Our Latest AI Seminar Series:
Hierarchical compartmental reserving models provide a parametric framework for describing the high-level business processes driving claims development in insurance using differential equations.
Markus Gesmann discusses how those models can be presented in a fully Bayesian modelling framework for the aggregated claims settlement process to capture trends observed in paid and outstanding claims development data reflecting the random nature of claims and latent underlying process parameters.
Markus shows how the experienced modeller can utilise their expertise to describe the volatility of the underlying risk exposure profile and uncertainty on prior parameter assumptions and highlight in particular the subtle, but important difference between modelling incremental and cumulative claims payments.