Like many actuaries, I’ve spent a large part of my career designing and building—or using the results of—complicated models. Current developments in the regulatory and rating agency realms, as well as advances in technology, ensure that models will continue to play an important role in the P&C insurance industry. This could and should be very positive for the industry, but if we are not careful, it could perpetuate counterproductive behaviors. It is entirely possible that, as the use of models increases, so too will uncritical acceptance of the results they produce. This would be unfortunate, as models are most useful when users understand their proper role and limitations, maintain an appropriate level of skepticism toward them, and view their results as only one of many inputs to final decisions.

Models are general tools, not surgical instruments. The most useful ones do not provide answers or solve problems; they provide information. No model can contemplate every possibility, nor should anyone expect it to. There are many unlikely events that could happen and for which we should be prepared, but building such events into a model requires estimates of the likelihood of their occurrence, their potential severity and also some quantification of the probability that these events can occur in tandem. We simply cannot model some unlikely events. It is incumbent upon model result users to understand before they come to any conclusions what the model in question does (and does not) include, take into account that the model may well be missing something, attempt to determine what the missing pieces are and try to devise a method for incorporating them into the decision-making process.

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