Fraud Prevention System
Combines ML and rule-based logic to detect anomalies faster and reduce false positives by 45%.
Solution
Core Capabilities
- Hybrid Architecture Combines legacy rule engine with ML-based anomaly detection
- Real-Time Data Access via MS SQL replication and Apache Ignite for historical and streaming data
- Intelligent Data Pipeline Event Receiver Service continuously collects and enriches behavioral data
- ML Pipeline Automation Python ETL and Model Pipeline handle training, scoring, and retraining
- Orchestrated Delivery DagsHub automates deployment, ensuring smooth rollout and measurable accuracy gains
Measured Outcomes
+46% Reduction in False Positives Fewer manual reviews and faster decision-making across fraud operations
+41% Operational Efficiency Lower workload for underwriters and improved turnaround for genuine transactions
+23% Customer Experience Index Driven by fewer unnecessary holds and quicker approvals for legitimate payments
+41% Operational Efficiency Lower workload for underwriters and improved turnaround for genuine transactions +23% Customer Experience Index Driven by fewer unnecessary holds and quicker approvals for legitimate payments