Catastrophe Modeling Session Reinsurance Boot Camp

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Catastrophe Modeling SessionReinsurance Boot Camp

• August 10, 2009

Aleeza Cooperman Serafin Guy Carpenter Co, LLC
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The Black Box
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Cat Modeling
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Presentation Outline

• What are catastrophe models?
• How do catastrophe models work?
• Cat modeling process
• Understanding model output
• How is model output used?
• Questions - throughout

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What are Cat Models?
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Catastrophe Modeling and Model Vendors

• What?
• A tool that quantifies risk
• How?
• Examines insured values that are exposed to
  catastrophic perils such as hurricanes,
  earthquakes and terrorism
• Why?
• Aids management decision making on
• Pricing and underwriting
• Reinsurance buying
• Rating Agencies
• Portfolio management

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Catastrophe Model Vendors

• Founded at Stanford University in 1988
• World's leading provider of products and
  services for the quantification and management of
  catastrophe risks.
• Grew in the 1990s, expanding services and perils
  covered.

• Founded in 1987
• Pioneered the probabilistic catastrophe modeling
  technology

• Founded in 1980s
• One of first catastrophe models in industry

Other models

• Most large reinsurers and other risk management
  companies have developed their own in-house models

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Modeled Perils

• Hurricane
• Wind and rain
• Demand Surge (Loss Amplification) and Storm Surge
• Earthquake
• Shake
• Fire Following
• Demand Surge and Sprinkler Leakage
• Other wind
• Winter storm
• Terrorism
• Flood (Europe)
• Wildfire

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Types of Models

• Deterministic Model
• Modeling using a single discrete event
• The event is assumed to happen without regard to
  probability
• Commonly seen as recreations of historic events
  or single- hypothetical analysis

• Probabilistic Model
• Uses a series of simulated events and accounts
  for the probability of those events over time

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Modeled Lines of Business

• Personal lines property
• Commercial lines property
• Industrial property
• Builders Risk
• Marine
• Auto physical damage (Personal Auto)
• Workers compensation
• Lives at risk Accident and Health

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Modeled Coverages

• Building/Vessel/Vehicle
• Other structures
• Contents
• Stock
• Machinery
• Inland marine
• Marine

• Time Element
• Business Interruption
• Loss of Use
• Head Count
• Payroll

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Catastrophe Modeling Terminology

• FTP Site used to transfer files to clients
  markets
• Transmittal Document includes instructions for
  accessing the FTP site, lists what files are
  posted and explains whats in them
• EDM RMS-specific database containing exposures
• RDM RMS-specific database containing analysis
  results
• CEDE AIR-specific database containing exposures
• CLF AIR-specific file containing detailed
  analysis results. Can be loaded into CATRADER in
  order to apply cat treaties.
• Unicede Text file containing aggregate (by
  county) exposure information by line of business,
  includes TIVs by county, no individual location
  detail. Used in AIR CATRADER (can be used in
  RMS) to perform aggregate analysis.
• Post Import Summary (PISR) RMS report
  summarizing exposures in a portfolio (TIV, count,
  geocoding, etc.)

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How do Cat Models work? Understanding the Black
Box
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The Four Catastrophe Model ComponentsThe Black
Box
Insurer Location and Policy Inputs
Portfolio Definition
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Defines the Event
Hazard Module
2
Vulnerability of the Structure
Engineering Module
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Loss Calculation
Financial Module
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Module 1 Portfolio DefinitionInputs
Portfolio Definition
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Hazard
2
Engineering
3
Financial
4

• Formatted exposure data
• Coverages
• Terms
• Risk characteristics
• Reinsurance
• Spatial Lookups
• Geocoding
• Hazard
• Hurricane Distance to Coast, Elevation
• Earthquake Soil type

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Module 1 Portfolio Definition Data Quality
Portfolio Definition
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Hazard
2
Engineering
3

• Completeness
• Correctness
• Construction, occupancy, etc
• Location information
• Values
• Valuation date
• Current
• Reflecting growth or reduction
• Sources of uncertainty
• Entry errors
• Old records
• Miscoding

Financial
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Module 1 Portfolio Definition Geocoding
Portfolio Definition
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Hazard
2
Engineering
3
Financial
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Individual risk locations
2
1
3
Geocoding geographic recognition
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Portfolio Definition
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Module 2 Hazard
Hazard
2
Engineering
3

