P&C Cat modelling: reinsurer’s standpoint...Les innovations face au développement des catastrophes non-vie Tours, 19 March 2013 . Impossible d’afficher l’image. 2 P&C Cat modelling:

P&C Cat modelling: reinsurer’s standpoint Benoît Hugonin Director of Prudential affairs - SCOR Les innovations face au développement des catastrophes non-vie Tours, 19 March 2013

Impossible d’afficher l’image.

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P&C Cat modelling: reinsurer’s standpoint

1 Attitude when CAT risk materializes

2 Providing diversification

3 Beyond model limitations

4 Beyond the non modelled


3

2011 was a year characterized by record Cat losses, exceeding $100 billiion1) for the insurance industry

Floods in Australia

Earthquake in New Zealand

Floods in Thailand

Earthquake and tsunami in Japan

2011 is the second most impacted year in terms of the frequency and level of nat cat losses

1) Source : AM Best report of 23 April 2012


4

In this volatile environment, reinsurers have fully played their shock-absorbing role

Financial disruptions

Regulatory & tax changes

Pandemic risks

Accounting rules

Solvency requirements

Protectionism menace

New risks

Expanding universe of shocks & ruptures

Nat cat, climate change

Anticipating and detecting early disruptions and discontinuities

Interpreting the various positive and negative news flows

Distinguishing potential adverse developments

Absorbing shocks

Respecting risk appetite and buffer capital

Optimizing ILS and retrocession protection

Enhancing financial flexibility Maximizing diversification

Identifying uncertainties 1

4

Assessing the potential impact of shocks on assets and/or liabilities

Using simulation models where necessary

Solving the “ambiguity” dilemma: change in statistical distributions or specific draws from a given distribution?

Using decision-making tools in uncertain environment models

Evaluating various alternative hedging strategies

Minimizing ex-post regrets

Preventing & hedging risks

Quantifying uncertainties 2

3

Source: SCOR


5

Reinsurers’ reactions when CAT risk occurs

After exceptional losses in 2011, some reinsurers have reconsidered their business models and have been retrenching

2 possible attitudes for reinsurers: Opportunistic approach Long-term commitment

Benefits of long-term commitment:

Providing capacity in tough times is an essential part of the value proposition of reinsurers over the long term

Pulling out of a market after a big Cat event doesn’t make sense. One event doesn’t usually make another one more likely!


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Strong franchise means constant innovation

A joint development project with RMS, the Cat Platform: Streamlines portfolio accumulation processes and integrates in real-time with SCORs contract management

system Uses simulated Year Loss Table methodology, providing more accurate modelling of reinstatements,

aggregate terms and seasonality Is designed to accommodate SCOR’s internally developed cat models and 3rd party models in addition to RMS

views, as such or in blended solutions

SCOR has deployed v1.0 of its Cat Platform Technology

SCOR supports new open-architecture cat modelling initiative

SCOR is part of an industry initiative (OASIS) to develop an open-architecture cat modelling framework, which aims to: Support validation of the existing suite of vendor models by enabling access to alternative views of hazard /

vulnerability models Facilitate the development of new models for territories that are not currently supported by the main vendors,

with the Thailand Flood model an early candidate


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8

High diversification facilitates better management of cat risk

Much has been said over the past few months against diversification:

"de-diversifying“ "di-worse-ification“ “diversi-fiction”…

We believe in the virtues of diversification, be it:

geographic diversification diversification across P&C lines of business… diversification between Life and Non-Life


9

Cat risks no longer always occur in the same place…

In Biblical times, plagues kept on striking the same country (Egypt) again and again: Water turned into blood Frogs Lice Flies Livestock diseases Unhealable boils Hail and thunder Locusts Darkness Death of the first-born of all

Egyptian humans and animals

Today, natural disasters do not always hit the same region

Source: Guy Carpenter, 2012


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The risk / return couple: optimization of the P&C and Life business mix

