Aon Loss Model Offers Insurers 7.5 Million U.S. Thunderstorm Scenarios

Aon Benfield’s catastrophe model development team, Impact Forecasting, has launched a U.S. severe thunderstorm (STS) scenario model that it says can help insurers more accurately estimate annual losses based on historical data.

Severe thunderstorms can produce damaging winds in excess of 57 mph, hail 1.00 inch in diameter or greater, and occasionally tornadoes. Over the last 10 years, severe thunderstorms have overtaken tropical cyclone as the costliest peril for U.S. insurers on an average annual basis, according to the analysts.

The costliest U.S. thunderstorm outbreak on record occurred in late April 2011 across the Lower Mississippi Valley and cost insurers $7.7 billion in today’s dollars.

When aggregated, these losses from severe thunderstorms can significantly affect the profitability of an insurer’s treaty program, according to Impact Forecasting. However, these may not be accurately assessed in probabilistic models that identify the most probable maximum loss from a single event.

Impact says its new model – STS RePlay – bridges this gap by incorporating the last 12 years of historical severe thunderstorm data from the Storm Prediction Center and replaying it to create nearly 7.5 million scenarios that are used to calculate average annual losses.

The new model assesses historical severe thunderstorm events in 48 U.S. states.

“Stochastic models have historically under-reported aggregate losses due to a lack of hail and convective wind historical data,” said Steve Drews, director at Impact Forecasting. According to Drew, STS RePlay leverages existing data and improves understanding of the actual extent of current loss behavior, allowing for more informed reinsurance and underwriting decisions.

Impact Forecasting’s STS RePlay drills down to the annual average loss in addition to the probable maximum loss. Among its benefits, it can support an insurer’s expansion into new U.S. regions by identifying a credible loss experience to be expected.

Source: Aon