• Generates the physical disturbance that is
  produced by an event
• Hurricane Site Wind Speed
• Earthquake Ground Motion
• Tornado/ Hail Event Intensity

Financial
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• Requirements
• Geocoding latitude and longitude coordinates
• Based on address information
• Geospatial information environmental and/or
  physical factors that can influence an events
  intensity at the site
• Soil conditions
• Topography and surface roughness
• Adjacent buildings

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Module 2 Hazard DefinitionHurricane Example
Portfolio Definition
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Hazard
2
Engineering
3
Financial
4
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Module 2 Hazard DefinitionHurricane Example -
Stochastic Database
Portfolio Definition
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Hazard
2
Engineering
3
Thousands of hypothetical events
Financial
4

• Windstorm Parameters
• Central Pressure
• Radius to Max. Wind
• Translational Speed
• Wind Profile
• Fill Rate
• Terrain, etc.

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Module 2 Hazard DefinitionHurricane Example -
Event Rates
Portfolio Definition
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Hazard
2
Engineering
3

• Each stochastic event is assigned a rate an
  annual frequency

Financial
4

• Last 100 years of historical data averages about
  2.4 landfalling events per year
• Traditional event probabilities distributed among
  thousands of storms

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Portfolio Definition
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Module 2 Hazard DefinitionHurricane Example -
Event Rates
Hazard
2
Engineering
3

• Near-term hurricane frequency
• Five year view (RMS)
• More than three landfalling events per year

Financial
4
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Module 2 Hazard DefinitionHurricane Example -
Calculate Site Windspeed
Portfolio Definition
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Hazard
2
Engineering
3
Financial
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Path
2
Distance (d)
Compute wind speed at each risk location Vw
f(Pc, d, regional topography)
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3
4
Hurricane
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Portfolio Definition
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Module 2 Hazard DefinitionEarthquake Example -
Site Ground Motion
Hazard
2
Engineering
3
Financial
4

• Frequency of earthquakes
• Fault location
• Fault geometry
• length
• depth
• strike angle
• dip angle
• Magnitude-recurrence
• Soil type

Epicenter
Rupture length
Fault
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Portfolio Definition
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Module 2 Hazard DefinitionLimitations
Hazard
2

• Major sources of uncertainty
• Limited historical data on events
• Unknown atmospheric elements may not be
  recognized e.g. Hurricane cycles

Engineering
3
Financial
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Portfolio Definition
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Module 3 Vulnerability Definition
Hazard
2
Engineering
3

• Data Required
• Value
• What is the value of the insured property?
• Occupancy
• How is the property used?
• Residential
• Single or Multi-Family
• Commercial
• Mercantile or Industrial
• Construction
• How is the property constructed?
• Frame, Masonry, Metal, etc.
• Lowrise or Highrise
• Age
• When was the property built?
• What building codes apply?

Financial
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Module 3 Vulnerability
Portfolio Definition
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Hazard
2
Engineering
3
Financial
4
Frame Construction
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1
Damaged Properties
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Hurricane
Damage Rates are for illustration only and are
not selected from any particular model
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Portfolio Definition
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Module 3 VulnerabilityLimitations
Hazard
2
Engineering
3

• Major sources of uncertainty
• Limited claims data
• Improper coding of risk characteristics
• Lack of understanding of structural behavior
  under severe loads

Financial
4
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Portfolio Definition
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Module 4 Financial Perspectives
Hazard
2
Engineering
3

• Calculates insured losses given the damage level
  and user risk inputs

Financial
4

• Evaluates multiple financial perspectives
• Ground up damage prior to coverage limits and
  deductibles
• Gross loss after deductibles, limits, attachment
  points
• Net loss after treaty cessions, facultative, etc.

Decreasing loss levels
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Portfolio Definition
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Module 4 Financial PerspectivesLimitations
Hazard
2
Engineering
3

• Major sources of uncertainty
• Limits versus Value at Risk
• Insurance and reinsurance structures are applied
  to loss distribution differently
• Site-level loss
• Policy-level loss

Financial
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Catastrophe Modeling Process
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The Catastrophe Modeling ProcessOverview

• Determine project scope
• Gather relevant data
• Evaluate, verify and format data
• Data quality checklist
• Data assumptions document
• Import
• Run the model
• Review the output
• Extract detailed losses
• Present results
• Post analysis portfolio management

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Understanding Model Output
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Model OutputTerminology

• Average Annual Loss (aka Pure Premium, aka
  Expected Loss) Long term average loss expected
  in any one year
• OEP - Occurrence Exceeding Probability
  Probability that a single occurrence will exceed
  a certain threshold
• AEP - Aggregate Exceeding Probability
  Probability that one or more occurrences will
  combine in a year to exceed the threshold.
• Return Period Level of loss and the expected
  amount of time between recurrences.

