How We're Different
Most payment risk tools use static rules from 5 years ago. We use ML models trained on 70,000+ scenarios that adapt to real PSP behavior.
MerchantGuard vs Traditional Risk Tools
Training Data
Risk Assessment
PSP Coverage
Model Validation
Updates
Free Tier
Why This Matters
Real Data Beats Guesswork
Our models learned from 70,000+ scenarios. Traditional tools rely on outdated rules from 2019 that don't reflect current PSP behavior.
PSP-Specific Predictions
Stripe has different approval patterns than Checkout.com. Our 7 separate models capture these nuances—competitors use generic scoring.
Continuous Improvement
We retrain models with new merchant data quarterly. Rule-based tools stay stuck with the same logic for years.
Try the ML-Powered Approach
Get your free AgentScore in 60 seconds. See PSP approval odds based on 70,000+ training scenarios—not outdated rules.
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📊 Transparency Note
Our ML models are trained on synthetic merchant and agent data generated from industry research and PSP documentation. Models validated using holdout test sets (70-87% accuracy, ROC-AUC 0.74-0.91). Real-world performance may vary. For educational purposes.