Overview Insurance and Risk Assessment for Extreme Weather Events Joanne Linnerooth-Bayer IIASA M.J....
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![Page 1: Overview Insurance and Risk Assessment for Extreme Weather Events Joanne Linnerooth-Bayer IIASA M.J. Mace Field Roda Verheyen University of Hamburg.](https://reader036.fdocuments.net/reader036/viewer/2022070306/55168547550346a25b8b4a76/html5/thumbnails/1.jpg)
Overview Insurance and Risk Assessment
for Extreme Weather Events
Joanne Linnerooth-BayerIIASA
M.J. MaceField
Roda VerheyenUniversity of Hamburg
![Page 2: Overview Insurance and Risk Assessment for Extreme Weather Events Joanne Linnerooth-Bayer IIASA M.J. Mace Field Roda Verheyen University of Hamburg.](https://reader036.fdocuments.net/reader036/viewer/2022070306/55168547550346a25b8b4a76/html5/thumbnails/2.jpg)
Insurance-Related Actions and Risk Assessment in the Context of the UN FCCC
• Background• The challenge• Risk analysis for insuring extreme weather events
• Risk transfer, collective loss sharing and public-private partnerships
• International legal responses to risk and approaches to insurance
• Opportunities, challenges and possible partners
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Overview• Weather-extreme losses are worsening, evidence
linking to climate change;
• Methodologies exist for assessing risks, extreme events becoming more insurable;
• Large uncertainties, however, contribute to high premiums of private catastrophe insurance;
• Many types of insurance-related instruments and systems, differential cost and incidence;
• Important precedents exist for building national and international burden-sharing regimes.
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Negotiating Background
Article 4.8 of the UNFCCC calls upon Parties to consider actions, including those related to insurance, to meet the specific needs and concerns of developing countries with respect to both the adverse impacts of climate change and the adverse impacts of response measures.
Article 3.14 of Kyoto Protocol calls for implementation and explicitly for consideration of the establishment of insurance.
These Articles had their genesis in a proposal by AOSIS on an international insurance fund to address damage from sea level rise.
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Context and Challenge
• The context: Sudden onset extreme weather events
• The challenge: To develop a framework for the implementation of insurance-related activities for developing countries facing extreme weather events
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Disaster losses on the rise
109
25127
71128
199
607
0
100
200
300
400
500
600
1960s 1970s 1980s 1990s
Loss
es in
U
SD
bill
ions
0
10
2030
40
50
60
7080
90
100
Num
ber
of e
vent
s
Insured Losses Economic Losses Number of events
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Loss increase
• Mainly from changes in land-use and increasing concentration of people and capital in vulnerable areas;
• IPCC has concluded that at least part of this loss is due to changes in climatic conditions
• IPCC predicts increasing frequency and intensity of extreme weather events.– Higher maximum temperatures– More intense precipitation– Increased wind intensities
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Poor countries hit hardest
Per capita cost of disasters in relation to GDP is at least 20 times higher in the developing countries.
Ninety-five percent of the deaths from recent natural disasters have occurred in poor countries.
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Burden sharing
VICTIMS
Households Businesses Agriculture Private
Marketinsurance
Donor AidInternational
FinancialInstitutions
GovernmentRelief and reconstruction Public Sector
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0%
5%
10%
15%
20%
25%
30%
Percentage of insurance coverage
> $9,361 $3,031-$9,360 $761-$3,030 < $760
Per capita income
Risk transfer/insurance in low-income countries
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Insurability
• If insurers can identify and quantify the risk;
• If they are unrestricted in setting premiums.
Insurers do not insure all insurable risks– Premium may be too high– Adverse selection– Moral hazard
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Estimating the risks of extreme events
• Risk: probability x consequence
• Independent events: Law of Large Numbers
• Dependent events: Heavy tails, lack of historical data, PML concept
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Improved Risk Estimates with Catastrophe Modeling
• What is the probability of selected hazard?
• How vulnerable are structures/people to the hazard?
