AI / ML

Real-Time Fraud Detection with Kafka and MLOps

We designed and implemented a real-time fraud detection system capable of processing over 10,000 transactions per minute with 99.2% accuracy and less than 0.1% false positives, leveraging gradient boosting and deep learning models. Our solution included behavioral feature engineering, real-time inference via Apache Kafka, and a robust MLOps pipeline supporting automated retraining, A/B testing, and performance monitoring—ensuring continuous improvement and reliability at scale.