ATM Fraud Detection with Apache Kafka and KSQL | Confluent

This post demonstrates how ksqlDB can be used to build a real-time fraud detection system for ATM transactions. It highlights the use of stream-stream joins with time windows to identify suspicious activity based on account number, location, and transaction timing. The post also shows how to integrate with Elasticsearch and Kibana for data storage and visualization, and discusses the nuances of stream-stream joins in KSQL, including the need for explicit windowing and the handling of self-joins.