Posts Tagged ‘Powers (Imelda)’



September 13th, 2018

Managing Catastrophe Model Change

Posted at 1:00 AM ET

powers_imelda_71x88Imelda Powers, Senior Cat Management Advisor, Asia Pacific, Global Strategic Advisory

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Incorporating new hazard and claims insights can improve the estimates derived from catastrophe models. By re-analyzing historical events using the latest scientific methods or refining claims with more granular geographical and line of business breakdowns, we can update models with the latest expertise and data. But model changes that yield large swings in loss estimates for frequent events must be carefully scrutinized to understand assumptions and processes in order to truly support ownership of risk. Continue reading…

May 17th, 2018

Building for Resilience: How to Avoid a Catastrophe Model Failure

Posted at 1:00 AM ET

Here we bring together our recent multi-part series on model resilience by Guy Carpenter’s Global Chief Catastrophe Modeler, Imelda Powers.

Since commercial catastrophe (CAT) models were first introduced in the 1980s, they have evolved as new scientific discoveries and claims insights emerged. Despite the sophisticated nature of each new generation of CAT models, occasionally a model misses a significant loss driver for a particular peril. This occurs when a previously hidden attribute reveals itself through unprecedented intensity. Lessons from such surprises stimulate model improvements as our understanding of the physics of the peril and its damage potential, increase. Through this process, models mature over time.

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April 26th, 2018

Building for Resilience: How to Avoid a Catastrophe Model Failure: Part IV

Posted at 1:00 AM ET

Imelda Powers, Global Chief Catastrophe Modeler

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Valuation Assumptions

There is no database of agreed property, contents or business interruption valuations among vendors or insurers.  Any user’s particular valuation may come from databases of property prices, or rebuild values from claims adjusters and building surveyors. If the model’s assumed valuations are under- or over-estimated, then the damage function may over- or under-compensate in order to balance to historical industry event losses during the model-building process. Consequently, it is important that the user adjust the damage module to reconcile these differences.

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April 25th, 2018

Building for Resilience: How to Avoid a Catastrophe Model Failure: Part III

Posted at 1:00 AM ET

Imelda Powers, Global Chief Catastrophe Modeler

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If resources permit, an insurer may carry out additional, micro level model suitability analyses - including a review of model hazards and vulnerabilities using the latest scientific literature and engineering studies. Guy Carpenter’s Model Suitability Analysis (MSA)® framework is designed to guide users through such an analysis.

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April 24th, 2018

Building for Resilience: How to Avoid a Catastrophe Model Failure: Part II

Posted at 1:00 AM ET

Imelda Powers, Global Chief Catastrophe Modeler

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Model Suitability Analysis

There is a repertoire of tests, at both the macro and micro levels, to evaluate the merits of a CAT model.  Regardless of resources, insurers should analyze how each test’s result informs their view of risk. Here we review the macro level.

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April 23rd, 2018

Building for Resilience: How to Avoid a Catastrophe Model Failure: Part I

Posted at 1:00 AM ET

Imelda Powers, Global Chief Catastrophe Modeler

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Since commercial catastrophe (CAT) models were first introduced in the 1980s, they have evolved as new scientific discoveries and claims insights emerged. Despite the sophisticated nature of each new generation of CAT models, occasionally a model misses a significant loss driver for a particular peril. This occurs when a previously hidden attribute reveals itself through unprecedented intensity. Lessons from such surprises stimulate model improvements as our understanding of the physics of the peril and its damage potential, increase. Through this process, models mature over time.

Continue reading…

November 29th, 2012

Taking Control of Quantifying Your Natural Catastrophe Risk: Part II

Posted at 1:00 AM ET

Elizabeth Cleary, Managing Director, Valerie Kloepfer, Managing Director, Imelda Powers, Ph.D., Global Chief Cat Modeler, Sherry Thomas, Head of Catastrophe Management - Americas and James Waller, Ph.D., Research Meteorologist
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Why Do Results for North Carolina Differ So Dramatically Between ALPHA and GAMMA?

  • Overall frequency is similarly modeled for North Carolina in both ALPHA and GAMMA. However, GAMMA has slightly higher overall modeled frequency (historical view), while ALPHA has a measurably higher modeled frequency of Cat 3-5 storms for North Carolina, and therefore fewer lower severity Cat 1-2 storms versus GAMMA.
  • In the ALPHA model, North Carolina storms generally have larger footprints, pushing the storms further north and west, even producing losses in areas where GAMMA does not generate any loss. For a state like North Carolina, where there are high exposure values inland, this is generally a key driver for larger ALPHA losses in the state. Factors that could reverse the aforementioned ALPHA and GAMMA comparison are usually not strong enough to reverse the general statewide observations. Such factors include a larger GAMMA damage ratio especially at higher wind speeds (impacting coastal counties) and larger wind deductible impact modeled in ALPHA.
  • Inland portfolios modeled in ALPHA are impacted by ALPHA’s slower wind decay for storms making landfall in North Carolina, typically resulting in larger losses for those portfolios versus GAMMA. The example in Figure 2  from Hurricane Isabel shows losses going all the way up to northwest Pennsylvania, which seems to be consistent with the reported impacts of the storm. Historical storm loss footprints for Hugo (1989), Fran (1996) and Floyd (1999) show similar patterns, with GAMMA losses typically truncated geographically more so than observed for these actual events.

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November 28th, 2012

Taking Control of Quantifying Your Natural Catastrophe Risk: Part I

Posted at 1:00 AM ET

Elizabeth Cleary, Managing Director, Valerie Kloepfer, Managing Director, Imelda Powers, Ph.D., Global Chief Cat Modeler, Sherry Thomas, Head of Catastrophe Management - Americas and James Waller, Ph.D., Research Meteorologist
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Amidst the fast pace and frequent trends and changes in the market, a single business conversation can stand out. With the passage of time, one sees that it was a precursor to what would become a consistently held view - a sort of drumbeat of the times.

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April 26th, 2012

Spatial and Temporal Earthquake Clustering – Earthquake Aftershocks, EQECAT Perspective: Forecast Models

Posted at 1:00 AM ET

Earthquake Forecast Models

Earthquake sequences appear to be globally continuous over time. This suggests that seismic sources or faults may be part of a critically-stressed, self-organized network where earthquakes occur as a chain reaction with respect to one another. Earthquakes trigger other earthquakes as stresses move around in the fault network.

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