XXIV International Seminar on Insurance and Surety ... Mehmet Ogut.pdf•Definition: Risk relating to business from prior accident years •Different lines of business modelled separately

Internal Models ©2014 Deloitte Consulting AG

CNSF – XXIV International Seminar on

Insurance and Surety

Internal models

20 November 2014

Mehmet Ogut

Internal Models ©2014 Deloitte Consulting AG 2

(1) SST overview

(2) Current market practice

(3) Learnings from validation of internal models

Internal models

Agenda


SST overview

3


• Aims to protect policyholders

• In-force since 2011

• “Largely equivalent” with Solvency II

• SST very strong in Pillar I

• FINMA may increase Pillar II (e.g. ORSA) and Pillar III (reporting)

requirements

Internal Models

SST overview

4

SST in force Solvency I

1973

2006

Compulsory

reporting for

large insurers

Compulsory

reporting for

all insurers

2008

2011

2013

Temporary

adjustments

Deemed

“largely

equivalent”

with SII


• The risk measure is the 99% Tail Value at Risk (aka Expected Shortfall)

• Requirement to model each legal entity explicitly

• Standard model consists of separate modules for market risk, life insurance

risk, non-life insurance risk, credit risk, scenarios (insurance and financial

scenarios, prescribed and company-specific), aggregation and the Market

Value Margin (risk margin)

Internal Models

SST overview

5


• Internal model requirements are principle based

• Documentation requirements covering methodology, parameterisation, data

quality, limitations and weaknesses

• Validation by FINMA is not a one-off exercise

• 69 companies (just over half of total number of SST participants) in

Switzerland have applied for internal models. 6 were accepted, 34

conditionally accepted and 29 declined

Internal Models

SST overview

Decision

Model accepted

To be used until essential

changes occur

Conditional accepted

Condition

Condition subsequent

Condition precedent

Legal requirements

Model declined

Fall-back solutions

Standard Model

Capital add-on / scenario

6


Current market practice

7


• All reinsurers are required to use internal models

• Most P&C insurers use internal models at least for insurance risk, most life

insurers use internal models for valuation, market and credit risk

• Modular approach

• Market risk

• Insurance risk (separate models for life and non-life)

• Sub-modules: reserve risk, premium risk, nat cat risk for non-life for example

• Scenarios

• Credit risk

• Outward reinsurance (including intra-group transactions)

• Aggregation

• MVM

• Expected result (technical plus financial)

Internal Models

Current market practice


Composition of required capital – P&C Composition of required capital – Reinsurers

9

• Most material risk is insurance risk for P&C insurers and reinsurers, and

market risk for life and health insurers

Internal Models

Current market practice – materiality of different risk types

Composition of required capital - Life Composition of required capital - Health

Source: FINMA website, SST 2014 results


• Definition: Risk relating to business from prior accident years

• Different lines of business modelled separately

• Approaches vary in terms of:

• Analytical (e.g. Mack) or Stochastic (e.g. bootstrap)

• Modelling ultimate risk and transforming it to one-year risk, or modelling one-year

risk directly

• Modelling claims together or separate modelling of large claims

• All approaches involve significant assumptions, increasing the importance of

validation

Internal Models

Current market practice – Example: P&C Reserve Risk


Portfolio information

Hazard model Vulnerability

model Event loss

table

11

Internal Models

Current market practice – Example: Natural Catastrophes

Scenario 1, e.g. WS Europe



model Event loss

table

Scenario 2, e.g. EQ California



model Event loss

table

Scenario 3, e.g. TC North America

Scenario 4, Scenario 5,………………..

Adjustments,

Aggregation

with Other Risks

in a Monte Carlo

Simulation,

Modelling of Outward

Reinsurance Conditions


• List of probabilistic events, frequency and intensity footprint of each

• Historic events are insufficient to capture all possibilities, so probabilistic

events are created using scientific models, with sub-models for:

• Generating the origin of the event (e.g. epicentre for earthquakes, or the tracks for windstorms)

• Attenuation functions to estimate the intensity (e.g. ground shake, wind speed, water depth) at

all locations affected by the event

• Allowance for soil characteristics, topographic factors, climatology, etc

• etc

• Sub-perils, e.g. storm surge, may be modelled as an extension of the hazard

model for the primary peril, e.g. wind, or separately

Earthquake zoning map for Turkey

Image from website of Kandilli Observatory and Earthquake

Research Institute

Sample output from the SLOSH storm surge

model, US National Hurricane Center

Global Tropical Cyclone Tracks, Wikipedia

Internal Models

Current market practice – Example: Natural Catastrophes (Hazard Model)


• Given the intensity of an event at each location, and characteristics of the

insured item(s), what will the insured loss be?

