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Challenges in Environmental Risk Management

Insurance

Dr Michael Maran

Chief Science Officer

Catlin Group Limited

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outline

• The emerging environmental challenges in the insurance sector:

• the needs of the insurance industry

• where there are gaps

• new services or products that might help to address these needs

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back to basics

Fair PriceTerms &

Conditions

Duty to Policyholders

Duty to Shareholders

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the needs of the insurance industry

Fair PriceTerms &

Conditions

Duty to Policyholders

“Fair Price” Equitable Price reflects Risk

Risk = f (Hazard, Exposure, Vulnerability)

Hazard = f (Frequency, Severity, [duration etc])

Duty to Shareholders

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Frequency / Severity

low

sev

erity

high

high frequency low

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precision v accuracy

Increased Precision Increased Accuracy

True value

True value

True value

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the gaps

• data

• understanding the uncertainties

• timescales

• rare extreme events

• event dependency and correlation

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data

• relevant

• accurate

• verifiable

• usable

• volume

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understand the uncertainties

know the rules

be wary of unknown factors

use but do not rely on the past

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timescales

Days

Weeks

Months

Years

Decades

Loss Mitigation

Policy Formulation

Business Planning

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rare extreme events

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Event dependency and correlation

• Insured events are generally considered as independent events

• In most cases this is probably true – or is it?

• Do we recognise when they are not independent?

• How do we identify and measure dependency?– Earthquakes: When do quakes stop being defined as aftershocks?– What about weather?

• How do we view independent but correlated events?– e.g. US Hurricanes and Australia drought

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Threat correlation

http://risk.jbs.cam.ac.uk/

University of CambridgeJudge Business SchoolCentre for Risk Studies

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new products and services

• How good is the data?– Is it raw / cleaned ; accurate ; verified ; up to date?

• Can we still use historical data?– Assessing the validity of historical data in a changing world

• Do we understand the uncertainties?– Are we getting / giving the full picture?

• How should we deal with dependant and correlated events?

• How good are the models?– Are we trying to be too clever?– Is there a better way?

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Are models always right or always wrong?

Model of an elephant This is not an elephant

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Feature Actual Model

Shape Curves Symmetry

Curves Symmetry

Texture Basically smoothWrinkly

Basically smoothWrinkly

Size ~ 6m ~ 0.1m

( Electron : Universe ~ 10 -15m – 1027m )

Mass ~ 5,500 kg ~ 15g

( Electron : Universe ~ 10 -30g – 1055g )

Colour Grey White

( not R O Y G B I V )

Composition C ; H ; O > 90% mass

> 50% Water

e.g. PLA (C3H4O2)n

Can contain water

An elephant

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Models are not wrong

• But are they the best answer?

• An incomplete set of equations

• Using uncertain parameters

• We need another way

• There is another way

• The challenge is to find it

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Q & A