BOSTON, June 2, 2011 ─ AIR Worldwide (AIR) today announced that Hardy Underwriting Bermuda Limited has selected AIR’s U.S. Multiple Peril Crop Insurance Model (MPCI), a weather-based crop insurance risk model that estimates underwriting gains and losses based on crop yield probabilities in the context of current conditions. The update to the AIR MPCI model reflects recent changes to the Standard Reinsurance Agreement (SRA) provided by the U.S. government to estimate retained losses for crop insurers.
Hardy underwrites across most of the major classes of commercial insurance and reinsurance business, and will leverage the AIR MPCI model to analyze agricultural reinsurance submissions. “During a volatile economic period and a changing regulatory environment, it is increasingly important that Hardy Group’s risk exposure to the multiple peril crop insurance business is modeled and managed via a number of reliable rating and analysis tools,” said Dominic Oldridge, senior underwriter of crop at Hardy Group. “AIR offers one of the preeminent independent risk management tools to help us monitor and manage our intermediary risks such as crop insurance.”
Starting in the 2011 crop year, structural changes to the Standard Reinsurance Agreement have a substantial impact on MPCI risk and profitability. “Updated SRA fund designations and gain/loss sharing mechanisms further limit the usefulness of relying on past historical loss experience,” said Dr. Gerhard Zuba, principal scientist at AIR Worldwide. “The AIR MPCI model is the only modeling solution that accurately accounts for the recent and significant changes to the Standard Reinsurance Agreement and other volatilities that affect crop insurance risk, including technological improvements, price fluctuations, and the direct effects of weather.”
The AIR MPCI model uses detailed weather observations from past growing seasons along with resulting crop yields to develop a current crop yield probability distribution for each modeled crop in each county. For major crops in the United States, the model generates a catalog of 10,000 potential year-end outcomes, including crop yields at county resolution and individual crop prices. The AIR crop event catalog captures the yield correlations between crops and between neighboring counties to track the effects of widespread weather events such as droughts. Crop insurance policy terms are applied to the modeled yield and price scenarios to quantify gross insured losses.
To accurately isolate and quantify the effects of weather on crop yield, it is necessary to remove the long-term impact of technological improvements. AIR developed the Agricultural Weather Index (AWI) to de-trend the time series of historical yields to create more accurate yield distributions. This approach explicitly accounts for extreme weather events that may otherwise be difficult to distinguish from the technological trend.
“The AIR model addresses the significant weaknesses in crop models that are based only on historical losses,” said Dr. Oscar Vergara, senior account executive at AIR Worldwide. “As a result, nearly all crop reinsurance submissions are analyzed using the AIR model, and the majority of crop reinsurers and insurers rely on it to assess their risk.”
About AIR Worldwide
AIR Worldwide (AIR) is the scientific leader and most respected provider of risk modeling software and consulting services. AIR founded the catastrophe modeling industry in 1987 and today models the risk from natural catastrophes and terrorism in more than 50 countries. More than 400 insurance, reinsurance, financial, corporate, and government clients rely on AIR software and services for catastrophe risk management, insurance-linked securities, detailed site-specific wind and seismic engineering analyses, agricultural risk management, and property replacement-cost valuation. AIR is a member of the Verisk Insurance Solutions group at Verisk Analytics and is headquartered in Boston with additional offices in North America, Europe, and Asia. For more information, please visit www.air-worldwide.com.