Diversification used for optimizing the return on risk taking

Risk / return curve based on the Life / Non-Life business mix

Risks (volatility of the portfolio)

Rat

e of

retu

rn

Minimized Risk taking

Optimized return on Risk taking

Life: ~50% of the

business mix

Life: ~75% of the

business mix

Life: 100% of the

business mix

Life: 0%

Sharpe ratio: Return per unit of risk

Market line

Intro | Internal Model | Diversification | Closing Remarks


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Diversification benefit: writing different CAT-lines (Gross figures)

Strong diversification benefits can already be realized by writing a portfolio of CAT-lines (different Peril / Region)

26,8%

7,2%

16,1%

10,7% 12,6% 12,5%

14,1%

19,5%

0,3% 3,0%

0,6% 2,2% 1,4%

3,8%

0%

10%

20%

30%

CAT-line 1 CAT-line 2 CAT-line 3 CAT-line 4 CAT-line 5 CAT-line 6 CAT-line 7

one-

year

cap

ital

StandaloneDiversified

0%

20%

40%

60%

80%

100%

Sum of standalone one-yearcapital across CAT-lines

Sum of diversified one-yearcapital across CAT-lines

one-

year

cap

ital CAT-line 7

CAT-line 6CAT-line 5CAT-line 4CAT-line 3CAT-line 2CAT-line 1

30.8%

100% = sum of GROSS standalone one-year capital across all CAT lines



12

Diversification benefit: writing different CAT-lines (Net figures)

Apart from the direct benefit from Reinsurance / Retrocessions additional diversification benefit is achieved through re-balancing CAT-lines to similar volume and volatility. The Scale is still based on the sum of the GROSS Stand-alone Capital to show effect of the Retro Protection.

12,8%

5,6%

7,8% 6,0%

10,7%

6,4%

10,4%

6,7%

0,3% 1,0% 0,3%

3,8%

0,7%

4,4%

0%

5%

10%

15%


one-

year

cap

ital


0%

20%

40%

60%

80%

100%



one-

year

cap

ital CAT-line 7


59.7%

17.3%

100% = sum of GROSS standalone one-year capital across all CAT lines



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CAT tools while mature, are not yet comprehensive.

Don’t forget the «non-modelled» !

57,8%

87,8%

42,2%

12,2%

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

90,0%

100,0%

Sum of standaloneone-year capitalacross CAT lines

Sum of diversifiedone-year capital

different CAT lines

CAT non-modelledCAT modelled

Impact on “modelled” & “non-modelled” CAT lines



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Diversification benefit (Net). with other lines of business & reserves

As expected material diversification benefits can be realized by additionally writing non CAT-lines. Scale is still based on GROSS for comparison to the two previous slides, showing the

combined effect of Retro and diversification with other lines.

12,8%

5,6%

7,8% 6,0%

10,4%

6,4%

10,4%

4,2%

0,1% 0,8% 0,3% 1,9%

0,6% 2,1%

0%

5%

10%

15%


one-

year

cap

ital

Standalone

Diversified

0%

20%

40%

60%

80%



one-

year

cap

ital CAT-line 7


59.7%

10.0%

100% = sum of GROSS standalone one-year capital across all CAT lines Note, diversification is across CAT and non-CAT lines, however, only the CAT-lines are displayed



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Diversification benefit: Illustration of the whole portfolio (Net)

Similarly, a global CAT portfolio aids in the diversification of the non-CAT lines. Scale is now the NET Standalone Capital of the whole portfolio, including

reserves

58,9%

41,1%

20,2%

8,8% 5,8%

1,1%

23,8%

48,0%

32,5%

6,6%

0,2% 3,6%

0,7%

13,7%

0%

10%

20%

30%

40%

50%

60%

Current UY Reserves CAT-line 1 CAT-line 2 Line of Business 1

Line ofBusiness 2

Line of Business 3

one

-yea

r cap

ital


100% = Standalone NET one-year capital Current UY + standalone NET one-year capital Reserves



