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Why Don’t Cat Models Work or Do They?
The Role of Models: A View From Both Sides CAS Presentation May 8, 2006 Maria Kovas
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Overview Role of Modeling during the Quiet Years
Original Role of Modeling Change in Expectations Return to the basics
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Post Event Loss Evaluation
During the Quiet Natural Catastrophe Years Leading Role in: Reinsurance Pricing Underwriting Primary Pricing Business Planning Post Event Loss Evaluation
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Original Role: Diagnostic Device
Distribution of Exposure Identification of High Density Areas Review of Adjacency of Risk in Key Peril Areas Consideration of Redistribution of Exposure
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Identification of Drivers of Risk
Review of PML in Modeled for Modeled Perils Application of Secondary Peril information Modeled Un-Modeled
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Consideration of Data Quality and the Impact on the Diagnostic Process
Inclusion of additional sublimits and deductibles Identification of more building characteristics Cost Benefit analysis of modifying systems to update the data
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Metrics Determination of Business/Underwriting Goals
Review the current position of the organization Chart the differences and devise options to achieve Goals Periodic review and updates of movement in the process
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Underwriting Cycle
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Catastrophic Response
It is not possible to plan for a Catastrophe It is possible to evaluate event curves Event drills Deployment of claims teams Setting management expectations
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Factors Contributing to the Change in Expectations:
Peril Modeling vs. Total losses Second Generation Modelers The Quiet Period Data Issues Updates to methodologies
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Peril Modeling vs. Total losses
Models are based on specific perils Review of actual events to calibrate model outputs Quiet period limited the number events for calibration Actual losses are based on all affected perils
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Second Generation Modelers
First Generation-Professional insurance/broker/reinsurers-recruited to use the models because of aptitude or interest Second Generation-Professional modelers recruited for technical aptitude and skill in running the models
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The Quiet Period Modeling became the sole focus of loss estimates
Comfort level because losses were within a tolerable variance
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Data Issues Models capable of refinement with additional data points
Data capture may be not updated to match the capabilities of the models Valuation issues New financial structures
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Updates to methodologies
New interpretation of historic data Updates to the science used in the models Changes to the methodology Re-calibration of models and vulnerabilities
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Re-establishing the Role of Modeling
Model data as Currency Return to the basics Ensemble Reporting Setting expectations
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Model data as Currency:
Definition of the data coin A data formatted in such a manner to be shared among industry business interests Standard evaluation of the data coin determine the confidence in the data Confidence in the data leads to rate considerations
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Return to Basics Underwriting Cycle
Review Reporting provided to management Recreate event drills Refresh training Update data capture and interface
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Ensemble Reporting Create Multiple Views of Exposure
Model what is available Identify and communicate gaps Evaluate Secondary Perils Use Mapping
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Communicate Anticipate questions Consider key issues in the firm
Review the diagnosis Determine if the remedies are cost effective
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