Upload your data. That's the entire setup.
- Upload transaction file
- Provide merchant URLs
- Analysis begins automatically

Cross-references your merchant transaction data with their digital footprint so you see what your merchants are, not just what they report.

Ballerine connects transaction patterns with real-world merchant behavior, helping you spot hidden risk before chargebacks, fraud, and losses surface.

No rule configuration. No model training. Upload your data and the system takes over.



Reduction in analyst review time
Automated detection and triage eliminates the bulk of manual data gathering your team handles today.
Merchants analyzed per
cycle
Process your full portfolio in the time it previously took to manually review a handful of accounts.
Rules to configure or
maintain
Fully automated analysis from day one. No training data, no rule tuning, no ongoing model maintenance required.
No modules to unlock. No add-ons to configure. Every capability runs automatically across your full merchant portfolio.
Transaction analysis is the process of examining merchant transaction data - including volume patterns, refund rates, chargeback ratios, and payment behavior - to identify risk signals such as laundering, bust-out fraud, or policy violations. Ballerine's transaction analysis uses AI to contextualize transaction patterns alongside web presence and business data, delivering audit-ready risk assessments rather than isolated alerts.
Rule-based systems flag transactions that cross static thresholds, generating high volumes of false positives and missing novel fraud patterns. AI-powered transaction analysis evaluates patterns contextually - correlating transaction velocity, merchant category, web activity, and historical behavior - to surface genuine risk while reducing noise. This means risk teams spend less time reviewing false alerts and more time acting on real threats.
Transaction analysis can detect transaction laundering, credit card testing, chargeback manipulation, bust-out schemes, and unusual refund patterns. By analyzing transaction data alongside a merchant's digital footprint, Ballerine identifies inconsistencies - such as transaction volumes that don't match a merchant's reported business type or web presence - that point to fraudulent activity.
Card scheme rules - including Mastercard's Merchant Monitoring Program (MMP) - require acquirers and payment facilitators to monitor merchant transaction behavior for signs of risk. Transaction analysis provides the audit-ready documentation and ongoing risk visibility needed to meet these requirements, detect problematic merchants early, and avoid fines or enforcement actions from card networks.
Yes. Ballerine's transaction analysis is designed to integrate with existing risk and compliance workflows via API. It layers transaction pattern intelligence on top of your current stack - enriching merchant risk profiles with behavioral data from payment activity, web presence analysis, and business verification - so teams get a more complete picture without replacing what already works.
