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Science into Policy Options for Risk Mitigation in Developing Countries. What Works and Does Not Work in the Science and Social Science of Earthquake Vulnerability Oxford Meeting 28 & 29 January 2011. Andrew Coburn Senior Vice President, Risk Management Solutions.

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science into policy options for risk mitigation in developing countries

Science into PolicyOptions for Risk Mitigation in Developing Countries

What Works and Does Not Work in the Science and Social Science of Earthquake Vulnerability

Oxford Meeting 28 & 29 January 2011

Andrew Coburn

Senior Vice President, Risk Management Solutions

who pays and how is it spread
Who Pays and How is it Spread?

Financial Industry

Exchequer

Tax payers

Sovereign Wealth Funds

Public Sector

Government

Central & Local

Capital Markets

Global

Reinsurance

Industry

Private Finance

Corporate Property Insurance

Business Interruption Insurance

Group Injury Insurance

Private Sector

Corporate Industry

Companies and corporations

Insurance

Industry

Personal Savings

Homeowner insurance

Micro Insurance

Individuals

Families

After a bad earthquake somewhere in the world your car insurance premium goes up

the development trap
The Development Trap
  • Emergent economies invest in infrastructure (roads and utilities) and property assets (factories and cities) which are then at risk of destruction from a natural disaster
  • Emerging economies generally invest in lower cost assets than those in industrialized countries, so are less robust and more vulnerable to damage
  • Investing in robustness for disaster resilience is more difficult to justify when boot-strapping economic growth with capital at a premium
  • This is both the constraints and the opportunity for private market stakeholders in catastrophe risk:
    • Insurance contributes to economic resilience by providing additional capital
    • Insurers also can provide know-how to improve the resilience of the property assets that need protecting
the emerging insurance markets
The Emerging Insurance Markets

Swiss Re, Sigma ,2006

Example countries in the Emerging Markets:

PR China

India

Brazil

Russia

Chile

Pakistan

Mexico

Costa Rica

Colombia

Turkey

Romania

Philippines

Iran

Serbia & Montenegro

Guatemala

Indonesia

an example addressing the new deadly vernacular
An Example: Addressing the New Deadly Vernacular

The 20thCentury Earthquake Killer

The 21st Century Earthquake Killer

Old, vulnerable masonry buildings

Poorly-built RC MRF structures

80+% of EQ deaths in 20thC

20-40?% of EQ deaths in 21st C

Collapse at MMI IX: 10-60%

Collapse at MMI IX: 2-25%

Low Ave Occupancy: 2-10 people

High Ave Occupancy: 5-100s of people

Construction cost: X

Construction cost: 10-100X

missing ingredient skill
Missing Ingredient: Skill
  • Built by local building contractors to standard templates with very little professional engineering design or supervision
  • Design and construction quality is not policed in any meaningful way: municipal control systems are minimal
  • ‘Codes’ are meaningless
  • Vulnerable faults include
    • Poor structural form, soft storey
    • Undersized structural members
    • Reinforcement detailing
    • Concrete quality, etc.
  • Appreciation of value of QA roles – clerk of works, inspector
  • Education & professional proficiency

Putting together programmes to address these requires costly investment decisions and complex administrative systems

metrics of mitigation the disasters that haven t happened
Metrics of Mitigation: The disasters that haven’t happened

“Building a culture of prevention is not easy. While the costs of prevention have to be paid in the present, its benefits lie in a distant future. Moreover, the benefits are not tangible; they are the disasters that did not happen…”

Kofi Annan, Secretary General of the United Nations, 1999

Mitigation benefits could become more visible through scientific concepts of risk

Risk is a complex and largely invisible concept

Risk metrics have become common tools for supporting decisions in the financial services industry that trades risk

economic resilience against disaster
Economic Resilience Against Disaster
  • Economic growth is the most important factor in disaster mitigation, providing society with the resources to protect itself and build a stronger and more resilient environment
  • Improving the reach and scale of societal wealth creation is an important objective for those of us who want to increase the effectiveness of mitigation
  • Financial support to emerging economy governments
    • Government post-disaster borrowing could be better budgeted as pre-disaster saving plan (like major corporate risk management)
    • Sovereign wealth access to international pools and risk swaps
    • Catastrophe bonds in capital markets
  • Government support to emerging insurance markets
    • Encouragement of citizens to protect themselves
    • Micro-insurance and micro-finance for lowest income and most vulnerable
    • Government endorsement, plus strict regulation, to increase trust
    • Follow policies of empowering individuals to protect themselves rather than promoting dependency culture
risk assessment frameworks are fundamental to mitigation activities
Risk Assessment Frameworks Are Fundamental to Mitigation Activities

They are key to the ‘business case’ for investment in mitigation

They facilitate a rational benchmark for public safety standards

They underpin the economics of financial engineering for funding recovery and spreading the risk

financial economics risk framework
Financial Economics: Risk Framework

Uncertainty

Occurrence Parameterization – location, frequency, magnitude and source characteristics of future events

Spatial Impact Estimation – Geography of ground motion, attenuation, frequency and

Vulnerability Assessment – likely levels of damage to different types of buildings resulting from ground motion

Inventory Audits – number and types of physical infrastructure and buildings, where they are, type and quality

Damage Costing – repair and reconstruction costs, loss productivity, variation in future supply and demand, economics and social impact

Financial Engineering – admin costs, risk loadings for uncertainty, premium pricing, net present valuation

High

Med

High

Med

Low

Med

Assessing the Frequency and Severity of Loss:

uncertainty where science can add most to policy
Uncertainty – Where Science Can Add Most to Policy
  • We don’t need to know everything to structure good mitigation decisions
  • Financial engineering adds loadings for uncertainty
  • We need to
    • Assess what we really know
    • Give a rigorous and honest assessment of what we don’t know
  • Science should help us assess:
    • How incomplete might historical catalogues be?
    • Uncertainty levels around location of faults
    • Uncertainties around assessments of activity rates
    • Uncertainties around loss modeling assumptions
    • Identify other areas of greatest uncertainty in risk frameworks
conclusions
Conclusions

Risk assessment frameworks facilitate the transfer of scientific knowledge to effective mitigation actions

There are major areas of uncertainty that reduce the willingness and ability of participants in mitigation

Science should address the greatest areas of uncertainty

Once of the greatest areas of uncertainty is assessing the level of uncertainty

Help us know what we don’t know…