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0100200300400500600700800900

-100%: -90%

-90% :-80%

-80% :-70%

-70% :-60%

-60% :-50%

-50% :-40%

-40% :-30%

-30% :-20%

-20% :-10%

-10% :0%

0% :10%

10% :20%

20% :30%

30% :40%

40% :50%

50% :60%

60% :70%

70% :80%

80% :90%

90% :100%

coun

ts o

f the

real

izat

ion

with

in th

e ra

nges

realization ranges

worst 1000 out of 100K realizations (1%) StandaloneDiversified

Negative outcome for the company positive outcome for the company

-100%= Most negative outcome for the company realized in the tail

100%= Most positive outcome for the company realized in the tail

How Diversification works: CAT-line 1 (Net figures) Worst 1% scenarios of Cat-line 1 (standalone), and Cat-Line 1 results in the worst 1%

scenarios of the whole portfolio (diversified)

There are still many scenarios where the contribution from a single CAT-line is profitable in the worst economic cases that drive the capital of the Non-Life company



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Diversification benefit: drivers for different Lines of Business (Net figures)

The drivers for & against diversification benefit are:

size/volume, volatility of the sub-portfolio as well as dependence with the rest of the portfolio

size of CAT-lines and LoBs is represented by the size of the spheres, respectively



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Cautionary preliminary conclusions

“The rising risk of extreme events has much in common with playing with

loaded dice.” - Pew Centre

Climate regimes: (El Nino, NAO, AMO) Climate change

Inaccurate dependencies

2010 & 2011 record years for natural hazards Increasingly frequent medium-severe to severe insured losses caused in

particular by “localized” natural catastrophes (tornadoes, wildfires, floods, hail storms, snow storms or frost)

Non-modelled or badly modelled losses


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Evolution of internal models

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Marke

t Ri

sk

Cred

it Ri

sk

Insur

ance

Ri

sk

Oper

ation

al Ri

sk

Financial Instruments Portfolio Data

Internal Group Retro.

Total Risk

Market Risk

Credit Risk

Insurance Risk

Financial Instruments

Portfolio Data

Scenarios

Risk Factors Financial Instruments

Valuation Engine

Portfolio Data

Internal Group Retro.

Management Strategy

Distributional and Dependency Assumptions

Balance Sheet

Profit and Loss Distributional and Dependency

Assumptions

Valuation Model 1

Valuation Model 2

Risk Model 1

Risk Model 2

Valuation Model 3

Collection of sub models quantifying parts of the risks

Quantification of different risk types

in a portfolio

Risk types are combined to arrive at

the company’s total risk in the tails

Modelling of underlying risk drivers with full

probability distributions

1960s - 1980s 1993 - today

Value Protection Value Sustainment Value Creation

Management Strategy



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Dependencies - Data insufficient to reliably measure

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• Domain of Risk Capital are the ‘tail’ or extreme scenarios (the 1/100 years for example)

• Historical data cannot capture the dependency at these extreme events, and sole reliance on it can be misleading

• Reliance on expert assessments, via an unbiased and thorough mechanism that digs into the sources of dependencies, is good complement.

X+Y

X Y

Assessment focus on the extreme scenarios and their causes:

“Suppose Y exceeds its 1-in-100 year threshold. What is the probability that also X exceeds its 1-in-100 year threshold?”

[ ])()( 99.099.0 YVaRYXVaRXP >>



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Calibration of P&C dependencies

The table represents a visual summary of the risk drivers documentation arisen from PrObEX

Risk drivers / Lines of Business

Natural Catastrophe

Man-Made Catastrophe Per Event Legal

Change Political Instability Economics Coinsurance

Model & parameter risks

Between LoBs

Agriculture

Auto

Aviation

Credit & Surety

Engineering

Liability

Marine

Property (Non CAT)

Space

Workers Comp.

