Catastrophe modeling
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- This article refers to the use of computers to estimate losses caused by disasters. For other meanings of the word catastrophe, including catastrophe theory in mathematics, see catastrophe (disambiguation).
Catastrophe modeling (also known as cat modeling) is the process of using computer-assisted calculations to estimate the losses that could be sustained by a portfolio of properties due to a catastrophic event such as a hurricane or earthquake. Cat modeling is especially applicable to analysing risks in the insurance industry and is at the confluence of actuarial science, engineering, meteorology, and seismology.
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[edit] Perils analysed
Natural catastrophes (sometimes referred to as "nat cat") include:
- hurricane (main peril is wind damage; some models can also include storm surge)
- earthquake (main peril is ground shaking; some models can also include fire following earthquakes and sprinkler leakage damage)
- tornado
- flood
- wind storm/hail
- wildfire
Other catastrophes include:
[edit] Lines of business modeled
- Business personal property
- Commercial property
- Workers' compensation
- Automobile physical damage
- Leasehold improvements
- Limited liabilities
[edit] Input
The input into a typical cat modeling software package is information on the properties being analyzed. This is referred to as the exposure data, since the properties are exposed to catastrophe risk. The exposure data can be categorized into three basic groups:
- information on the site locations, referred to as geocoding data (street address, postal code, county/CRESTA zone, et cetera)
- information on the physical characteristics of the structures (construction, occupancy, year built, number of stories, et cetera)
- information on the financial terms of the insurance coverage (coverage value, limit, deductible, et cetera)
[edit] Output
The output is estimates of the losses that the model predicts would be associated with a particular event or set of events. When running a probabilistic model, the output is either a probabilistic loss distribution or a set of events that could be used to create a loss distribution; probable maximum losses (PMLs) and average annual losses (AALs) are calculated from the loss distribution. When running a deterministic model, losses caused by a specific event are calculated; for example, Hurricane Katrina or "a magnitude 8.0 earthquake in downtown San Francisco" could be analyzed against the portfolio of exposures.
[edit] Uses
Insurers and risk managers use cat modeling to assess the risk in a portfolio of exposures. This might help guide an insurer's underwriting strategy or help them decide how much reinsurance to purchase. Some state departments of insurance allow insurers to use cat modeling in their rate filings to help determine how much premium their policyholders are charged in catastrophe prone areas. Insurance rating agencies such as A. M. Best and Standard & Poor's use cat modeling to assess the financial strength of insurers that take on catastrophe risk. Reinsurers and reinsurance brokers use cat modeling in the pricing and structuring of reinsurance treaties. Likewise, cat bond investors, investment banks, and bond rating agencies use cat modeling in the pricing and structuring of catastrophe bonds.
[edit] Demand surge
Some cat models allow the user the option of including demand surge in the loss estimates, which is post-event inflation. After a large disaster, construction material and labor can temporarily be in short supply, so construction costs are inflated. The larger the impact of the event on the local economy, the larger the effect of demand surge. For example, an event that causes a $5 billion insurance industry loss might cause demand surge to increase construction costs by 5%, while an event that causes a $40 billion insurance industry loss might cause demand surge to increase construction costs by 25%.
[edit] See also
[edit] External links
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