© 2014 Finity Consulting Pty Limited

Catastrophe Models:

knowing what questions to

ask as a Director

Prepared by Tim Andrews | February 2014

2

Nine quotes from a Catastrophe Modelling Conference earlier this month

3

“Boards don’t understand what a return period is.”

4

1 in 475

Source: Stirling et al, 2012

ITALY

5

Exceedance probability

ARI

Return period

Tail values

Single peril single/site vs multi-peril/site

A paradox

6

How can a 1 in 400 year event occur every 50 years?

Does a diversified insurer need to allow for a more severe catastrophe than an insurer concentrated in one location?

Single state insurer – single peril

7

$300m

1 in 200

Two state insurer – single peril

8

$300m

$300m

1 in 200

1 in 200

$300m event every 100 years for the portfolio

Two state insurer – single peril

9

$500m

$500m

1 in 400

1 in 400

$500m event every 200 years for the portfolio

Multi state multi peril

10

$300m

$200m

$400m

$300m

$500m

$200m

$500m

$400m $300m

• 1 of these 1 in 400 year events every 44 years!

• $700m event every 200 years for portfolio

Single State vs Multi State

11

PML equivalent to worst

1 in 200 year event

$200m

PML equivalent to worst

1 in 200 year event for portfolio

$700m

Single State Insurer Multi State Insurer

An insurer’s modelled cats

12

Event Frequency Cost Location Description

A 0.00000042 $1,350m WA, Yilgam E/Q 7.1

B 0.00000038 $1,350m Northern New

England

E/Q 6.8

C 0.00000000 $1,348m NW Victoria E/Q 7.2

D 0.00000513 $1,346m Perth Basin E/Q 6.5

E 0.00000774 $1,342m Nth Qld Cat 5 Cyclone

F 0.00000775 $1,342m NT Cat 5 Cyclone

13

“Why aren’t the regulators here to listen to this?”

RBNZ requirements

14

Greater of:

Major E/Q in Wellington, calibrated to 1 in 500

Major E/Q not in Wellington, calibrated to 1 in 500

Non earthquake event occurring anywhere, calibrated to 1 in 250

And onerous Australian guidance

15

“……an insurer to be able to articulate its view on overall probability of sufficiency with respect to model outputs…….”

Really?!

“More generally, boards and senior

management of insurers should satisfy

themselves that the policies and practices

they follow for catastrophe risk management

are sound and lead to appropriately prudent

outcomes.

Each insurer should ensure that it:

• clearly sets and articulates its appetite for

catastrophe risk;

• understands the strengths, weaknesses

and inherent assumptions of any models

it uses.”

Some insurer responses

16

Clarify who has responsibility for assessing the PML

Implement clear framework, and process for oversight

More communication with cat modellers

Better documentation

More education

Possible roles of stakeholders

17

Catastrophe modellers

Running models

Assessment of models

Sensitivities

Realistic Disaster

Scenarios

Reinsurance Manager

Improving data quality

Dialogue with modellers

Assess gaps in modelling

Design of reinsurance

arrangements

CFO, Actuary, CRO

Develop decision making

framework

Consistency with capital targets, risk

appetite

Consideration of key risks,

allowance for uncertainty

Set RDSs

CEO

Agree framework

Implement oversight process

Recommend PML and RI

Board

Set risk appetite

Agree framework

Oversight

Approve PML and RI

18

“The models are being ‘opened up’ and this will enable better

understanding and will impact insurer decision making.”

Understanding what is modelled

19 Source: GNS

Hazard - Seismic risk Response - Ground shaking (RMS Paper)

Damage - Damage Ratios

Ground shaking

20 Source: RMS Paper by Chang, Molas and Shome

Questions that an insurer may seek

answers to

21

What model are we using and why?

How does it compare to other models?

What are the key assumptions in the model?

How does the seismic assessment compare to GNS’ current view?

What would be the impact of using alternative views of ground shaking?

How was the damage ratio calibrated?

What did we learn from Christchurch about the damage ratio?

22

“If I was an insurer my main focus would be on ensuring our data is as

good as we can get it”

What insurer data is important?

23

For each location (vs each policy)

Location of risk Construction

details

Age of property

Exposure ANZSIC

24

“APRA keep asking us about our model for non-modelled perils.”

A framework that considers non-modelled

hazards and perils

25

Modelled PML

Explicit allowance for non modelled:

Hazards Costs

e.g. Fire following

earthquake

e.g. Loss Adjustment

Expenses

Are these modelled?

26

Hazards

“Ultra-liquefaction”

Landslide

Fire following

Sprinkler leakage

Tsunami

Costs

LAE

BI

Fences, driveways

Temporary accom

Legal

Post loss amplification

Loss of rent (tenanted)

Infrastructure

27

“Its hard to know what to do about unknown unknowns, or

known unknowns for that matter.”

28

“The Board wants to know if we have we identified 85% of the risk,

or 25%. What is the order of magnitude?”

29

“We are uncertain about how to deal with the uncertainty”

Unknowns

30

“Geologists have no information on when the fault last

ruptured as it was unknown until last weekend. All we

can say at this stage is that this newly revealed fault

has not ruptured since the gravels were deposited

around 16,000 years ago.”

GNS NZ 6/9/2010

Known unknowns

31

Post loss amplification

Normal inflation associated with delays

Unintended/unexpected types of payments

Demand surge

Fraud

Legal costs

Approaches for dealing with uncertainty

32

Make no adjustment

Blending the results of various catastrophe models

Adopt a higher return period

Add a judgemental margin

Add explicit margin tied to the assessment of uncertainty

Estimating cat model uncertainty

33

Is 50/50

assessment

of PML good

enough, or is

a higher

probability

preferred

34

“An RDS is a better way of gaining Board understanding.”

Lloyds RDS for Japan Quake

35

“Managing agents should consider

all other lines of business that

would be affected by the event.

Particular consideration should be

given to losses arising from:

1) Personal Accident - it should be

assumed that 2,000 deaths and

20,000 injuries will arise as a

result of this major earthquake.

Assume that 50% of those injured

will have PA cover……..”

Issues a Director may consider

36

Linked to oversight

How did we assess how good

our data is? Do we have a

process for dealing with

shortcomings?

How did we assess different

models?

How did we assess what

perils are not modelled?

How does the level of

protection compare to our

competitors?

How should we allow for

uncertainty?

As evidence of process

What model are we using and

why?

What allowance is made for

growth?

What costs are not allowed for

by the models?

Did we prepare RDSs? What

did we learn from them?

Final thoughts

37

Yes there is a lot of uncertainty

The models are a good place to start, but not the end point

We have learned a lot in recent years

Resist ITALY.

Keep asking questions, but don’t expect them all to be answered (yet)

Diversified insurers have an advantage

Distribution & Use

This presentation has been prepared for the New Zealand Director

Forum, held on 19 February 2014. It is not intended, nor necessarily

suitable, for any other purpose.

Third parties should recognise that the furnishing of this presentation

is not a substitute for their own due diligence and should place no

reliance on this presentation or the data contained herein which

would result in the creation of any duty or liability by Finity to the

third party.

Reliances & Limitations

Finity wishes it to be understood that the information presented at

the seminar is of a general nature and does not constitute actuarial

advice or investment advice. While Finity has taken reasonable

care in compiling the information presented, Finity does not warrant

that the information provided is relevant to a particular reader’s

situation, specific objectives or needs.

Finity does not have any responsibility to any attendee at the

conference or to any other party arising from the content of this

presentation. Before acting on any information provided by Finity in

this presentation, readers should consider their own circumstances

and their need for advice on the subject – Finity would be pleased to

assist.