Solvency II Revealed
October 2011
Contents
4
An Optimal Insurer in a
Post-Solvency II World
27
Boosting Knowledge of Life
Catastrophe Risk
10
Changing the Landscape of
Insurance Asset Strategy
32
Rating Agencies and Solvency II
35
Reinsurance Assets: Aggregate or
Individual?
41
Risk and Capital Modelling for
Solvency II: A Pillar of Strength
16
Capital Relief Through Reinsurance
21
Natural Catastrophe Capital
Requirement Under Solvency II
Aon Benfield
Solvency II Revealed
The insurance industry has seen an extraordinary rise to prominence for the proposed Solvency II regulation
which will bring fundamental reform of insurance supervision across Europe. As the deadline for implementation
approaches, and the economic environment continues to present significant challenges, the key is in
understanding how and where to prioritise resource to not only achieve compliance but also make the most of
the business opportunities that Solvency II offers.
Aon Benfield, in collaboration with its clients, has made enormous progress in understanding the practical implications
of the new regulatory landscape. Solvency II Revealed explores new ways of thinking about the regulatory challenges
and practically addresses these through a series of in-depth articles and case studies. Aon Benfield identifies where
Solvency II will have most impact on the industry, with advice on how best to plan ahead for all roles involved in
managing the regulation from CFO and CRO to actuaries and catastrophe modellers.
Seven key themes are explored in the report:
t "O0QUJNBM*OTVSFSJOB1PTU4PMWFODZ**8PSME After Solvency II implementation, what will a capital-efficient insurer
look like? Taking a long-term approach, the article predicts how an insurer would structure its business to maximise
capital efficiency under the Solvency II rules, considering both the asset and liability sides of the balance sheet.
t $IBOHJOHUIF-BOETDBQFPG*OTVSBODF"TTFU4USBUFHZ The insurance industry faces significant challenges
transitioning to an economic framework for investments. The article reveals how Solvency II will impact insurance
asset strategy and identifies the key considerations for the CFO and CIO in repositioning their portfolio to achieve
capital efficiency and sidestep possible dislocations in the financial markets.
t $BQJUBM3FMJFG5ISPVHI3FJOTVSBODF This case study examines the potential impact of a non-proportional
retention protection reinsurance on the non-life solvency capital requirements (SCR) for a notional company under
the Standard Formula. The study demonstrates how such a contract can substantially reduce capital requirements as
an additional benefit of the reinsurance protection.
t /BUVSBM$BUBTUSPQIF$BQJUBM3FRVJSFNFOU6OEFS4PMWFODZ** Internal models, despite requiring a significant
investment, result in more accurate reinsurance recoveries and, consequently, net capital requirements, than the
Standard Formula. The article delves into the alternatives to calculate insurers’ natural catastrophe SCR.
t #PPTUJOH,OPXMFEHFPG-JGF$BUBTUSPQIF3JTL Assessment of terrorism and pandemic risks has been taken to a
new level through innovative developments in partial internal models. Case studies are used to illustrate the
risk-mitigating effect of reinsurance.
t 3BUJOH"HFODJFTBOE4PMWFODZ** Not only are regulators focused on Solvency II, but to no surprise, so are the
rating agencies. Reviewing recent feedback from rating agencies, the article helps reinsurers prepare for the
potential impacts of rating agencies’ calculations of capital requirements.
t 3FJOTVSBODF"TTFUT"HHSFHBUFPS*OEJWJEVBM Calculating the fair value of a reinsurer’s share of technical non-life
liabilities could be a challenging task if the reinsurance programme has changed in recent years. This article examines
Solvency II’s framework directive requirements and presents two different approaches from a practical perspective.
t 3JTLBOE$BQJUBM.PEFMMJOHGPS4PMWFODZ** a pillar of strength: Companies using internal models need to ensure
they satisfy each pillar of Solvency II. The article highlights how an internal model can deliver tangible benefits
when completing the Own Risk and Solvency Assessment (ORSA) and help companies prove to regulators that risk is
being effectively managed.
