AI-Powered Fraud Detection for Tier-1 Global Bank
The client faced increasing fraud losses and customer dissatisfaction due to aggressive but inaccurate legacy rule-based systems.
40%
reduction in false positives
$50M
saved annually
Real-time
processing of 10M+ transactions/day
We implemented a hybrid AI model combining supervised learning with unsupervised anomaly detection to identify novel fraud patterns in real-time.
PythonTensorFlowAWS SageMakerKafka
