Rethinking Catastrophe Model Evaluation By Getting Out Of Model Land

For effective risk management, insurers require a catastrophe model evaluation framework that focuses on past performance, expert judgements, consistency in confidence levels, and a well-defined attitude to model risk.

We want to assess future risk. But because the future hasn't happened yet, our only way of accessing knowledge about the future is by making models. Unfortunately, because models are simplifications of reality, they are inherently limited and uncertain, so we don't just need to know what the model says, we also need some indication of how far we should trust it.

If we are interested in low-probability events or tail risks, as is often the case with natural catastrophe models used by insurers, this is going to be a difficult ask. First, we don't have very much data, because low-probability events by definition don't happen very often. Second, the tail risks are unlikely to be stationary – societies are evolving; businesses are transforming; the