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Exposure,hazard,vulnerability – insurance risk management with and without climate change

Mr. Andrew Mitchell

exposure, hazard, vulnerability – insurance risk managementwith and without climate change

Andrew MitchellWillis Analytics

Climate Change: Impacts on the CaribbeanCaribbean Community Climate Change CentreUniversity of the West Indies16 June 2007

©Copyright 2007 Willis Limited all rights reserved.

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insurance risk identification and quantification

• the cost-benefit of insurance - smoothing, pooling, diversifying

• experience-based rating - generalised linear models

• poor identification of extremes - no geography, no science, no engineering

• reinsurance provides cover for catastrophe event accumulations of loss

• cat modelling introduced to reinsurance sector in early 1990s

• discipline this created is as important as the numbers in output

• cat modelling has become a pre-requisite for new capital, esp Bermuda

• provided demonstrable stability - far fewer failures in 2000-2005 vs 1990-1995

• cat modelling is cross-disciplinary and multi-component

• stochastic event sets

• probabilistic treatment of primary and secondary uncertainty

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catastrophe loss models: structure

HAZARD

• event generation

• local intensity calculation

VULNERABILITY

• mean damage ratios

• building inventory

FINANCIAL• applying insurance terms and conditions

location details policy conditions

EXPOSURE• sums insured

• risk type• coverage type

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catastrophe loss models: output

Island Jamaica Jamaica Jamaica JamaicaParish St. James St. James St. James St. JamesOccupancy Temporary Lodging Temporary Lodging Temporary Lodging Temporary LodgingConstruction Unknown Reinforced Concrete Reinforced Concrete Reinforced ConcreteHeight Unknown Unknown 4 stories 4 storiesYearbuilt Unknown Unknown Unknown 2006         Return Period Occupancy only + Construction + Height + Year Built

1000 61.36% 57.41% 46.01% 44.17%750 56.49% 52.72% 41.26% 39.53%500 49.48% 46.06% 34.65% 33.11%250 37.50% 34.82% 23.87% 22.64%200 33.74% 31.29% 20.60% 19.47%100 22.59% 20.84% 11.40% 10.60%50 12.72% 11.58% 4.39% 3.95%25 5.00% 4.40% 0.69% 0.57%10 0.23% 0.17% 0.00% 0.00%5 0.00% 0.00% 0.00% 0.00%

0%

10%

20%

30%

40%

50%

60%

70%

80%

0 100 200 300 400 500 600 700 800 900 1,000

return period (year)

gro

ss

los

s O

EP

as

% o

f in

su

red

va

lue

Occupancy only

+ Construction

+ Height

+ Year Built

model sensitivity analysis

RMS RiskLink v6.0

hurricane EP curve

primary modifier variations

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exposure: US land-falling hurricane losses – actual

source: Normalized Hurricane Damages in the United States: 1900-2005

Pielke et al Natural Hazards Review (submitted)

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exposure: US land-falling hurricane losses – revalued

source: Normalized Hurricane Damages in the United States: 1900-2005

Pielke et al Natural Hazards Review (submitted)

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exposure: growth and data capture

• population growth

• growth in property values

• growth of urban concentrations

• settlement and development in exposed regions

• rise in standard of living

• increased international trade - marine cargo exposure

• increased insurance penetration

• increased correlation means exposure to cat events rises faster than income base

• insurance exposure data:

• capture and reporting limited by legacy systems

• quality and type has not been standardised

• trans- and multi-national policies mean location identification is confused

• ? largest source of error in modelling

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hazard: source of losses

hurricane earthquake

hurricane earthquake

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hazard: relative size of losses

RMS v6.0 Jamaica hurricane (long-term historical event set) - buildings only

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

0 100 200 300 400 500 600 700 800 900 1,000

return period (years)

OE

P g

ros

s lo

ss

as

% o

f to

tal i

ns

ure

d v

alu

e

IED WS (LT)

50:50 Res:Com WS (LT)

20:80 Res:Com WS (LT)

20:60:20 Res:Com:Hotel WS (LT)

RMS v6.0 Jamaica earthquake - buildings only

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

0 100 200 300 400 500 600 700 800 900 1,000

return period (years)

OE

P g

ros

s lo

ss

as

% o

f to

tal i

ns

ure

d v

alu

e

IED EQ

50:50 Res:Com EQ

20:80 Res:Com EQ

20:60:20 Res:Com:Hotel EQ

other types of hazard:

• fire

• theft

• explosion

• terrorism

• volcanic eruption

other classes of business:

• liability

• health

• aerospace

• marine

• credit

• finex

hurricane earthquake

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hazard: complications

• secondary hazards not modelled - landslip, fire following earthquake

• other non-modelled loss contributors - economic loss, vulnerability factors

• impact of climate change will vary geographically and over time

• existing hazards change, new hazards emerge

• impact on frequency and severity unclear

• data too limited:

• current trends vs natural variability

• local uncertainty - confused by feedback systems

• downscaling and regional modelling not ready

• climate change - just another source of uncertainty?

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vulnerability: other components of insurance loss

• mean damage ratios

• engineering - design and construction components

• calibrated by loss and claims experience

• non-linear factors

• economic demand surge

• claims inflation - fraud, propensity to claim

• business interruption

• loss adjusters expenses

• claims management strategy

• approved suppliers, approved repairers

• regional restrictions

• saturation point unclear

• poor repair quality vs retro-fitting

• natural increase in vulnerability and inter-dependence of systems

• political interference

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insurance: risk management and climate change

• growing connection between insurance and academia

• contextual information vs “plug-in” data

• the flat earth has returned - data and modelling required for everywhere

• solvency and regulation - risk-based capital

• underwriting, reserving, credit, operational, liquidity, investment

• insurance as economic not social function

• reduction in insurance relief relative to economic losses

• risk appetite to meet return-on-capital targets

• interface between insurance and public policy

• non-stationarity means limited insurance adaptation is possible

• insurance cannot provide cover for the predictable