Influence of risk drivers on LoB: high medium low

Inside LoB reading



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A couple of specific challenges to CAT (internal) models

Key requirements for internal models: 1. Reliable expert judgment / choice of assumptions 2. Data quality (appropriate, complete and accurate)

Additional challenges with CAT modelling

1. Use of external/vendor models 2. Rare events

Insurers and reinsurers are usually in different positions to face those challenges

1. Expertise on peak risks @ reinsurers > insurers 2. Data more directly available to insurers > reinsurers

Answers from a reinsurer

1. Robust documentation 2. Enhanced access to data through Cat Platform

Observations and Trends | Cat Platform Initiative | Fac Platform Initiative | Wrap-up and Q&A


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What is a platform?

Most importantly, a platform is not A piece of bolt-on software that is unnecessarily complex and weighty A silo software that you simply use for “running a model” and “generating a report”

A platform can simply be defined as a place to launch application software and it may include some baseline hardware and software.

A successful platform in the context of re/insurance should be an agile and scalable business eco-system and have, amongst other features:

A comprehensive toolkit that allows robust execution and reduction of “model-ware” clutter Be designed to go beyond the conventional limits of modelling by leveraging advances in

analytic and technical computing capability Be able to drive out manual and repetitive processes that don’t add value Create integration and automation points to other business workflows to aid decisions Improve risk quantification through risk intelligence (e.g. explore uncertainties /sensitivities) Allow generation of internal view of risk with interoperability, blending and calibration of

multiple model sources

SCOR’s Platform initiatives include the Cat Platform and the Fac Platform.



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The accidental cat modelling ecosystem

Cat models have become embedded within organisations and facilitate key functions : Cat pricing Portfolio management including post event response Inwards risk management and retro placement Calculation of capital adequacy Regulatory compliance and rating agency reporting

Off-the-shelf cat models have provided incredible value by enabling:

Improved Risk quantification of natural and man-made disasters Increased discipline across the entire risk transfer chain Ease of risk transfer through the “currency” of model outputs Robust risk management analytics Data creation to support the overall ERM process

Over the last 20 years or so...



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The accidental cat modelling ecosystem

Business leaders, regulators and practitioners are continuously raising the bar… Conventional model packages are creating real operational challenges for businesses Analytical appetite of users are no longer being fulfilled, challenges around:

Model performance/execution capability (behind what is needed and what is possible) Core financials are modelled well but more complex T&C’s on the perimeter are often not Business requirements around data governance (reporting/downstream) are increasing

across the entire risk transfer chain Models are generally fine (…although always evolving) for peak perils but not for

secondary, non-peak and un-modelled perils

Model inflexibility has forced companies develop suites of bespoke and complex ‘model interfacing tools’. These accidental modelling ecosystems have evolved over time but there are issues: Significant overhead to keep bespoke “model-ware” aligned High risk strategy and often this introduces key person risk Reached a saturation point where the value proposition is diminishing

The current challenges...



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Cat Platform – An ambitious development project

Platform capability to handle a reinsurers complex cat book including advanced analytics tools including: Cedant exposure analytics Cedant and portfolio modelling Dynamic portfolio risk aggregation an follow-up Portfolio management and optimization

Real-time integration with other production systems:

Contract management system Pricing Capital Model

Increased operational efficiency by driving out manual processes

Delivering interactive access and value to a broader internal audience beyond cat modelling team

Phased development with releases timed to deliver business value in time

State-of-the-art comprehensive analytical framework...



