Impact Forecasting launches scenario modeling and loss estimation tool


A new risk modeling tool which allows users to run scenarios and generate loss estimates against a range of specific historical or hypothetical catastrophe events has been launched today by Impact Forecasting, the catastrophe model development center at reinsurance broker Aon Benfield. The tool will allow users to run scenarios to analyse the potential financial impact of their potential reoccurrence today.

The tool includes historical scenarios for some of the largest catastrophe loss events to affect the globe in recent years, including superstorm Sandy in 2012, the largest insured loss European windstorm event Kyrill from 2007, Japanese tsunami events, 2011’s Thailand flooding, earthquakes and storm surge.

All of these historic events, and more, can be run through the tool to calculate estimated financial impacts should they occur again today. This will be very useful to insurers and reinsurers trying to assess their potential exposures, particularly in regions of the world where modelling has been more limited to date.

Scenarios can also be created to run hypothetical events, such as analysing events based on the maximum possible magnitudes of an earthquake or footprint of a flood. The scenarios are generated by integrating footprints (maps highlighting the extent of the area affected at a given intensity) from either Impact Forecasting’s own data, insurers and reinsurers or third party organisations such as PERILS AG.

These scenario models will importantly enable insurers and reinsurers to validate existing probabilistic models that they use and also examine specific events in territories where models are lacking or do not even exist. In addition to this, users can analyse and monitor exposures in key locations, giving them a source of data which can assist with reinsurance buying, claims management and their overall risk transfer strategies.

Impact Forecasting are making the scenario footprints available through ELEMENTS 7, its loss calculation platform. Footprints for key peril and regional hotspots that are available include:

  • US: Superstorm Sandy storm surge footprints by Impact Forecasting (developed by the SLOSH model) and PERILS (produced by SERTIT). In addition, footprints are available for hurricanes Katrina and Ike
  • Japan: 15 event scenarios for tsunami, based on events defined by the Japanese government and USGS
  • Europe: PERILS windstorm scenario events for Klaus, Xynthia, Joachim and Andrea (produced by the MeteoSuisse, German Weather Service (COSMO-EU) and EuroTempest)
  • Flood: Thailand (2011), Switzerland (2000, 2005, 2007), Slovakia (2010), Austria (2002, 2005), Poland (2010)
  • Storm Surge flood: Netherlands (1953), Germany (1962, 1976, 1994, 1995, 1999)
  • Earthquake: Morocco (Agadir 1960, Al_Hoceima 1994, 2004), Algeria (Boumerdes 2003, Djidjelli 1856, El Asnam 1980), Turkey (Erzincan 1939, Kocaeli 1999, Sultandagi 2002, Van 2011), Israel (Galilee 1837, Safed 1927, Red Sea 1995, Dead Sea 2004) and Kazakhstan (Almaty 1911)

Steve Jakubowski, President of Impact Forecasting, commented; “Any insurer or reinsurer Impact Forecasting licensee can use ELEMENTS with any event footprint to estimate scenario losses. The ELEMENTS platform unlocks the full potential of event footprints to estimate losses, computing in minutes work that would take hours to complete using Geographical Information Systems and databases.”

Adam Podlaha, international head of Impact Forecasting, said; “ELEMENTS not only runs Impact Forecasting models but, as a completely universal catastrophe modelling platform, can run any model or any footprint for any peril or territory. This is what differentiates ELEMENTS from other tools in the market.”

This kind of scenario modelling can be extremely useful to those looking to assess their risk transfer plan for its ability to handle peak peril type exposures. It could also be useful to those considering issuing a catastrophe bond or for independently assessing existing cat bonds risk of attachment under specific catastrophe event conditions.

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