BOLTON WED 330PM VEN IV.pdf

8/12/2019 BOLTON WED 330PM VEN IV.pdf

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US Earthquake Model:Its in the Details

RAA Cat Modeling 2014

Februar 12 2014

Product Manager, Global Earthquake Products


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Introduction

Its in the detailsHazard

Financial Loss

Aggregation Output


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First ste : Define stochastic event set

Hazard Modeling

How Big?

Where?


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Gutenber Richter Recurrence Relationshi

Defining Stochastic Event Set

BIAS

Too High

oo ow


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Understanding Bias:Probability of Occurrence

. n years

is1-in-30,000 years

In a 300,000 yearsimulation is sam led10 times

In 10 000 ear simulation?

If included = model too high!

Not included = model too low!


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Why is Sampling Important?

https://www.facebook.com/pages/Geomorphology-Rules/


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Minimizing Bias:California Example

http://upload.wikimedia.org/wikipedia/commons/c/cf/Flat_eq_map_anotated.png


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Quantifying Bias:Variability of 10,000 Years

Catastrophe modeling uncertaintyis significant at decision points.

Increasin event set size reduces

modeling uncertainty


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Stability of 300,000 Yearsof Simulation

Additional samples in a 300,000year simulation minimizes bias

and lessens uncertaint


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Stability of 300,000 Yearsof Simulation

beyond decision points

Stability for decision

making return periods


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Capturing AllLevels of Hazard

.(states of AR, IL, IN, KY,MS, MO, TN)

USGS

Earthquake Shaking Perilfire not included

Coverages includeBuilding, Contents, andTime Element


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Historicall

Financial Loss Modeling

StructureContents

BuildingA

Mean &Standard Deviation

Structure

ContentsTime Element

u ngB

Mean &Standard Deviation

StructureContentsBuilding Mean &

Standard Deviation


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Financial Loss Modeling the old way

? ??

UNCERTAINTY x UNCERTAINTY!


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Financial Loss Modeling the old way

Convolution??


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Example: Modeling Sub-Perils

Earthquake policies often encompasses several sub-perils:

the new way

EQSH - Earthquake ground shaking EQFF Earthquake fire following

Limits/Deductibles can be different by sub-peril.

Results are determined for each sub-peril and bycombination. Care is taken not to double/triple countexposures & losses

Ground up values dont burn rubble

Each calculation is Incremental

Sub-perils are correlated


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Calculating Sub-Perils the new way

The calculation begins at the insured coverage level.amage s a e re never excee s


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Allocate Deductible

deductible

deductible

Blanket deductible = 40


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Apply EQ Shake Sub-Limit

shake sub-limitdeductible

deductible

Earthquake ground shaking sub-limit = 20


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Apply Blanket Limit

shake sub-limitdeductible

deductible

Blanket limit = 45


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he Event Loss Table ELT re resented the 1st

Catastrophe Model Output

generation of model output format The Year Loss Table (YLT) provides a more consistent

an co eren me o o aggrega e oss


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Portfolio Analysis:California Earthquake

Simple portfolio of~80,000 risks inSouthern California


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Transparency in Model Output

ModelingTransparency: EventRecurrencemodels

YLT Statistics: California EQ

51,587

5,411 370 18 2 0

250,000

300,000

rsEQECATs YLT produces high-

150,000

200,000

fsim

ulationyea reso u on ca as rop e r s s a s cs

Outputs are direct simulations therecurrence model can be directly

242,612

100,000Numbero

evaluated by reviewing model results

0

50,000

Zero One Two Three Four Five Six

Num ero Eart qua eswit ossinayear


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Example of YLT Statistics:

$250

llions

California EQ

$200

Mi

The YLT can be used

to create theexceedance probability

$150

Loss,$

OEP_Value

-from the same data!

$50

$100 _

$0

1 10 100 1,000 10,000 100,000 1,000,000

eturn er o , ears


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$250

llions

Decomposition of the TVAR curveTVAR250FaultDriversofRisk

$200

Mi

18%

SantaMonica

S.SanAndreas

SierraMadre

PuenteHills

ElysianPark

PalosVerdes

ElsinoreFault

n ng a po n s n

the risk curves to thestochastic event libraryenables more insi hts

$150

Loss,$

OEP_Value

14%

12%8%

7%

6%

AnacapaDume

NewportInglewood

Northridge

Verdugo

Hollywood

Raymond

OakRidge

into risk

$50

$100 _

11% SanGabrielSantaSusana

5%

TVAR250EQMagnitudeDriversofRisk

$0

1 10 100 1,000 10,000 100,000 1,000,000

23%

5.5


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E ECAT rovides leadin -ed e solutions to hel measure

he Future of Cat Modeling

your risk

Eliminating inherent biases

e er con ro an ransparency

Measurable solutions

,

if you cant measure it, cant manage it


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Its in the details

rProduct Manager, Global Earthquake [email protected]

www.eqecat.com/software/rqe

BOLTON WED 330PM VEN IV.pdf

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