Aon Benfield is helping insurers prepare for all pillars under Solvency II by identifying cost effective means of
improving capital efficiency, by assisting with modelling of asset and underwriting risks and by validating
(partial) internal models and ESGs. The firm offers expertise on both sides of the balance sheet and is advising
clients on designing optimal insurance and asset strategies under Solvency II. Our Solvency II capabilities
comprise asset management, reinsurance and capital market solutions covering life, non-life and health insurance.
As the industry rapidly approaches implementation, Solvency II Revealed aims to provide insurers with a fresh view
of Solvency II and empower firms to achieve both regulatory compliance and a level of capital efficiency that
exceeds investors’ expectations.
3
Solvency II Revealed
An Optimal Insurer in a
Post-Solvency II World
3FWFBMFE
Uniting the management of insurance and asset risk provides a valuable opportunity for
insurers to implement better management practices by viewing risk and capital
holistically. This approach targets the overall balance sheet risk rather than insurance or
investment risk as a silo. By leveraging the internal model framework, insurers can
optimise business strategy across insurance and investment to improve both shareholder
return and economic efficiency.
Solvency II is changing the way regulatory capital is
assessed for European insurers. The results of the latest
impact assessment study, QIS 5, suggest that the
average solvency ratio for non-life European insurers
will drop from over 200% to around 165% (overall ratio
since non-life ratio is not available separately).
Additionally, unlike the existing Solvency I regime,
Solvency II uses a risk-based approach to set the level of
each individual insurer’s solvency capital — thus
requiring more capital to be held for riskier insurance
and investment activities. This means that insurers that
take a higher level of risk, as measured by Solvency II,
will suffer a far greater fall in solvency ratio than those
with less risky portfolios, whose solvency ratio may
even improve.
Despite presenting clear challenges, Solvency II also
offers insurers the opportunity to improve their
business strategy through better allocation of risk and
capital to target opportunities that provide the highest
rate of return per unit of risk. Solvency II encourages
firms to view risk, capital and value from a top-down
perspective, rather than from a silo based approach.
Insurers must set strategy in accordance with two sets
of constraints simultaneously: the capital constraints
imposed by regulators, and the economic constraints
imposed by stakeholders, including shareholders,
policyholders and management. To maximise
performance, insurers must pursue a combined strategy
for both sides of the balance sheet — a strategy that
comprehends the potential dependence between
insurance and asset risk behaviour.
To date, very few organisations have optimised their
allocation of risk and capital across both insurance and
asset risk under a consistent measurement framework.
4
In practice, the two sides of the balance sheet have
been managed by separate business functions and
strategies are set without a full understanding of the
impact on the overall level risk and capital. For
example, credit insurance losses are highly correlated to
economic risks and setting asset strategy without
consideration of insurance risks may result in a strategy
that actually increases overall risk for the firm.
New approach for optimisation
Aon Benfield has developed an optimisation process for
setting consistent strategy across asset and liability
risks, recognising all relevant economic and capital
constraints. This process will support insurers to better
manage their risk and capital under Solvency II. In a
post-Solvency II world, those insurers that can
transform their business to maximise economic and
capital efficiency will enjoy competitive advantages and
improved shareholder returns.
The process is outlined below, with sample exhibits for
a hypothetical insurer “Multi-line Plc”. Figure 1
illustrates the process for optimising the firm’s overall
business strategy across insurance and asset risk.
The initial strategy of Multi-line Plc is derived from the
insurance and asset strategy of the average non-life
company in Europe. The risk assessment of the existing
business strategy has been carried out using the Aon
Benfield Insurance Risk Study assumptions for 2011 for
underwriting volatility and correlations and Aon Hewitt
Capital Market Assumptions 2011 for asset risk.
Additional assumptions for reserve risk and underwriting
performance have been assessed using industry data.
