Climate Change & the Bottom Line conference- Keynote, Alex Kaplan, Swiss Re
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Transcript of Climate Change & the Bottom Line conference- Keynote, Alex Kaplan, Swiss Re
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Public-Private Partnerships inRisk ManagementAddressing the Costs of Climate Change
Alex Kaplan
October 31, 2013
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Massive gap between total and insuredlosses shows insurance potential
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Source: Swiss Re Economic Research & Consulting, sigma catastrophe database
Natural and man-made catastrophe losses 1980-2012, in USD billion (2012 prices)
0
50
100
150
200
250
300
350
400
1980 1985 1990 1995 2000 2005 2010
Insured losses Uninsured losses
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Insured catastrophe losses, 1970–2012
0
20
40
60
80
100
120
1970 1975 1980 1985 1990 1995 2000 2005 2010
Earthquakes/tsunamis Man-made disasters Weather-related natural catastrophes
1992:
1994:Northridge
EQ
1999:Winter storm
Lothar
2001:Attack on
WTC
2004:Hurricanes Ivan,Charley, Frances
2005:Hurricanes Katrina, Rita, Wilma
2008:HurricanesIke, Gustav
USD bn, at 2012 prices
2011:Japan , NZ EQs
2012:Hurricane
Sandy
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Growth of values is the main driver ofincreasing natural catastrophe losses
Increasing values
Concentration in exposedareas
Increasing vulnerability
Growing insurancepenetration
Changing hazard (climatevariability, climate change)
Shanghai 1990 - 2010
Loss history is not a good guide for risk, models are an indispensable tool
Source: weburbanist.com
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Total insured value of property along the Atlantic and Gulf coast was$10.6 trillion, with New York and Florida topping the list at $2.9 trillionapiece.
Sea level rise is accelerating, especially along the U.S. East Coast and Gulfof Mexico.
Natural catastrophes (earthquake and weather related) cause averageeconomic losses of $60-100 billion annually. (Hurricane Sandy = ~$70billion)
The US Government spent $96b in 2012 to pay for climate-related events(Source: NRDC).
– If this so-called "Climate Disruption Budget" were included in the actual budget,it would be the largest non-defense discretionary budget item.
– The Government paid more for climate-related losses than it did fortransportation or education.
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The US has a high level of exposure toclimate change
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Closing the Gap: Including ex-anteinstruments into the overall risk financingstrategy
Including ex-ante instruments in the overall risk financing mix helps a governmentto lower its financial exposure to catastrophic risks, natural and man-made.
Smaller gapbetweeneconomic andinsured losses
Reduced financialburden for thegovernment afteran event
Less volatility forthe state budgetand more planningcertainty
Debtfinancing
Tax increases
Donorassistance
Budgetreallocation
Others
Ex-post financing
Reserve funds,parametric
reinsurance,catastrophe bonds
(Re-)insurancepolicies
PrivateCitizens /
Individuals
Corporations /CommercialEnterprises
Government’sexposure
(state budget)
(Re-)insurancepolicies
Ex-ante risk financing
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Systematic risk managementapproach for natural disasters
Identification AssessmentPrevention
andMitigation
Adaptation
Likelihood
Severity(in USD)
Pandemic
Coastal flooding
Earthquake
Drought
Typhoon
Tsunami
below1%
1-5% 5-10% 10-20%above20%
<1
00
mill
ion
0.1
-1.0
billi
on1
-3bi
llion
3-1
0bi
llion
>1
0bi
llion
Prevention and mitigation strategies must bethe first priority in order to reduce the extent ofany economic loss
However, public natural disaster managementincludes also the financial preparedness for theresidual risk
Hence the deployment of public funds shouldbe well balanced between prevention/mitigation and adaptation measures
Adaptation measures include ex-ante disasterfinancing instruments, such as reserve fundsand a variety of risk transfer instruments
illustrative
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Economics ofClimate Adaptation
88
Please find the full study at www.swissre.com/climatechange
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Climate-resilient development needs toaddress total climate risk
Adaptation measures are available to make societies more resilient to theimpacts of climate change and should be an urgent priority for thecustodians of national and local economies, such as finance ministers andmayors.
Decision makers need the facts to identify the most cost effectiveinvestments.
The Economics of Climate Adaptation (ECA) methodology provides decision-makers with a fact base to answer these questions in a systematic way.
