External factors influence our day-to-day lives, which make the world an uncertain place. Insurance carriers, like Lighthouse, look to remove uncertainty in order to properly develop products for our customers, adjust rates for risks taken, and protect ourselves from a catastrophic loss caused by an external event like a hurricane, tornado, hail, or earthquake.
Technology continues to advance across all industries to try and mitigate our level of uncertainty. Over the last 30 years, for insurance carriers that offer property coverage in geographic areas threatened by catastrophic events, computer simulation models have continued to evolve.
Catastrophe risk computer models are used to help insurance carriers understand, for example, the financial impact that a storm event can cause at a specific risk location, or portfolio of locations. Financial models can predict how an event loss can impact a policyholder’s deductible all the way through the entire property structure value. Utilizing these models is the first step in understanding how each risk can contribute to the overall portfolio protection carriers need.
The models evaluate all the characteristics of the risk itself, including square footage, construction type and age, roof shape and age, roof covering (tile, shingle, or other), roof attachment strength, and many more. If any of the risk characteristics are unknown, the level of uncertainty grows. If we cannot identify where a risk is located, with a specific address, the uncertainty continues to grow.
Each risk model has its own approach in developing simulated events based on its meteorological and wind engineering backgrounds. Although these events are not real, thousands are created to try and develop as many scenarios as possible and still have enough computing power to make it a feasible tool for us to use in our “normal course of business.” These models capture characteristics of events that have occurred in the past, so they can be added to the event catalog and utilized as a learning tool in the future. For example, models typically recreate wind field footprints based on a storm’s intensity, landfall point, forward speed, and ensuing degradation (weakening of the storm) once it interacts with land. As users, we can then run these historical events against our current portfolio of risks to estimate what a historical event could cost in today’s dollars.
When there is significant exposure to catastrophic risk, the less uncertainty we have, the better loss estimate we have. This not only helps us provide the right product at the right price, but also allows us to better serve our customers. Based on the severity of loss that these catastrophic risk models produce for any given event as part of a real-time response initiative, we can deploy the appropriate level of pre and post event resources.
Catastrophe risk models have now become sophisticated enough to allow us to run simulations on live events, pre-landfall. This is helpful because as a storm shifts direction, speed, and intensity, we can also shift our plans of action accordingly.
Written by Eric Gobble, Chief Risk Officer