Transcript Climate change

Climate Change
Quantification of business impacts
by means of catastrophe modeling
leading to tailormade risk transfer
solutions
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Or: Nat Cat Reinsurance – how it works and what it needs
(Nat Cat) Risk Management
generic

Identification/Awareness
– perception is based on a shared mental model that can
be conceptualized

Quantification
– From conceptual to quantitative model

Mitigation
– Explore/quantify options through quantification

– costing of options: need for integrated models: loss
costs (expected loss), cost of capital (or ‘for capacity’)
specific
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Transfer
– portfolio management  diversification

Market: price the option and trade etc.
Reality and Model
Reality
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
To be more precise: Perceived reality
Reality and Model
Reality
Model
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Reality and Model: Proportions
Reality
Model
Economy
Society
Legal Framework
Environment
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Reality and Model: What can be described
Reality
Model
Unrealistic?
Modeled
Not modeled
Reality  Model: Abstraction
Described in Model
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Model  Reality : Interpretation (Verification/Falsification/Calibration)
Reality and Model: Development
Reality
Model
conceptional
Unrealistic?
incremental
Modeled
Not modeled
Reality  Model: Abstraction
Described in Model
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Model  Reality : Interpretation
Reality and Model: Development
Reality
Model
conceptional
Unrealistic?
incremental
Modeled
Not modeled
Reality  Model: Abstraction
Described in Model
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Model  Reality : Interpretation
Be reminded: Perceived reality
Nat Cat loss model
4 elements
Hazard
Vulnerability
How strong?
How frequent?
How well built and
protected?
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Value distribution
Cover conditions
What exactly is covered ...
where...
and how?
-
Sums insured
-
Cover limits
-
Deductibles
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Exclusions
-
etc.
Example: Detailed Single Event Simulation
Literally hundred thousands of such simulations are run in e.g. the catXos Nat Cat model to assess a portfolio
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
TC North Atlantic – probabilistic (zoom)
North Atlantic
tropical cyclone
event set
historic
~1000 events
~100 years
probabilistic
~100‘000 events
~10‘000 years
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
The largest loss potentials
110
Peak risks:
 Earthquake or storm
 In industrialised
countries
 With high insurance
density
Hurricane
US+Carib.
(100y)
Quake
California
50
75
35
45
19
Northridge
1994
Quake
Japan
Storm
Europe
7.2
FHCF
2007
Typhoon
Japan 20
8.4
Daria
1990
Mireille
1991
Katrina
2005
Insurance loss potentials in USD billions:
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Nat cat events (indexed to 2006, source: sigma 2007)
Loss potentials from events with a return period of 200
years (100 years for Hurricane North Atlantic)
FHCF: Florida Hurricane Catastrophe Fund
JER: Japan Earthquake Reinsurance Scheme
state-run
schemes
JER
How will climate change impact
the re/insurance industry?
Possible change in mean AND variance
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
summer
heatwave
The next 100 years:
Increasing variability
Model results
What has been exceptional in 2003 might become usual by 2070
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Source: Schär et al., Nature 2004
summer
heatwave
The next 100 years:
Increasing variability
Model results
What has been exceptional in 2003 might become usual by 2070
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Source: Schär et al., Nature 2004
The effects of climate change:
Storm damage in Europe on the rise
Climate change is affecting winter storms in Europe. Based on the findings
of a scientific study, Swiss Re forecasts a significant rise in damage from
storm events in the long term, creating additional risk for society and
insurers to manage
CORNELIA SCHWIERZ1, PAMELA HECK2, EVELYN ZENKLUSEN1, DAVID N.
BRESCH2, CHRISTOPH SCHÄR1, PIER-LUIGI VIDALE1 and MARTIN WILD1
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
1) Institute for Atmospheric and Climate Science, ETH Zürich, Schweiz
2) Swiss Reinsurance Company, Zürich, Schweiz
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
Future, A2
Current, Control
IPCC Scenarios
Source: IPCC 2007, Summary for Policy Makers
European Winter Storms
Goal and Methodology
Compare wind storm losses on a Europe-wide property insurance portfolio in
current and future climate conditions:
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Use 3-dimensional global climate models (Int. community, ETH)
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Drive regional climate models over Europe with initial and boundary conditions from
global models (ETH)
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Couple windfields (climate model output) with Swiss Re’s state-of-the-art loss model
(probabilistic storm hazard set for current and future climate conditions)
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
European Winter Storms
Climate Change Impact
Increase in annual expected loss for the period 2071–2100
compared to a 1961–1990 reference period:
Climate
model 1
Swiss Re
loss model
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
68%
Climate
model 2
48%
Climate
model 3
16%
Climate models show an increase in both storm severity
and frequency.
Source: Schwierz et al, Modelling European winter windstorm losses
in current and future climate, submitted to climatic change
Climate Impact Studies
On-going Joint Projects
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Winterstorm Europe
– MeteoSwiss, Zürich (NCCR climate), see P. Della Marta
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Tropical Cyclones North Atlantic
– University of Bern, (NCCR climate)
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Flood Europe
– EC Joint Research Center, Ispra, Italy
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Drought and Subsidence Europe
– ETH, Zürich (NCCR climate)
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Sea Level Rise, Coastal Risks
– University of Bern, GKSS Hamburg
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]

Tropical Cyclones West Pacific
– City University of Hong Kong (more general study, done)
Conclusions

Past and Present Climate
– solid base period  longer re-analysis period, better representation
of extremes (‘tail events’)
– comprehensive probabilistic set (multimodel) ensemble based reanalysis
– variables to best represent the cause of loss  gust better than
mean wind, flood water level better than run-off ( e.g. coupled
hydrological and hydraulic models)
– reasonable resolution to capture local risk and consistent spatial
signals  footprint (dependency)

Future climate
– Avoid surprises, abrupt change (prevention, mitigation, adaptation)
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
– Near future (decade) of more immediate concern (from time-slice to
continuum)
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Ceterum censeo: Easy data access (at adequate costs, simple legal terms)
Further reading
www.swissre.com
Research &
Publications 
Swiss Re
publishing
Dr. David N. Bresch
Swiss Re
23 June 2008
[email protected]
[email protected]