Catastrophe modeling [1] (also known as cat modeling) is the process of using computer-assisted calculations to estimate the losses that could be sustained due to a catastrophic event such as a hurricane or earthquake. Cat modeling is especially applicable to analyzing risks in the insurance industry and is at the confluence of actuarial science, engineering, meteorology, and seismology.

Catastrophes/ Perils

Natural catastrophes (sometimes referred to as "nat cat")[2] that are modeled include:

Human catastrophes include:

Lines of business modeled

Cat modeling involves many lines of business,[4] including:

Inputs, Outputs, and Use Cases

The input into a typical cat modeling software package is information on the exposures being analyzed that are vulnerable to catastrophe risk. The exposure data can be categorized into three basic groups:

The output of a cat model is an estimate 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.[6] 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.

Cat models have a variety of use cases for a number of industries,[7] including:

Open catastrophe modeling

The Oasis Loss Modelling Framework ("LMF") is an open source catastrophe modeling platform. It developed by a nonprofit organisation funded and owned by the Insurance Industry to promote open access to models and to promote transparency.[8] Additionally, some firms within the insurance industry are currently working with the Association for Cooperative Operations Research and Development (ACORD) to develop an industry standard for collecting and sharing exposure data.[9]

See also

References

  1. ^ Mitchell-Wallace, K. Jones, M., Hillier, J. K., Foote, M. (2017) Natural catastrophe risk management and modelling: A practitioner’s guide. Wiley ISBN 978-1118906040.
  2. ^ "NatCat Models" (PDF). Schweizerische Aktuarvereinigung. Retrieved December 23, 2019.
  3. ^ Edwards, Scott. The Chaos of Forced Migration: A Means of Modeling Complexity for Humanitarian Ends
  4. ^ Kaczmarska, Jo; Jewson, Stephen; Bellone, Enrica (2018-03-01). "Quantifying the sources of simulation uncertainty in natural catastrophe models". Stochastic Environmental Research and Risk Assessment. 32 (3): 591–605. doi:10.1007/s00477-017-1393-0. ISSN 1436-3259.
  5. ^ Malyk, Dmytro (2014-05-15). "Presentation: Introduction to Cat Modeling". Slideshare.net. Retrieved 2019-12-23.
  6. ^ "About Catastrophe Modeling". www.air-worldwide.com. Retrieved 2019-12-23.
  7. ^ Extreme Events and Property Lines Committee (July 2018). "USES OF CATASTROPHE MODEL OUTPUT" (PDF). American Academy of Actuaries. Retrieved December 23, 2019.
  8. ^ "Overview — Oasis LMF 0.1.0 documentation". oasislmf.github.io. Retrieved 2019-12-23.
  9. ^ "Association for Cooperative Operations Research and Development". acord.org. Retrieved 2019-12-23.