• Characteristics of the insured item:

• Location

• Policy conditions (e.g. deductibles, limits)

• Coverage (buildings, contents, business interruption, etc)

• Occupancy types (residential, commercial, industrial, etc)

• Construction type (brick, timber, etc)

• etc

• Vulnerability curves are often based on:

• Historical data

• Post-disaster surveys

• Engineering analyses, building code information

• PPA (Probability of Property to be Affected) and MDD (Mean Damage

Degree) may be modelled separately, or MDR (Mean Damage Ratio,

PPA*MDD) modelled directly

• It is common for secondary uncertainty to be allowed for in the model

Internal Models

Current market practice – Example: Natural Catastrophes (Vulnerability Model)


• Modelling NatCats is a complex task, parameter uncertainty and model

uncertainty can be significant

• There is no perfect model

• Significant differences between the results from different vendors

• FINMA expects that the companies are able to explain and justify their

selection between vendor models and own models, and the adjustments to

these by considering:

• Assumptions and limitations of the different models

• Their own risk profile

• The effort needed to build up this understanding, if not already there, is a big

task

Internal Models

Current market practice – Example: Natural Catastrophes


Learnings from validation Internal Models

15


1) Interviews & workshops in addition to reading documentation is often

essential

• Good documentation is essential but it often comes with gaps and ambiguity and can

be aspirational

2) Some insurers criticise the speed of the regulatory reviews but in my opinion

proper and valuable reviews need time,

• A lot of terms in requirements are ambiguous, e.g. “appropriate”, “reasonable”

• Quick checklist approach may lead to misleading conclusions

• IMs contains many parameters, takes time to understand them

• And changes in economic environment and modelling literature and market practice

may lead to new request/questions from the regulator

3) Benchmarking requires care

4) Assigning materiality to findings can be challenging

Internal Models

Learnings from validation of internal models


5) Some commonly not well-understood model elements, e.g.

• One-year risk

• Risk margin

• Model risk, parameter risk

• Intra-group guarantees (consolidated models do not give policyholder view)

6) Two types of validation

1.Checking whether the model works as documented

2.Checking whether the methodology makes sense and fit for the company using it

• Both are important, both require different types of skill set. FINMA sometimes

makes use of consultants. Specialist expertise and creativity required for the

second type.

7) Despite challenges in making conclusions on materiality, appropriateness,

etc, in most cases the discussions involved in design and validation of

internal models improve the company’s and the regulators understanding of

risk profile and lead to better decisions

Internal Models

Learnings from validation of internal models


Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (“DTTL”), a UK private company limited by guarantee, and its network of member firms,

each of which is a legally separate and independent entity. Please see www.deloitte.com/ch/about for a detailed description of the legal structure of DTTL

and its member firms.

Deloitte Consulting AG is a subsidiary of Deloitte LLP, the United Kingdom member firm of DTTL.

This publication has been written in general terms and therefore cannot be relied on to cover specific situations; application of the principles set out will

depend upon the particular circumstances involved and we recommend that you obtain professional advice before acting or refraining from acting on any of

the contents of this publication. Deloitte Consulting AG would be pleased to advise readers on how to apply the principles set out in this publication to their

specific circumstances. Deloitte Consulting AG accepts no duty of care or liability for any loss occasioned to any person acting or refraining from action as a

result of any material in this publication.

© 2014 Deloitte Consulting AG. All rights reserved.

Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (“DTTL”), a UK private company limited by guarantee, and its network of member firms,

each of which is a legally separate and independent entity. Please see www.deloitte.com/ch/about for a detailed description of the legal structure of DTTL

and its member firms.

Deloitte Consulting AG is a subsidiary of Deloitte LLP, the United Kingdom member firm of DTTL.

This publication has been written in general terms and therefore cannot be relied on to cover specific situations; application of the principles set out will

depend upon the particular circumstances involved and we recommend that you obtain professional advice before acting or refraining from acting on any of

the contents of this publication. Deloitte Consulting AG would be pleased to advise readers on how to apply the principles set out in this publication to their

specific circumstances. Deloitte Consulting AG accepts no duty of care or liability for any loss occasioned to any person acting or refraining from action as a

result of any material in this publication.

© 2014 Deloitte Consulting AG. All rights reserved.

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XXIV International Seminar on Insurance and Surety ... Mehmet Ogut.pdf•Definition: Risk relating to business from prior accident years •Different lines of business modelled separately