Catastrophe modeling remains work in progress. With each upgrade we aim to build a better model, employing expanded data sets for hazard calibration, longer simulation runs, more detailed exposure data, and higher resolution digital terrain models (DTMs).
Yet the principal way that the catastrophe model “learns” still comes from the experience of actual disasters. What elements, or impacts, were previously not fully appreciated? What loss pattern is new? How do actual claims relate to the severity of the hazard, or change with time through shifts in the claiming process?
After a particularly catastrophic season we give presentations around ”the lessons from last year’s catastrophes.” We should make it a practice, a few years later, to recount how those lessons became implemented in the models.