This is like having a 24/7 digital security guard that watches every transaction in your bank or fintech system, instantly spots suspicious behavior that looks like fraud, and alerts humans before the money actually disappears.
Detects and prevents fraudulent financial transactions (payments, card use, onboarding abuse, account takeover, money laundering) faster and more accurately than manual rules or human review, reducing financial losses and false positives.
Domain-specific historical transaction and customer behavior data, proprietary risk signals and features, integration into core payment and banking workflows, and continuous model improvement pipelines create a strong data and workflow moat over time.
Classical-ML (Scikit/XGBoost)
Feature Store
High (Custom Models/Infra)
Real-time scoring latency and feature computation at high transaction volumes, plus data quality and label availability for supervised learning.
Early Majority
Positioned as an AI-first, customizable fraud detection solution that can combine supervised risk scoring with anomaly detection and time-series behavior modeling, and integrate into existing financial systems and workflows rather than being a rigid, closed SaaS black box.
146 use cases in this application