Deployed real-time transaction monitoring using anomaly detection algorithms to identify fraudulent patterns, processing 1M+ transactions daily.
Financial institution needed real-time fraud detection across millions of daily transactions while minimizing false positives that disrupt legitimate customers.
Implemented Isolation Forest algorithm for unsupervised anomaly detection, identifying fraudulent patterns without requiring labeled training data.
Achieved 0.02% false positive rate while saving $2M annually in fraud losses and processing over 1M transactions daily.