Extreme events and re insurance
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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


Richard J. Murnane

RPI/BIOS, 16 Jjune 2011

Researcher Colloquium onExtreme Weather Phenomena under Climate Change

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

Extreme events and re insurance

Washington Post, June 15, 2011



  • 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

Generic risk model

Generic Risk Model

Existing risk models

Existing Risk Models

  • Public models (not open source!)

    • HAZUS-MH

    • Florida Public Hurricane Model

  • Proprietary models


    • “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








Percent Change


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






Great recession?






Guy Carpenter, 2011



  • Introductory comments

  • (Re)insurer’s view of science

  • Climate change relative to business change

Changes in hurricane power

Sea Surface Temperature

Power Dissipation Index


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



  • 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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