It allows decision-makers to integrate adaptation with economicdevelopment and sustainable growth.
The insurance industry is an important partner in future adaptation plansbecause of its experience in risk management and modeling, and indeveloping new insurance products.
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We've conducted climate adaptationstudies in 17 regions of the world
Samoa
Florida
MaliMali
IndiaMaharashtra
U.K. / HullChina
North, Northeast
Samoa
GuyanaGuyana
TanzaniaTanzaniaAnguilla, Bermuda,Barbados , Jamaica,Antigua and Barbuda,St. Lucia, Dominica
US Gulf coast
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Case study methodology
Set of adaptationmeasures
– Identify potentialadaptationmeasures
– Determine societalcosts and benefitsand basic feasibility
– Interviews withexperts
– Economicanalysis
Implementationassessment
– Assess currentprogress againstthe measures
– Understandrequirements toimplementation
– Determine actionsrequired toimplementmeasures
Where andfrom what is
the Statemost at
risk?
What is themagnitude ofthe expected
loss?
What is themagnitude ofthe expected
loss?
Whatmeasuresshould be
considered?
Whatmeasuresshould be
considered?
How canmeasures be
impleme-nted?
How canmeasures be
impleme-nted?
Input intoadaptation
strategy
Input intoadaptation
strategy
Estimate ofpotential loss
– Hazard: Developfrequency andseverity scenarios
– Value: Quantifyassets and incomevalue in area at risk
– Vulnerability:Determinevulnerability ofassets and incomesto the hazard
Map of areasat risk
– Identify mostrelevant hazard(s)in case location
– Identify areas thatare most at-risk, byoverlayinghazard(s) on:
– Population
– Economic value(GDP)
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Sea level rise and altered hurricane frequenciessignificantly increase losses in New York City
Source: www.nyc.gov: A Stronger More Resilient New York
Expected annual lossesfrom storm surge and wind(billion USD)
+ 88%
+ 70% + 168%
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Quantifying expected losses at zip codelevel (annual expected loss)
Source: www.nyc.gov: A Stronger More Resilient New York
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Loss frequency curves(the frequency of a loss equaling orexceeding a specific value)
Source: www.nyc.gov: A Stronger More Resilient New York
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Residential/commercial
1 Improved building codes
Oil and gas
6 Floating productionsystems
7 Replacing semi-subs withdrill ships
8 Levees for refineries andpetrochemical plants
Infrastructure/Environmental 3 Wetlands restoration3
2 Beach nourishment
4 Levee systems3
Electric utility 9 Improving resilience ofelectric utility systems
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4
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4
2
2
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Benefit (lossaverted)2
$ Billions
• There will be a strongneed for leadership inthe gulf coast, in orderfor these actions tooccur
• There may be need forbroad policy support toincentivize private capitalinvestment, e.g.,by subsidizing homes inlow-income areasbuilt to higher buildingcodes
Identifying the most cost effective resiliencebuilding options
1 Total capital and operational costs, discounted, across 20years2 Total loss averted, discounted, across 20 years3 Included despite high C/B ratios due to strong co-benefits,risk aversion
5 Improved standards foroffshore platforms
Total
AverageC/B ratio
x
0.7
1.3
1.6
0.7
0.5
3.3
0.7
3.8
1.0
Cost1$ Billions
64
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1
6
15
5
6
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Gulf Coast case
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1.1
0.8
6.0
1.60.4
2.6
1.8
1.44.7
7.1
5.9 3.1
4.2
6.1
2.1
0.0 1.1
0
2
4
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annual expectedlosses as %of local GDP
total expected loss todayresidual loss 2030cost-effectively avertible loss 2030
Significant economic value is at risk –40-65% of losses can be averted cost-effectively
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high GDP country low GDP country
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Insurance is suited for low frequency,high severity events
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Case study India
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The Solutions
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Case study United States:Alabama – First parametric cover for agovernment in an industrialized country
Solution features Insured peril: Hurricane Payments to offset economic costs of hurricanes Trigger type: Disaster occurring within a defined geographic
area ("box") along coast (“cat-in-the-box”)
– Trigger based on wind speed of hurricane eye as itpasses through pre-determined box
– Payout in as little as two weeks Time horizon: July 2010 – July 2013 First parametric catastrophe risk transfer for a government in
an industrialized country
