Fires caused damage in San Fernando Valley, Malibu, Venice
Liquefaction at Simi Valley
Northridge-PCS Estimates
Nisqually/(Seattle) (2001)
Magnitude 6.8, 400 people injured
Major damage in Seattle-Tacoma area
Insured Damage $305 Million
Max. intensity VIII in Pioneer Square area
Landslides in the Tacoma area
Liquefaction and sand blows
Earthquake vulnerability factors
Building construction
Unreinforced masonry vs. seismic designed
Building height
Taller buildings vulnerable to long-period waves
Soft story (hotel lobby) increases vulnerability
Building location
Soil type is critical
Fire following losses can be very significant
Financial model factors
CEA mini-policy
Earthquake sublimits on commercial
Per policy
Per location
Regional sublimits (e.g. CA only)
Interlocking clause
Reduces event loss across multiple treaty years
Hard to model
Differences between models
Detailed vs. Aggregate
Detailed models better capture these vulnerability and financial considerations
Fire Following
Significant difference in modelers
New Madrid
Significant difference in return period
Earthquake prediction
Earthquakes not a Poisson process
Poisson implies inter-arrival times are exponentially distributed (memory-less)
1999 Izmit (Turkey) Earthquake
Increased risk for a quake in Istanbul
San Andreas Fault
Is an earthquake due? Where on fault?
Izmit Quake ctd.
60% chance of Istanbul earthquake in next 30 years - Thomas Parsons, USGS
Researchers took into account the stress transfer from a magnitude 7.4 earthquake in Izmit, Turkey in August 1999.
San Andreas Fault
Over the past 1,500 years large earthquakes have occurred at about 150-year intervals on the southern San Andreas fault.
As the last large earthquake on the southern San Andreas occurred in 1857, that section of the fault is considered a likely location for an earthquake within the next few decades
The San Francisco Bay area has a slightly lower potential for a great earthquake, as less than 100 years have passed since the great 1906 earthquake
Cat Models and Earthquake Pred.
At least one cat modeling firm has variable earthquake rate (changes with calendar date)
Annual model updates allow for changing earthquake rate with time.
Hurricanes
Meteorology of Hurricanes
Frequency of Hurricanes by category
Recent Hurricane Activity
Hurricane Andrew
Vulnerability and Financial Models
Hurricane prediction (?)
Meteorology of Hurricanes
Occur in both Northern and Southern Hemispheres
Don’t occur on the equator
Factor in the 2004 Tsunami tragedy
Coriolis Force
spin clockwise in southern hemisphere
spin counter-clockwise in northern hemisphere
Need warm sea surface temperatures
Always travel from east to west
Safir-Simpson Scale
Atlantic Basin Hurricanes
US Landfalling Hurricanes
2004 Season
2003 Season
2004 Hurricanes
Charley: 8/9-14, Small storm- strengthened rapidly to Cat 4 just before FL landfall
Frances: 8/25-9/8, Larger storm, weakened from Cat 4 to Cat 2 before FL landfall
Ivan: 9/2-9/24, Long-lived, Cat 5 storm, weakened to Cat 3 before AL landfall
Jeanne:9/13-9/28, Crazy Cat 3 storm, same landfall as Frances but smaller & faster
2004 Hurricanes ctd.
Modeling Issues raised by 2004 storms
Storm Surge
Demand Surge
Frequency Distribution of Hurricanes
Offshore oil rig losses
Caribbean Clash modeling
Hurricane Andrew
Period: 8/16-8/28 1992
Small, intense CAT 5 Cape Verde storm
Affected Bahamas, S. Florida, Louisiana
Damage $25 BN, $15.5 Insured US damage
Central Pressure 992 mb, third lowest since 1900
Vulnerability model factors
Construction
Concrete bunkers vs. mobile homes
Location
Properties near ocean very vulnerable to storm surge
Secondary modifiers
E.g. Roof tie downs
Financial model factors
percentage deductibles can be very significant
New season deductible in FL
What is a risk?
Issue for per-risk treaties
For hurricanes, widely dispersed buildings on one policy often considered one “risk”
E.g. school district
Differences between models
Detailed vs. Aggregate models
Location (distance to coast) is critical
Need detailed model to properly assess
Northeast Hurricane
Significant difference between modelers
Caribbean clash
Not all modelers facilitate this analysis
Hurricane Prediction
Data/Modeling Issues
Need for completeness
Reinsurers need compensation for all risks being accepted
Model all exposures
Model all perils
Run multiple models
Missing exposures
Sometimes only get tier 1 wind counties
Sometimes only certain states
E.g. CA, Pacific NW, New Madrid only
Other shake exposure ignored (e.g. East Coast)
Fire following exposures ignored
Sometimes entire books of business are missing
Must cross-check cat model exposure data
Premium often n.a. , policy counts (?)
Modeling Tricks
Failing to load for LAE
Failing to consider demand surge
Abuse of secondary modifiers
“Really, all my policyholders have roof tie-downs!”
Running all the models and providing the lowest
different modeling firms
Aggregate vs. detailed models
Portfolio Management
Event Set framework is a powerful tool for portfolio management
Ability to model portfolio’s risk vs. return
Determine portfolio capital and allocate to individual deals
Portfolio Framework Example
Consider two countries
Oceania and Eurasia
5 possible events for each country
Industry losses specified
Goal-determine risk vs. return for various reinsurance portfolios
Event Sets
Create a set of Simulation Years
Check against Poisson
Contracts
Calc. Contract Losses by year
Compute AAL and expected profit for each contract
Distribution of profit/(loss)
Calculate return on capital
Portfolio Effects
Now assume that the reinsurer’s portfolio consists of certain shares of these 3 contracts
Want to calculate the overall portfolio capital and
Each contract’s share of this portfolio capital
Portfolio
Consider the following portfolio:
P = 20% A + 10% B + 5% C
Then consider 3 other portfolios
P+0.1% A
P+0.1% B
P+0.1% C
Portfolio ctd.
Allocating Portfolio Capital
The portfolio capital can be allocated as follows:
Cap[20%A]= 20%/0.1% * (422.89-422.02)=174
Cap[10%B]= 10%/0.1% * (422.56-422.02)= 54
Cap[5%C] = 5%/0.1% * (425.90-422.02)=194
-------------- --------
Cap[Portfolio] = 422
Return on Allocated Capital
Tail oriented Capital Metrics
Approach also works for tail oriented capital metrics- e.g. TVAR
Define capital = 3 x TVAR (80%)
Tail oriented ROAC
Allocated Capital Calcs
As before, alloc. capital based on marginal
For example, for the 20%A contract:
450 = (793.5-791.25)/0.1% * 20%
Portfolio Cap = Sum of Alloc. Capitals
N.B. according to this capital metric, 10%B has the highest ROAC in the portfolio
Summary
CAT Models provide a powerful tool for portfolio management
Can be used to derive capital for a contract within a portfolio and ROC
There is no “contract order” issue as is sometimes thought
