Cat Modeling Chaos; the missing invisible fifth box of Maria

​People are wondering where the actual versus modeled lossfor Maria may eventually wind up. The answer to that question depends on the often ignored and missing fifth box of modeling – what I refer to as Modeling Chaos. Cat models are a mix of science, engineering, experience and judgement. Modeling building coverages have a strong foundations in science, engineering and experience. As we move further away from the traditional building coverages the models gradually move along with it introducing more professional judgement and with it more loss uncertainty in the analysis. 

Models do an excellent job of evaluating wind, earthquake, or flood risk when considered as a standalone structure insulated from other surrounding influences. However catastrophe events do not exclude other influences. Natural phenomena typically impact large areas introducing many new hazard elements and competing recovery needs which are invisible to most of today's models. The interaction between the modeled risk(s) and it's surrounding influences can be quite extreme, variable, and chaotic. As such it is difficult to calculate and model. Some may be included by a general loss amplification adjustment but the majority of the surrounding influences are too variable by event or location and not considered. These should be within a missing and not fully comprehended fifth box of models that accounts for the chaos surrounding an event. A fifth important box that needs to be included with the hazard, vulnerability, encoding and financial modeling boxes of today. 

Models are learning models and with each new event we begin to act on things that we suspected were deficient in our prior thinking. Three major chaotic components that are not fully considered when modeling extreme events and need to be are how the human, infrastructure, interplay between mutiple hazards, and the competing elements influence the eventual insured and economic losses. 

Human elements included preparedness, reaction, decision priorities, socio-economic resiliency, psychological, and other responses that can decrease or increase recovery costs. This would also include the potential for any post event political (regulatory and statutory) decisions. 

The quality and availability of a sound supporting infrastructure. This would include how extensive the supporting infrastructure can be, how well built it is, are there multiple means for moving resources in and out of the impacted area, how quickly can the infrastructure be repaired and most importantly how geographically accessible is the affected community by other means? Islands such as Puerto Rico are more isolated than other areas of the US and this makes it more difficult to undertake widespread infrastructure recovery. The lack of working infrastructure impedes our ability to rebuild the infrastructure the areas it serves. Examples of other the major areas that may be difficult to rebuild quickly due to geographical challenges include Long Island and NYC, Miami (peninsula), and San Francisco. Longer recovery times mean larger losses. 

Competing Elements.  This includes during and after the event. During an event the debris and building components of one structure could become damaging projectiles to other surrounding structures that otherwise would not have been damaged. Too many times an up to code building was damaged by the debris from a neighboring building. If a model does not have information about these surrounding structures then how can a model account for the additional exposure?.. it can't   After an event affected entities compete against each other for resources, material and labor, pushing up rebuilding costs and times. The greater and more congested, hard to get to, and conflicting the number of competeing entities seeking resources are then the more expensive and time consuming it will be to rebuild.

As an industry our first concern is to help those impacted by hurricane Maria. We hope that people can get back to their normal lives as soon as possible. As someone who has looked at natural catastrophes for decades I also see Maria as another lesson to all of us just how important the influence that this fifth box has on the actual versus modeled losses. It could be significant or less than anticipated by some. Nevertheless the fifth box, Modeling Chaos, needs to be accounted for when considering capacity,modeling, and underwriting results. To ignore this box challenges our understanding of the true economic and insured risk that we face. I am eager to see how the human, infrastructure, and competing elements of the fifth box differed in the industry's modeling of Maria.

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