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EXTREME EVENTS AND (RE)INSURANCE. Richard J. Murnane RPI/ BIOS, 16 Jjune 2011 Researcher Colloquium on Extreme Weather Phenomena under Climate Change. (Hurricane Fabian over Bermuda. Sept. 5, 2003). Washington Post, June 15, 2011. Overview. Introductory comments

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Extreme events and re insurance

EXTREME EVENTSAND(RE)INSURANCE

Richard J. Murnane

RPI/BIOS, 16 Jjune 2011

Researcher Colloquium onExtreme Weather Phenomena under Climate Change

(Hurricane Fabian over Bermuda. Sept. 5, 2003)



Overview
Overview

  • Introductory comments

  • (Re)insurer’s view of science

  • Climate change relative to business change


Why am i here
Why Am I Here?

  • Senior research scientist at BIOS and program manager for the Risk Prediction Initiative, a science-business partnership at BIOS

  • Chief scientist with OpenRisk LLC, a catastrophe risk business platform


What is risk
What Is Risk?

  • Risk = f(climate, exposure, vulnerability)


Top 40 for victims 1970 2010
Top 40 For Victims (1970-2010)

Swiss Re Sigma, 1/2011


Top 40 for victims 1970 20101
Top 40 For Victims (1970-2010)

Swiss Re Sigma, 1/2011


What is risk1
What Is Risk?

  • Risk = f(climate, exposure, vulnerability)

  • Focus on risk of losing $$$

  • Probability of loss:

    • Annual Average Loss (AAL)

    • Return period loss, e.g., 100 year event

  • Variance around the probability of loss

    • Correlation of occurrence and intensity

    • Clustering


2008 non life premium volume
2008 Non-life Premium Volume

US and Europe premium: ~$1.4 trillionGlobal ~$1.8 trillion

Swiss Re, Sigma 3/2009


Top 40 property cat losses 1970 2010
Top 40 Property Cat Losses 1970-2010

In 2010 dollars:

Total ~$350 billion2010 losses ~$43billion

Swiss Re Sigma, 1/2011


How do re insurers
How Do (Re)Insurers:

  • Assess their risk?

    • Using catastrophe risk models that provide the “technical” price



Existing risk models
Existing Risk Models

  • Public models (not open source!)

    • HAZUS-MH

    • Florida Public Hurricane Model

  • Proprietary models

    • AIR, ARA, EQECAT, RMS

    • “In-house”models


How do re insurers1
How Do (Re)Insurers:

  • Assess their risk?

    • Using catastrophe risk models that provide the “technical” price

  • Price their (re)insurance?

    • Model results, in part, but also market price, investment expectations, business considerations, …


Underwriting vs investment returns
Underwriting Vs. Investment Returns

Aggregate of US, Canada, France, Germany, UK, and Japan

15

10

5

0

-5

-10

-15

Percent Change

1998 1999 2000 2001 2002 2003 2004*

Underwriting result

Current investment income

Operating result

Capital gain/loss

Other income/charges

Swiss Re, Sigma 2/2005


Guy carpenter s global property rate on line index
Guy Carpenter’s Global Property Rate On Line Index

400

300

200

100

0

Great recession?

Andrew

Katrina

9/11

1990 1995 2000 2005 2010

Year

Guy Carpenter, 2011


Overview1
Overview

  • Introductory comments

  • (Re)insurer’s view of science

  • Climate change relative to business change


Changes in hurricane power

Sea Surface Temperature

Power Dissipation Index

Year

Changes In Hurricane Power?

“… future warming may lead to an upward trend in tropical cyclone destructive potential, and – taking into account an increasing coastal population – a substantial increase in hurricane-related losses in the twenty-first century.”

K. Emanuel, Nature, 2005.


Or no change
Or, No Change?

“Subjective measurements and variable procedures make existing tropical cyclone databases insufficiently reliable to detect trends in the frequency of extreme cyclones.”

Landsea et al., Science, 2006.


Future unfavorable conditions
Future Unfavorable Conditions?

“… the increase of [vertical wind shear] has been historically associated with diminished hurricane activity and intensity. A suite of state-of-the-art global climate model[s] project… [s]ubstantial increases in tropical Atlantic and East Pacific shear …”

Vecchi and Soden, GRL, 2007.


Upward trend in strongest storms
Upward Trend In Strongest Storms?

“We find significant upward trends for wind speed quantiles above the 70th percentile…”

Elsner et al., Nature, 2008


State of knowledge
State Of Knowledge

IPCC, 2007

CCSP, 2008


Overview2
Overview

  • Introductory comments

  • (Re)insurer’s view of science

  • Climate change relative to business change


Potential impacts
Potential Impacts

  • All other things being equal, losses will increase with:

    • Sea level rise

    • More frequent events

    • More intense events

    • Wetter events (i.e., more floods)

    • Etc…..

  • But, to what extent, and over what time scale, can we say with certainty that these changes will occur?


Real world impacts
“Real World” Impacts

  • Regulatory and ratings agencies

  • New cat models


Amo and hurricane landfalls
AMO And Hurricane Landfalls

Goldenberg et al., 2001


Florida hurricane commission on loss projection methodology
Florida Hurricane Commission On Loss Projection Methodology

  • FHCLPM created during the 1995 Legislative Session

  • Models used for rate filing in the state must be certified by FHCLPM

  • To date only models based on climatology approved

  • Models not approved by commission used for reinsurance transactions


New models
New Models

  • New RMS hurricane model

    • Updated construction and roof types

    • Higher inland wind speeds

    • Heightened building vulnerability

    • Increased losses due to storm surge

  • Change in losses

    • Increased insured loss results range from 20 to 100 percent

    • Some loss estimates in Texas have doubled, losses for Middle Atlantic states also increased significantly

    • Smaller increases in Florida


Market response
Market Response

  • Ratings:

    • S&Pissued a negative watch on 17 cat bonds due to the revised model

    • A.M. Best expects companies to incorporate model revisions as soon as practical.

    • Those companies that have started to use the new version apparently are quick to move as they see little or no impact on their rating or capital requirements


Closing comments
Closing Comments

  • (Re)insurers time horizon is very short: quarters and years, not decades and centuries

  • To my knowledge:

    • Clustering not incorporated in models

    • Correlation in frequency and intensity not incorporated in models

  • Under-appreciated problem is how to combine, in an optimal manner, results from multiple model


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