catastrophe modeling in the caribbean 17 may 2005
TRANSCRIPT
Catastrophe Modeling in the Caribbean
17 May 2005
Guy Carpenter 2
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)
Guy Carpenter 3
Hurricane Ivan track
Guy Carpenter 4
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
Guy Carpenter 5
The Caribbean
26 countries
Hundreds of islands
38 million people– Three major languages
Spanish 65% French 22% 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
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Guy Carpenter 7
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
Guy Carpenter 8
“PML”Definitions
“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
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“PML”
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)
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“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
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“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
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“PML”Caribbean practice
USVI 25%
Caymans 15% - 20%
Bahamas 8% - 15%
Barbados 10% - 15%
BVI 10% - 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
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“PML”Current practice
Exposure data capture and quality
Hazard frequency and severity
– Hurricane
– Earthquake
– Other perils
Damage functions
– Wind
– Water
– Shake
– Fire following
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“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
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“PML”Current practice
Cat models
– RMS
– EQE
– AIR
– Reinsurer models
– Insurer models
– Broker models
– Consultant models
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“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)?
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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?
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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
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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
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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
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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
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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
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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
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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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