multi-Model AI

XGBoost + Graph Neural Networks + Anomaly Detection fused via MCP orchestration

Zero Trust Security

Device fingerprinting, behavioral biometrics, and continuous authentication

Self-Learning

Auto-retraining pipeline with feedback loop and drift detection

Live Fraud Detection Demo

Test our API in real-time. No signup required.

Transactions Aujourd'hui
0
+12.5% vs hier
Fraudes Détectées
0
2.4% du total
En Révision
0
Manuellement
Temps Moyen
85ms
< 100ms target

Nouvelle Transaction

Pipeline de Détection

Input
Preprocessing
Feature Eng.
ML Model
Rules

Historique des Transactions

Time User Montant Score Décision Raisons

Score de Fraude

0.00 Score Global
En attente...
ML Model (70%) 0.00
Rule Engine (30%) 0.00

Configuration des Règles

Pays différent
User country vs IP country
Montant élevé
> 5000€
Velocity 1h
> 10 tx/heure
Nouveau Device
Device fingerprint inconnu
Seuils de Décision

Facteurs de Risque

Aucune analyse en cours

Distribution des Scores

Tendances Heures

Simple, Usage-Based Pricing

Pay only for what you use. No hidden fees.

Starter
$0.005
per transaction
  • Up to 10K tx/month
  • ML + Rules
  • Email support
  • 7-day retention
Most Popular
Pro
$0.01
per transaction
  • Up to 100K tx/month
  • + Graph AI
  • Priority support
  • 30-day retention
  • Webhooks
Enterprise
$0.02
per transaction
  • Unlimited volume
  • + Zero Trust
  • Dedicated support
  • 1-year retention
  • SLA / Custom models

Simple API Integration

One endpoint. Instant decision.

cURL
# Check transaction for fraud
curl
-X POST
https://api.fraudshield.ai/v1/fraud/check
\
-H "Authorization: Bearer YOUR_API_KEY"
\
-H "Content-Type: application/json"
\
-d '{
"user_id": "usr_123",
"amount": 299.99,
"currency": "USD",
"merchant": "Acme Store",
"device_id": "dev_fingerprint_xyz"
}'
Response
{
  "fraud_score": 0.23,
  "decision": "ALLOW",
  "reasons": [],
  "latency_ms": 47,
  "model_version": "v2.1.0-mcp"
}