• What is distribution of structures/people exposed?
• What is probability distribution of losses (Monte Carlo simulation)
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Flood Catastrophe Model
HydrologicalModel
One-dimensionalUnsteady Flow
InundationModel
GIS-BasedFlood DepthFlood Duration
LossModel
AgriculturalUrbanInfrastructureHistorical Buildings
Policy Model
Set premiumsMitigation
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Incorporating climate change
• Empirical data on effects of climate change on weather-related disasters highly uncertain;
• Global circulation models cannot provide predictions on changes in regional climate (downscaling)
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Limitations
• Data intensive
• Resource intensive
• Uncertainty
Note: Not necessary to have loss frequency for insurance – physical trigger
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Insurability improving, but uncertainty remains
• Models for the most part give better estimates of risk and improve insurability
• Much uncertainty remains – high premiums
With 1 billion people living on less than $1 a day, any discussion on insurance must take into account the capacity to engage in such efforts on the part of citizens and their governments.
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Financial vulnerability
• Low: Most exposed households and businesses can afford to be part of a risk-sharing pool;
• Medium: The country as a whole can afford the pool, but regions where citizens cannot;
• High: Most exposed households and businesses cannot afford to be part of a risk-sharing pool.
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0200400600800
100012001400
Lo
ss
es
[U
SD
]
10 50 100 500
Event [year]
Government losses and financing for storm and flood risk
Government losses
Available Financing
Honduras financing gap(Mechler and Pflug, 2003)
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The dilemmaHow can insurance-related pools be accessible to poor,
very vulnerable countries – households, businesses, and governments?
• Private insurance is not only alternative;• Many types of insurance-related instruments that
spread burden differently, and even globally;• New instruments, especially for public infrastructure
insurance;• Many ways for international community to support
these systems.
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Insurance-related instruments: Risk transfer and collective loss sharing
Collective loss sharing: Non-contractual arrangement for sharing losses after a disaster. A pre-disaster instrument, e.g. fund, may be put into place. The collective can be– Taxpayers (governments) e.g, Fondem calamity
fund– The international community, e.g. AOSIS – Parties or enterprises imposing risks, eg nuclear
power liability regimeThe collective can transfer its risk though
insurance or other risk-transfer instruments, e.g. nuclear power operator insurance
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Insurance-related instruments: Risk transfer and collective loss sharing
Risk Transfer: Contractual hedging instrument generally paid for by persons, enterprises or governments at risk, e.g., insurance, cat bonds. Governments, international bodies can subsidize risk-transfer systems, e.g., World Bank support of Turkish system.
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Risk transfer instruments
• Insurance, re-insurance
• Catastrophe bonds
• Weather hedges
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Private sector risk transfer
• Too expensive for households, businesses– Micro-insurance– Weather hedges
• Yet, governments cannot continue large liabilities
• Insurers increasingly reluctant to offer cat insurance
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Turkish Catastrophe Insurance Fund
(TCIF)
World Bank
Private Reinsurance
World Bank
Government fund Mandatory Risk-based premiums
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How can insurance-related actions be used to transfer risks and share losses associated with adverse effects of climate change within the legal framework of the climate change regime?
Examine insurance-related instruments in international civil liability and compensation regimes
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Nuclear liability regime
Joint State Funds (Int’l solidarity pool)
State(taxpayers)
Operators
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Opportunities and Challenges for developing insurance framework
– Data collection and analytical capacity– Collective loss-sharing funds– Risk-transfer for governments – Public-private partnerships– Micro insurance
No regret strategy even with uncertainty of effects of climate change on extreme weather events.
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International risk sharing
• Contributions on the part of emitters, countries based on emissions, GDP?
• Role of the public?
• Time frames for initiating action, based on observed effects?
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Background
AOSIS Proposed fund for compensating victims of sea-level rise – Mandatory contributions from industrialized countries
based on GNP and emissions
– Trigger for claims: global and relative sea level rise
– Claims for retreat and accommodation measures
– COP-controlled “Authority”