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Catastrophe Modeling in the Caribbean PowerPoint PPT Presentation

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17 May 2005. Catastrophe Modeling in the Caribbean. The Issue. Hurricane Ivan caused an estimated $11 billion damage in the Caribbean and USA Grenada (7 Sep 04) Cayman Islands (11-12 Sep 04) Gulf of Mexico / Offshore Marine (13-15 Sep 04) United States (16-24 Sep 04)

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Catastrophe Modeling in the Caribbean

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17 May 2005

Catastrophe Modeling in the Caribbean

The Issue

  • Hurricane Ivan caused an estimated $11 billion damage in the Caribbean and USA

    • Grenada (7 Sep 04)

    • Cayman Islands (11-12 Sep 04)

    • Gulf of Mexico / Offshore Marine (13-15 Sep 04)

    • United States (16-24 Sep 04)

  • Third highest insured natural perils loss in history

  • “According to the NHC, Ivan is the sixth-strongest storm to ever hit the Atlantic basin” (13 Sep 04)

Hurricane Ivan track

The Issue

  • Insurer insolvencies and impairment

    • “Industry PMLs” provided insufficient levels of protection

    • Cat models did not generally anticipate the extent of storm surge damage in the Cayman Islands

The Caribbean

  • 26 countries

  • Hundreds of islands

  • 38 million people

    • Three major languages

      • Spanish 65%

      • French22%

      • English 14%

  • Approximate land size and population of the USA between Pennsylvania and Maine

  • Spread out over an area roughly equivalent to the USA east of the Mississippi

The Caribbean

  • Huge natural perils exposure

    • Atlantic hurricane track

    • Caribbean plate

  • Market standard natural perils deductibles

    • Typically 2% of insured values

    • Can be higher

  • Property insurance rates vary from 0.3% to 3.0% (and higher)

    • Depending on geographical location, recent loss activity, historical activity, perceived exposure, occupancy, construction, coverage, quality, cat modeling, and market practice

    • Little or no rate regulation


  • “MPL” (Maximum Possible Loss) for any given portfolio is 100% of insured values (less deductibles)

    • Absolute worst case

  • “MFL” (Maximum Foreseeable Loss) for any given portfolio may be lower than 100%

    • Generally associated with the extreme “tail” of a distribution (e.g., cat model output, realistic disaster scenario)

  • “PML” (Probable Maximum Loss) for any given portfolio may be lower than 100%

    • Explicitly or implicitly associated with a frequency (“return period”)

    • There exist a range of PMLs for various interested parties with various risk appetites


  • Could be 100% for any given location

  • Mathematically, limited to the range (0%, 100%)

    • 0% at frequent return periods (e.g., per day, per month)

    • 100% at remote return periods (e.g., per millenium, per eon)

“PML”Historical practice

  • Historically, based on extrapolation of extreme events from relatively small sample event sets

  • Insurance and Reinsurance market rules of thumb

  • Regulatory requirements

  • Rating agency requirements

“PML”Caribbean practice

  • Caribbean companies have historically been among the leaders in cat risk management of necessity

    • Reinsurer pricing and PMLs guide market practice

    • Explicitly split rates (Fire vs Cat premium)

    • CRESTA system set up in 1977 to capture exposure data by zone

    • Caribbean exposures by CRESTA zone were generally provided on reinsurance submissions

“PML”Caribbean practice

  • USVI 25%

  • Caymans15% - 20%

  • Bahamas 8% - 15%

  • Barbados10% - 15%

  • BVI10% - 25%

  • Market practice can and does vary widely from insurer to insurer due to variances in deductibles, spread of exposure, quality of construction, level of capitalization, and risk appetite

“PML”Current practice

  • Exposure data capture and quality

  • Hazard frequency and severity

    • Hurricane

    • Earthquake

    • Other perils

  • Damage functions

    • Wind

    • Water

    • Shake

    • Fire following

“PML”Current practice

  • Financial variables

    • Coverages

    • Deductibles

    • Coinsurance

    • Insurance to value

    • Sublimits

    • Hours clauses

    • Loss Adjustment Expense

    • Demand surge

  • Combination of factors produces “PML” estimates

    • Cat models often provide our current best estimates of damage for “modeled” perils and events

“PML”Current practice

  • Cat models

    • RMS

    • EQE

    • AIR

    • Reinsurer models

    • Insurer models

    • Broker models

    • Consultant models

“PML”Current practice

  • Post-event, cat modelers learn from losses and adjust models

  • Recent Caribbean events

    • Gilbert (1988)

    • Hugo (1989)

    • Marilyn & Luis (1995)

    • Georges (1998)

    • Ivan (2004)?

Caribbean PMLsScenario estimates

  • Caribbean “MFLs” often assume it’s possible for an island to be hit with a SS-5 hurricane

    • “Close” vs. “Direct” hit?

    • Fast-moving vs. slow-moving?

    • Dry vs. wet storm?

    • Without storm surge or with?

Caribbean PMLsScenario estimates

  • Limited geographical scope (single island)

    • Easier to model “small” islands (e.g., Caymans, Barbados, St Croix)

    • More difficult for “larger” islands (e.g., Puerto Rico, Hispaniola, Cuba), as storm intensity will vary over the island

    • Portfolio damage is weighted average of individual location damage

Caribbean PMLsProbabilistic estimates

  • Cat models are collections of event scenarios

    • Discrete approximations, with probabilities attached to each scenario

    • Not exhaustive

    • Limited perils

    • Calibrated using historical experience

      • Recalibrated as required, based on research and actual event experience

Risk Management in the Caribbean

  • Define “PML” as the maximum loss an insurer can reasonably expect to pay with 99% certainty

  • Define “PML Bust” as the occurrence of an event that produces loss in excess of the “PML”

    • “PML Bust” is unlikely, but not impossible

    • “PML Bust” events will in all likelihood happen every year, somewhere in the world

Risk Management in the Caribbean

  • First principles

    • PMLs range from 0% to 100%

    • PMLs are associated with return periods (frequency)

    • PMLs less than 100% will always (eventually) be exceeded

Risk Management in the Caribbean

  • Many Caribbean insurance companies cede away most premium proportionally

    • Geographically concentrated portfolios and high levels of natural perils exposure

    • Security of insurance product is dependent on security of backing reinsurance and Event Limits purchased

    • Insurance company net results are largely dependent on overrides and volume (rather than profitability of rates and risk appetite)

  • Costs can still be high for those who purchase a mix of excess of loss and proportional reinsurance

    • Geographically concentrated portfolios and high levels of natural perils exposure

Risk Management in the Caribbean

  • Insurance is a business

    • It’s impractical to hold capital and/or purchase reinsurance up to full limits (“MPL”)

      • Suboptimal use of capital

    • The market (e.g., insureds, regulators, ratings agencies) deems it acceptable to provide less than perfect insurance and reinsurance security

    • Need to quantify risk appetite

      • Probability of default

      • Risk-equivalent returns

    • Need to use best available tools in a cost-effective manner to make sound business decisions

      • Multiple cat models, combined with first principles

Risk Management in the Caribbean

  • Most people want certainty, not “sufficiently low probabilities”

    • Most insurance companies think and plan in terms of “point estimates” rather than distributions

    • Regulators want policyholders to be paid

    • Cat models should be used as a guide, not a rule

      • Never lose sight of first principles

    • Deterministic thinking pervades society

      • Statistics is a relatively young science


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