How can we asses risks with small data sets? One of the challenges in insurance is that despite having many customers, insurance companies often have only small amounts of claims data with which they can assess risks.

Markus Gesmann will present some Bayesian ideas to analyse risks with little, or even no event data.

We will touch on ideas from Daniel Kahneman and David Spiegelhalter and play around with Bayesian Belief Networks, hierarchal models and Stan.

YOU MAY ALSO LIKE:

• Tensorflow & Firebase Hacknight (in London on 3rd September 2018)
• CloudNative London 2018 (in London on 26th - 28th September 2018)
• Kubernetes: Master Application Deployment and Scaling with Daniele Polencic (in London on 13th - 14th December 2018)
• Deep Learning Fundamentals (in London on 25th - 26th March 2019)