Accelerating Insurance Claims With a Stream Processing Architecture

This post details a practical application of Confluent's data streaming platform, specifically Apache Flink on Confluent Cloud, for accelerating insurance claims processing. It outlines a 5-step architecture for real-time claims, emphasizing the use of Kafka topics for event ingestion (FNOL), data enrichment via temporal joins with customer and policy data streamed from Oracle CDC, and Flink for data filtering and routing. The post highlights the benefits of stream processing over batch jobs for improved customer experience, reduced risk of inaccurate assessments, and enabling parallel processes like fraud detection and ML model training. It also showcases Confluent's managed connectors and Flink SQL capabilities.