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Catastrophe Models (Property)

Background

Last Updated: 6/2/2025

Issue: is a computerized process that simulates thousands of plausible catastrophic events scenarios. Simulated event scenarios are based on realistic event parameters drawing data from meteorological history, geology, and geography to probabilistically model what could happen in the future. These scenarios are used by the models to quantify the expected damages for an underlying portfolio of exposures using an engineering approach. Lastly, the insured loss is calculated by incorporating underlying insurance policy coverage, terms, and conditions. These models provide valuable insights for risk identification, risk quantification and risk management strategies by taking a multi-disciplinary approach of science, engineering, and mathematics/statistics.

Catastrophe models have been rapidly evolving since their introduction in the 1980s based in part through technological advances and higher resolution exposure data. Catastrophe models were developed to estimate the probability of loss due to extreme weather events but have expanded to apply to non-weather risks including casualty or liability loss, terrorism, and cyber-attacks.

Cat Model Basics: Catastrophe models are used to quantify the financial impact from a range of potential disasters, looking beyond limited historical loss data and using the latest scientific research regarding current and near-term environmental conditions. Models can estimate a range of direct, indirect, and certain types of residual losses. Direct losses result from incidents such as damage to physical structures and contents, deaths, and injuries. Examples of indirect loss are loss of use, additional living expenses, and business interruption. Residual losses include effects such as demand surge, which is a temporary increase in the cost of labor and construction materials immediately after a catastrophic event.

Basic components underpinning a catastrophe model include hazard, vulnerability, exposure, and financial. The first three components are based on the widely known concept of ‘’ as shown in the picture. Depending on the source, these modules’ names can slightly vary, but the underlying function of the modules remains the same.

A diagram of risk and exposure</p>
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Hazard: This module contains a large catalog of simulated events representing a wide range of plausible scenarios. These simulated events are stored in the event catalog, which also provides information on how frequently events of certain size are likely to occur, and where such events are likely to occur. Each event in the event catalog is characterized by a specific strength, size, location, path, and annual probability of occurrence (also known as event rate). Every event scenario in the catalog is associated with the unique event footprint reflecting the relative intensity and extent of the hazard over the event’s path during the event duration.
Vulnerability: The vulnerability module quantifies the expected damage for the underlying exposures from an event based on the building characteristics and local event intensity using damage functions. Damage functions are essentially equations that are used to compute the amount of expected damage for a given hazard intensity (such as windspeeds) based on characteristics (e.g., construction, occupancy, building height) of the property at risk.
Exposure: The exposure module houses the user’s insurance portfolio data, which includes location-specific information, along with risk characteristics and insured values. The exposure module also includes information about insurance policy terms and conditions such as deductibles, limits, and any applicable reinsurance.
Financial: The financial module calculated the financial losses from all the event scenarios that the underlying exposures are exposed to. Insured loss estimates are generated based on policy conditions, such as deductibles, limits, attachment points as well as applicable reinsurance. The losses from all the event scenarios are aggregated to create a loss probability distribution. Loss distribution is used to derive expected losses as well as the likelihood of different loss levels.

Cat Model Uses: Catastrophe models produce outputs that can be used by insurance industry professionals in various ways. An exceedance probability (EP) curve calculates the loss for each event in the portfolio and sorts all scenarios from smallest to largest, either by the sum of all losses (aggregate loss) or the largest event each year (occurrence loss). This EP curve can then be used to rank each event by the probability of the event exceeding the aggregate or occurrence-based loss amount. Probable maximum losses based on specific return periods can also be identified from the EP curve. An average annual loss (AAL) can be calculated on an occurrence (largest event within a year) or aggregate (all events within a year) basis and represents the loss amount averaged across all years in the event set.

The output derived from catastrophe models is widely used for many purposes, including ratemaking, premium mitigation credit quantification, reinsurance purchase, capital, and solvency assessment. In July 2018, the American Academy of Actuaries developed a paper, to provide overviews on uses of catastrophe model output in selected actuarial tasks.

Background: Historically, insurers used historical averages to estimate catastrophe risk. Because catastrophes are volatile and occur infrequently, even using 20-year averages may not adequately represent the true risk the company is exposed to. This came to light in 1992, when Hurricane Andrew caused $20 billion in insured losses, becoming the largest loss event at the time and causing several insurers to become insolvent. This led the insurance industry to adopt catastrophe modeling as a way to improve risk management through better loss estimation. Catastrophe models have continued to evolve to reflect a better understanding of the underlying assumptions, intricacies, and science of a peril and its loss drivers. Models are continually advanced as new events occur, leading to improved knowledge and data.

The 2004 and 2005 Atlantic hurricane seasons had a substantial impact on modeling assumptions. Two consecutive years of record activity and losses brought a new focus on the impact of aggregate losses from multiple hurricanes. In addition, Hurricane Katrina in 2005 caused more losses from secondary flooding than the traditional wind generated events. As such, modelers began to incorporate the impact of secondary perils in catastrophe models. Hurricane Katrina also highlighted the impact of secondary factors, such as demand surge, evacuation, sociological risks, and political influence. Models are increasingly using combinations of economic and sociological modeling to incorporate loss amplification resulting from these additional factors.

Actions

Status: In 2022, the Climate and Resiliency (EX) Task Force recommended a Catastrophe Modeling Center of Excellence (COE) be established within the �Ӱ��Ƶ Center for Insurance Policy & Research. The COE provides regulators with technical training and expertise regarding catastrophe models and information regarding their use within the insurance industry. The COE also conducts research utilizing outputs from catastrophe models to assess the risk of loss from natural hazards. A regulator-only site has been created to share information, resources and tools. Regulators who would like access to the site should send an email request to Connie Roland at croland@naic.org.

In 2021, the Task Force issued a referral to the Catastrophe Risk (E) Subgroup to evaluate catastrophe perils for possible inclusion in the Risk-Based Capital charge (other than hurricane and earthquake which were added in 2013). Beginning in 2022, modeled loss data for wildfire started being collected for informational purposes only. Starting with yearend 2024, additional information about severe convective storms and climate-conditioned catastrophe risks is also being collected for information purposes only.

The �Ӱ��Ƶ Catastrophe Insurance (C) Working Group of the Property and Casualty (C) Committee serves as a forum for discussing issues and solutions related to catastrophe models. The Working Group also maintains the �Ӱ��Ƶ . The Handbook explores catastrophe computer models and issues that have arisen or can be expected to arise from their use. It provides guidance on areas and concepts to allow for better understanding and to stay updated about cat models. The Handbook is currently undergoing review and updates and will be re-branded as the �Ӱ��Ƶ Catastrophe Model Primer, the draft of which was recently exposed for public comments in late 2024.