Involved parties Insured: State Insurance Fund of Alabama Swiss Re: Lead structurer and sole underwriter
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Case study Mexico:MultiCat - Funding for immediaterelief efforts after disasters
Solution features Insured perils: Earthquake and hurricane Payments to be used for immediate emergency relief after a
disaster Parametric catastrophe bond: USD 315 million Trigger type: Index
– Earthquake: physical trigger (quake magnitude)– Hurricane: physical trigger (barometric pressure)
Time horizon: October 2012 – November 2015 Renewed cat bond launched through the World Bank’s
MultiCat facility and third cat bond for Mexico
Involved parties Insured: Fund for Natural Disasters (FONDEN) of Mexico Reinsured: AGROASEMEX S.A. Arranger: World Bank Treasury Swiss Re: Co-lead manager and joint bookrunner
Swiss Re Global Partnerships | January 2013
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Case study Caribbean:Caribbean Catastrophe RiskInsurance Facility (CCRIF)
Solution features The CCRIF offers parametric hurricane and earthquake insurance
policies to 16 CARICOM governments The policies provide immediate liquidity to participating
governments when affected by events with a probability of 1 in 15years or over
Member governments choose how much coverage they need upto an aggregate limit of USD 100 million
The mechanism will be triggered by the intensity of the event(modelled loss triggers)
The facility responded to events and made payments:– Dominica & St. Lucia after earthquake (2007)– Turks & Caicos after Hurricane Ike (2008)– Haiti , Barbados, St. Lucia, Anguilla and St. Vincent (2010)
Involved parties Reinsurers: Swiss Re and other overseas reinsurers Reinsurance program placed by Guy Carpenter Derivative placed by World Bank Treasury
Swiss Re Global Partnerships | January 2013
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Case study Haiti:The Microinsurance CatastropheRisk Organization (MiCRO)
Solution features Insured perils: Hurricane, earthquake and rainfall Payments are made to microfinance borrowers post-disaster to reduce their
loans and provide emergency cash Parametric and basis risk policies are distributed through a local Haitian
microfinance institution, Fonkoze Trigger: Index measured at Fonkoze branches in Haiti Basis risk absorbed by new donor funded company, MiCRO Inception: March 2011
Involved parties Insured: Fonkoze Sole Reinsurer: Swiss Re Other partners: MercyCorps, CaribRM, Guy Carpenter
Background information Haiti is a nation that is susceptible to catastrophes and is unprepared for the
costs of response Prior to the setup of MiCRO, Fonkoze's clients bore 100% of natural disaster
risk MiCRO was named “Company Launch of the Year” at The Review magazine’s
annual Worldwide Reinsurance Awards in September 2011.
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Solution features Insured peril: Wildfire Payment to offset wildfire suppression costs of the
Government of the Province of Alberta The insurance cover allows for budget planning certainty Semi-parametric solution: The loss is calculated by
multiplying the area burnt in hectares with CAD 300 perhectare
The Government of Alberta provides Swiss Re with monthlyreports of the suppression costs, number of wildfires, andarea burnt
Annual cover of CAD 100m above CAD 100m retention Inception: 2008
Case study Canada:Wildfire suppression cost insurance
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Founding sponsor of Climate WeekNYC
Mind the Risk report
– Calculated affected population and losteconomic productivity for 616metropolitan areas globally.
100 Resilient Cities Challenge
– Support at least 100 cities in the nextthree years to appoint Chief ResilienceOfficers (CRO), create resiliencestrategies, and establish a CRO supportnetwork to share information and bestpractices.
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Knowledge SharingIncreasing Climate Resiliency
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Contact Information
Alex Kaplan
Public SectorSenior Client Manager
Swiss Re America Holding Corp.101 Constitution Ave. NW, Suite 700
Washington, DC 20001USA
Tel +1 (202) 742-4623Fax +1 (202)742-4630
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Thank you
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Legal notice
©2013 Swiss Re. All rights reserved. You are not permitted to create anymodifications or derivatives of this presentation or to use it for commercialor other public purposes without the prior written permission of Swiss Re.
Although all the information used was taken from reliable sources, Swiss Redoes not accept any responsibility for the accuracy or comprehensiveness ofthe details given. All liability for the accuracy and completeness thereof orfor any damage resulting from the use of the information contained in thispresentation is expressly excluded. Under no circumstances shall Swiss Reor its Group companies be liable for any financial and/or consequential lossrelating to this presentation.
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