Financial Intelligence
SanQya
SanQya applies quantum-enhanced machine learning to credit risk scoring, fraud detection, portfolio optimization, and options pricing — finding risk signal that classical models plateau on, without GPU infrastructure.
5-10% better accuracyUse Cases
- →Banking: Credit scoring and loan underwriting
- →Fraud Ops: Real-time transaction fraud detection
- →Treasury: Bond risk analysis and portfolio optimization
Benchmarks
| Feature | Classical AI (SOTA) | Quanverge Hybrid |
|---|---|---|
| Model Accuracy | Baseline (SOTA ML) | +5-10% |
| Hardware | GPU Required | CPU Only |
| Validation | Synthetic / backtest only | Real bank data (NDA) |
| Fraud False Positives | High | Reduced |
| Deployment | Weeks | Hours |
Estimate your SanQya ROI
Estimated accuracy with Quanverge
%
Based on: the full 5-10% better accuracy band measured on real bank data
Illustrative estimate based on Quanverge's published benchmarks — actual results vary by deployment.