The Aon Benfield business strategy optimisation process
for Multi-line Plc is illustrated on the next page:
Aon Benfield
Figure 1: Aon Benfield Process for Insurance and Asset Strategy Optimisation
Insurance Asset Strategy Optimisation
1
Articulate the firm’s overall risk
appetite, capital target and driver
of shareholder value
Risk
t "SUJDVMBUFSJTLBQQFUJUFTUBUFNFOU
Risk
t *EFOUJGZRVBMJUBUJWFDPOTUSBJOUT
Capital
Capital
t *EFOUJGZCJOEJOHDBQJUBMNFBTVSF
e.g. 150% Solvency II ratio
t 4UBOEBSEGPSNVMBWT*OUFSOBM
model
Value
Value
t 4IBSFIPMEFSTSFXBSETUBCMF
earnings volatility combined
XJUIBUUSBDUJWF30&
2
Identify optimal allocation of
insurance risk under selected risk
and capital measure
Insurance
Classes
Insurance
Classes
t *EFOUJGZVOJWFSTFPGJOTVSBODF
risks
Insurance
Constraints
Insurance
Constraints
t .JONBYBMMPDBUJPOTSFMBUJWFUP
current strategy
Optimise
Optimise
Insurance
Insurance
Strategy
Strategy
t $SJUFSJBGPSPQUJNJTBUJPO
t 2VBOUJGZSJTLBOESFUVSO
characteristics
t 0WFSBMMQSFNJVNWPMVNF
t &DPOPNJDFƆDJFODZBOEDBQJUBM
FƆDJFODZ
3
Utilise remaining risk and capital
budget to develop optimal
investment strategy
Asset
Asset
Classes &
Classes
&
Constraints
Constraints
t *EFOUJGZBENJTTJCMFBTTFUTGPS
firm
Insurance
Insurance
& Asset Risk
&
Asset Risk
Model
Model
t 'VMMNPEFMPGJOTVSBODFBOE
asset risk
Optimise
Optimise
Asset
Asset
Strategy
Strategy
t 4USBUFHJDBTTFUBMMPDBUJPO
to identify portfolios that
NBYJNJTFSFUVSOXJUIJOSJTL
budget and capital budget
t *OTVSBODFTQFDJmDBTTFU
constraints
t 2VBOUJGZPWFSBMMCBMBODFTIFFU
SJTLBOEDBQJUBMSFRVJSFNFOU
Source: Aon Benfield
1
Risk Appetite, Capital Target
and Drivers of Value
Overall risk for the firm will be quantified as the
volatility of surplus, i.e. assets less liabilities, from
all sources of insurance and asset risks. An internal
model of the full balance sheet will be utilised to
measure surplus volatility and to consistently
allocate risk between insurance and asset risks.
Aon Benfield’s price-to-book regression study
points to a volatility measure of risk as best
capturing investor risk tolerances.
The binding capital metric for Multi-line Plc is the
Solvency II capital requirement (SCR) under the
Standard Formula. Capital utilisation for insurance
and asset risks will be measured by the
contribution to the overall SCR from non-life
insurance and market risk. This assumes that
shareholders are motivated by optimal exposure to
insurance risks, careful management of balance
sheet volatility and attractive returns on equity.
Following consultation with Multi-line Plc’s
management, the overall risk appetite for the
company has been articulated as 10.0% surplus
volatility across both insurance and asset risk,
hence maintaining its existing level of overall
balance sheet risk. Its existing Solvency II ratio of
165% has been judged an appropriate long term
position and the strategy review should maintain
this level of capital adequacy.
2
Identify Optimal Allocation of Insurance Risk
The firm wants to improve its insurance strategy to
generate improved returns for shareholders and
achieve better risk characteristics. Shareholders of
non-life insurers typically seek firms that offer
exposure to a carefully selected portfolio of
insurance risks, with an asset strategy that supports
their liabilities and enhances risk-adjusted return
within the overall risk and capital budget.
