Let’s talk about risks and pricing in insurance: From an insurance company the customer expects a fair (and affordable) tariff. How can we offer this, especially if the tariff model is very static? With KSQL, we are building the entire Processing Piplines directly in Kafka. With each deal we can re-evaluate the overall risk and learn from each claim. With each quote request, we understand the market better. And with this knowledge, we can adjust prices in real time to keep it cheap for the customer and still make some money. We expect peaks with twenty requests per second in Q4 and our partners allows us only one second to stick a price tag on the quote. Therefore we need a system that is fast, scalable and reliable. The central point is Confluent Kafka with a heavy use of streaming processing with KSQL. We start with the insurance product on 01.10. in the German market and look exclusively at architecture and function.