The Challenge
A fast-growing payment platform hemorrhaging millions to sophisticated fraud
A leading Digital Payment Platform serving over 15 million active users across the UK was losing $4.2 million annually to increasingly sophisticated fraud attacks. Their legacy rule-based system was unable to keep pace with evolving fraud tactics, from account takeovers and synthetic identity fraud to coordinated ring attacks targeting their peer-to-peer and merchant payment flows.
Compounding the problem, their existing fraud filters generated a 35% false positive rate, blocking legitimate transactions and frustrating customers. The platform needed a real-time scoring system that could evaluate every transaction in under 50 milliseconds while dramatically reducing both fraud losses and false positives.
Our AI Solution
Ensemble ML models for real-time fraud detection and adaptive learning
Ensemble ML Model
Built a stacked ensemble combining XGBoost, Random Forest, and LSTM networks to capture both tabular feature patterns and sequential transaction behavior for maximum fraud detection accuracy.
- XGBoost + Random Forest + LSTM ensemble architecture
- 150+ fraud indicators including device fingerprinting
- Behavioral pattern analysis and geolocation signals
- Confidence scoring for every transaction
Real-Time Processing
Ultra-low-latency inference pipeline scoring every transaction in under 50 milliseconds, powered by Kafka streaming and Spark for batch feature computation.
- <50ms latency per transaction scoring
- Kafka streaming pipeline for event ingestion
- Spark for batch feature computation
- Auto-scaling to handle peak transaction volumes
Adaptive Learning
Self-improving system that automatically detects and adapts to emerging fraud patterns through daily retraining cycles and controlled rollout strategies.
- Daily model retraining on new fraud patterns
- 12 new fraud patterns discovered automatically
- A/B tested with 20% traffic before full rollout
- Continuous monitoring and drift detection
Explainable AI
Transparent decision reasoning that enables compliance teams to understand, audit, and defend every fraud decision with full traceability.
- Transparent decision reasoning for compliance teams
- Audit trail for every flagged transaction
- PCI-DSS compliant architecture
- Role-based access and reporting dashboards
Results & Impact
Measurable improvements across every key metric
Technology Stack
Production-grade AI infrastructure built for financial services
ML Models
XGBoost, Random Forest, LSTM
Streaming
Kafka, Spark Streaming
Cloud
AWS SageMaker, Lambda
Compliance
PCI-DSS, Encryption
"We've slashed fraud losses by over 75% while dramatically reducing false positives. The system learns and adapts to new fraud tactics automatically. It's rare to see such clear ROI from a single technology investment."
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