Critical Prob. Return Period AEP Loss OEP Loss
0.10 1,000 160 147
0.20 500 144 134
0.40 250 126 118
0.50 200 120 112
1.00 100 97 90

Pure Premium Pure Premium 8
Standard Deviation Standard Deviation 18

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Model OutputThe Event Loss Table

• Sample Event Output

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Model OutputThe Event Loss Table determining
PMLs - OEP

• Different levels of severity based on company
  appetite
• Common to monitor portfolios 1-100 year loss
  level
• In the example, 100 year loss level is saying
  that there is a 1 chance that there will be a
  single occurrence of 2.5 billion or greater in
  any given year

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Model OutputThe Event Loss Table AEP

• AEP reflects years worth of events rather than a
  single event
• i.e. there is an X chance that there will be a
  total of XX billion or greater losses in total
  in any given year

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Model OutputThe Event Loss Table determining
average annual loss

• Average annual loss is the weighted average of
  the event losses and their likelihood of
  occurring
• A company should collect at least 91million in
  CAT premium to cover its average annual expected
  loss for the peril and portfolio being modeled

Sum Product of Event Probability and Loss 91M
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Average Annual LossProperties

• AAL used to determine loss drivers
• Territory
• Zip code
• County
• State
• Rating territory
• Source
• Risk location
• Policy
• Product line
• Producer
• Characteristics
• Construction class
• Occupancy

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Understanding Model Uncertainty

• Primary Uncertainty - Uncertainty in the
  occurrence of an event
• Secondary Uncertainty - Uncertainty in the loss
  level
• Range of possible loss levels
• Inherent uncertainty
• Uncertainty in the vulnerability (damage) driven
  by
• Insufficient historical data (infrequent)
• Poor quality data
• Translating data from one region to the next (San
  Francisco 1906)

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How is Catastrophe Model Output Used?
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How Is Catastrophe Model Output Used?

• Portfolio Management
• Monitor Exposure Growth / Geographic Spread
• Evaluate Impact of Portfolio Expansion /
  Contraction
• Underwriting on New/Renewal Books of Business
• Evaluate Reinsurance Needs
• Evaluate Reinsurance Program Effectiveness
• Pricing
• Insurance Policies
• Reinsurance Treaties
• Rating Agency (e.g. A.M. Best) Requirements
• Real-time Event Analysis

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Catastrophe Model OutputPortfolio Management -
Monitoring Loss/Premium Ratio in RML
Risk Managed Layer (RML) a range of loss levels
from the EP Curve that the company wants to manage
Excluding 685 policies from portfolio
produces an optimal RML/Premium ratio
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Catastrophe Model OutputGradient Map Zip Code
Index
Index Range
ZipCodes

• Identifies how geographic areas are correlated to
  show growth/reduction opportunities
• Reveals the most critical geographic areas
  contributing loss to the RML
• Shows relative contribution to RML losses by Zip
  Code.

Top 10 ZipCodes ZipCode Index
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Catastrophe Model OutputReal-time event
monitoring
Hurricane
Wildfire
Severe Weather
Flood
Tornado/Hail
Earthquake
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ConclusionsCatastrophe Model Benefits and
Shortcomings

• Values
• Valuable risk measure
• Encourage better data tracking
• Create marketplace advantages
• Innovation
• Dangers
• Over-reliance
• Misuse
• Errors

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Questions?
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Disclaimer
The data and analysis provided by Guy Carpenter
herein or in connection herewith are provided as
is, without warranty of any kind whether express
or implied. Neither Guy Carpenter, its
affiliates nor their officers, directors, agents,
modelers, or subcontractors (collectively,
Providers) guarantee or warrant the
correctness, completeness, currentness,
merchantability, or fitness for a particular
purpose of such data and analysis. In no event
will any Provider be liable for loss of profits
or any other indirect, special, incidental and/or
consequential damage of any kind howsoever
incurred or designated, arising from any use of
the data and analysis provided herein or in
connection herewith.
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