Title: Risk Analysis: Experience vs Data
How to asses risks with small data sets? One of the challenge in insurance is that despite of having many customers, insurance companies have often little claims data to assess risks. I will presented some Bayesian ideas to analyse risks with little, or even no data. I will touch on ideas from Daniel Kahneman and David Spiegelhalter and play around with Bayesian Belief Networks, hierarchal models and Stan.
Markus is responsible for research and modelling at Vario.
Prior to Vario, he headed up the Analysis function at Lloyd's of London for eight years, where he was responsible for market-wide analytical research and development.
Before Lloyd's, he was responsible for pricing at Libero Ventures, a start-up backed by Lehman Brothers. There he developed new technology to transfer underwriting risk into capital markets.
Markus is the maintainer of the claims reserving ChainLadder package and he is the founder of the R in Insurance conference. He is a regular speaker at industry conferences.