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Catastrophe Models


Issue:  A catastrophe model 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. 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 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 loss includes demand surge due to temporary increase in cost of labor and inflation in construction material 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 ‘Risk Triangle’ 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.

  • Hazard: This module contains a large catalog of simulated events representing a wide range of plausible scenarios Event catalog provides information on how frequently events of certain size are likely to occur, as well as where such events are likely to occur. Each event in the event catalog is characterized by a specific strength or size, location, or 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: Exposure Module houses the portfolio data such as location specific information. Building’s location 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. The financial module measures the value at risk or the probability of financial loss from an event, based on a given time period. Insured loss estimates are generated based on policy conditions, such as deductibles, limits, and attachment points. 
  • 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, produces either by the sum of all losses (aggregate loss) or the largest event each year (occurrence loss) and ranks each event by the probability of the event exceeding the aggregate or occurrence-based loss amount. 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 ratemaking, premium mitigation credit quantification, reinsurance purchase, capital, and solvency assessment. In July 2018, the American Academy of Actuaries developed a paper, Uses of Catastrophe Model Output to provide overviews on use of catastrophe model output in selected actuarial tasks.

Background: In 1992, Hurricane Andrew caused $20 billion in insured losses, becoming the largest loss event at the time, 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. Unique to prior hurricanes, Katrina in 2005 resulted in 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.


Status: In 2022, the Climate and Resiliency (EX) Task Force recommended a Catastrophe Modeling Center of Excellence (COE) be established within the NAIC 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 Amy Lopez at

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 is being collected for informational purposes only. The Subgroup has formed an ad hoc group to review severe convective storm models. 

The NAIC 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 NAIC Catastrophe Computer Model Handbook. 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 NAIC Catastrophe Model Primer.

On March 23, 2021, the Capital Adequacy (E) Task Force met to discuss various issues, including CAT models that deviate from the primary vendor models: (1) internal company CAT models; (2) vendor CAT models with adjustments or different weights; and (3) derivative models based on the vendor models. Instructions for evaluating internal CAT models are included in the risk-based capital (RBC) instructions. The Task Force discussed that in-depth instructions on the derivative model and the vendor models with adjustments may be necessary.

In July 2021, the Actuarial Standards Board adopted revisions to the Actuarial Standard of Practice No. 38, Catastrophe Modeling (for All Practice Areas) providing guidance to actuaries with respect to selecting, using, reviewing, or evaluating catastrophe models.


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