28

Cat Platform - Functional features overview

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Non-peak, non-modelled is no excuse for non-management

2011 Cat events were unusual: Regional pattern:

Asia-Pacific skew Non-Peak: over 50% of insured costs

Perils: Earthquakes/floods rather than wind Non-modelled: 28% of insured costs

Thai floods Australian floods

The lack of model can apply :

to the event itself: Copenhagen floods to secondary perils: Japanese tsunami following earthquake to the consequences for insureds: CBI/Supply chain disruptions

following Thai floods


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2011 : ‘Annus Horribilis’ for Catastrophe Losses…

Impact on the industry / society: over $100bn insured losses; Economic losses: ~ $350bn Mortality: ~27,000

Unusual (?) peril-regional pattern Asia Pacific skew Earthquake / Flood dominated

Non-Peak over 50% Everything apart from Tohoku,

Irene Non-modelled $30bn (28%)

Thai flood Australia flood

‘Surprises’ Japan: Mag, Tsunami, Fukushima US: Tornadoes NZ: Frequency, aftershocks,

liquefaction Thai/Japan: CBI / Supply Chain

A record year:

Intro | Blind Spots| Closing Gaps | Paradigm Shift | Closing Remarks


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…against a backdrop of higher expectations

Regulatory Solvency II and equivalent Internal model, ORSA, Pillar III…

Ratings Agencies Cat Questionnaires/Surveys ERM

Investors / Analysts Transparency, confidence

Clients Capacity Price stability Continuity

Management Effective controls Better information for strategic

decision making Protect Balance Sheet and Earnings

Stakeholder needs:



33

An incomplete vendor modelled view of global cat risk

Flood models (primary hazard) Thailand, Australia, India, China,

US, Brazil, Central Eastern Europe, Saudi Arabia…

2ndry perils Tsunami…everywhere Storm surge other than US, UK Fire-following earthquakes

Hail, Bushfire Correlations between perils

Large scale weather patterns El Nino/La Nina NAO, AMO

Lines of business Non-property CBI / Supply Chain

Not available…yet



34

Some ways to bridge the gaps…

Tracking exposure Availability Reliability Confidentiality Complex contracts

Extending the model framework Bolt on risk profiles Tsunami, Fire-following earthquake Correlate non-, badly-modelled LoBs

In-house models Not easy, but sometimes necessary Simple models, leveraging 3rd party

research Pricing and capital analysis

Coherence, consistency One internal model

Scenarios – thinking the unthinkable

…to a comprehensive view

0%10%20%30%40%50%60%70%80%90%

100%

2 5 10 15 20 50 75 100 200 250 500 1000

Model Pareto

TVaR contribution by Return Period



35

An Oasis in the desert?

An ‘open’ framework for cat modelling

Prototype models under

construction: UK Flood European Wind North Africa

Earthquake Cascadia Tsunami

New cat model initiative ‘Plug and Play’



36

Some closing comments (1/2)

Vendor cat models have served the industry well for 20 years, and will continue to for the next 20 …but, material gaps remain.

Insurers and reinsurers need more and better models, quicker than the ‘big 3’ can deliver

The cat modelling eco-system needs to and will get bigger



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Some closing comments (2/2)

But, risk that regulators somehow slow down that process of growth Delays with Solvency II

Growing skepticism around the use of internal models for regulatory purposes, for the time being in the banking world: “In surveying the failings of financial authorities, both here and abroad, one can certainly identify

some specific characteristics of pre-crisis regulation that look today to have been significantly misguided, rather than the advances they were formerly thought to be. So, for example, regulators became prone to place too much confidence in the capacity of firms to measure and manage their risks. […] a supervisory approach, which relies on a more opaque, firm-specific process of watching over banks' own risk-management and compliance systems. […] standardized measures serve as a floor to guard against the potential for models-based capital measures to understate capital needs under some circumstances. They are also substantially less opaque than, for example, the advanced internal ratings-based approach of Basel II, and thus would provide more comparable measures that are also more amenable to international monitoring.”

Daniel Tarullo, member of the Board of Governors of the Fed, 22 Feb 2013 Growing skepticism around diversification benefits

Joint Forum reports Insurance risk vs financial risk: not the same (in)dependence in stressed situations.


Documents

P&C Cat modelling: reinsurer’s standpoint...Les innovations face au développement des catastrophes non-vie Tours, 19 March 2013 . Impossible d’afficher l’image. 2 P&C Cat modelling: