AI Scam Detection
Behavioral AI models trained on 50B+ real calls detect fraudulent callers, social engineering attempts, and suspicious conversation patterns in real time — before damage is done.
50B+ calls
Training Data
Every 2s
Score Update
< 0.3%
False Positive Rate
99.7%
Detection Rate
40+
Languages
REST / WebSocket
Integration
Capabilities
Real-Time Risk Scoring
Continuous fraud risk score updated every 2 seconds throughout the call lifecycle.
Behavioral Pattern Analysis
Detects manipulation tactics, urgency creation, and deceptive conversation patterns.
Voice Clone Detection
Identifies AI-generated and cloned voices used in synthetic identity fraud.
Automatic Agent Alerts
Pushes risk alerts to agent desktops in real time without interrupting the call flow.
Regulatory Audit Trail
Full immutable audit log of every fraud signal for regulatory and compliance reporting.
Custom Risk Thresholds
Tune sensitivity levels by call type, customer segment, or channel.
Quick Start
const session = await alpandia.voice.stream({
features: ['scam-detect'],
onScamAlert: (alert) => {
console.log(alert.score); // 0.94
console.log(alert.signals); // ['urgency', 'gift-card-request']
console.log(alert.severity); // 'high'
console.log(alert.recommended); // 'transfer-to-supervisor'
}
});Use Cases
Banking Call Centers
Protect customers from authorized push payment fraud and social engineering.
Telecom Operators
Network-level fraud detection for suspicious call patterns at scale.
Insurance Claims Lines
Detect fraudulent claims callers using behavioral pattern analysis.
Government Service Lines
Protect citizens from impersonation scams targeting public services.