Therefore, when optimising the insurance and
asset strategy of a non-life insurer, the first stage is
to optimise the insurance portfolio. Once the
optimal allocation of insurance risks has been
selected, the remaining risk and capital budget can
be deployed to enhance shareholder returns
through the asset strategy.
Multi-line Plc has defined upper and lower
bounds for premium volume by class of business
and agreed that the total premium volume can
vary between 85% and 100% of the current level
(€100m): by optimising the risk allocation it may
be possible to achieve higher profitability at a
lower premium volume.
5
Solvency II Revealed
Table 1: Insurance Allocation Constraints
Allocation
LOB
Initial
Min
Max
.PUPSWFIJDMFMJBCJMJUZ
33%
28.0%
38.0%
.PUPSPUIFSDMBTTFT
18%
15.5%
21.0%
.BSJOFBWJBUJPOBOEUSBOTQPSU
4%
2.5%
4.5%
'JSFBOEPUIFSEBNBHFUPQSPQFSUZ
30%
25.5%
34.5%
General Liability
12%
8.5%
14.5%
$SFEJUBOETVSFUZTIJQ
4%
2.5%
4.5%
Source: Aon Benfield
The Solvency II capital efficient frontier differs from the
economic frontier, and capital allocations that are
efficient under the proposed Standard Formula can be
suboptimal from an economic perspective. This is
because the proposed Standard Formula assesses
capital based on prescribed volatilities and correlations
for non-catastrophe underwriting risk and prescribed
events for natural and man-made catastrophes — these
prescribed factors are not based on economic best
estimates and are often conservative.
The goal of optimisation is to identify portfolios of
insurance risk that are efficient from both the economic
and capital perspective. The identification of jointly
efficient portfolios is achieved by comparing the
economic and capital efficient frontier and seeking
portfolios that lie on the intersection of the two
frontiers. Figure 2 plots the economic and capital
efficient frontiers on a single graph in volatility-return
space. The economic and capital efficient frontiers
coincide in locations A and B, which provide jointly
optimal allocations. In order to decide which mix of
insurance risk is preferable, it is necessary to consider
performance metrics at the two candidate portfolios.
6
Figure 2: Superimposition of Economic
and Capital Efficient Frontiers
4.1
Economic
Capital
B
3.9
3.7
3.5
Profit
An internal model of the insurer is created and, using
Aon Benfield’s proprietary optimisation framework,
determines the economic and capital efficient frontiers
of the insurance portfolios that provide the maximum
expected profit for a specified level of economic
volatility or Solvency II capital utilisation, respectively.
3.3
3.1
Initial Portfolio
A
2.9
2.7
2.5
8.0%
8.1%
8.2%
8.3%
8.4%
8.5%
8.6%
8.7%
8.8%
Economic Volatility
Source: Aon Benfield
In Figure 3, the insurance portfolio composition is
shown along the economic efficient frontier and two
performance metrics: the economic Sharpe ratio and
return on capital. In comparing options A and B, the
highest ratio of profit to risk and capital is sought: this
will achieve the optimal allocation of insurance risk.
The selected portfolio is at the left most point of the
intersection of the economic and capital efficient
frontier in region B, where both the economic Sharpe
ratio and return on capital is higher than at region A,
leading to greater profit per unit of risk and capital. This
portfolio provides the best combination of economic
and capital efficiency.
Aon Benfield
Figure 2: Optimisation of Insurance Risk Under Economic Risk Measure
100%
40%
90%
35%
80%
30%
Allocation
70%
60%
B
A
50%
25%
20%
40%
15%
30%
10%
20%
5%
10%
0%
0%
8.04%
8.10%
8.20%
8.30%
8.35%
8.40%
8.45%
8.50%
8.55%
8.60%
8.65%
8.70%
8.75%
Economic Volatility
Credit and Suretyship
Marine, Aviation and Transport
General Liability
Fire and Other Damage to Property
Motor and Vehicle Liability
Motor, Other Classes
Sharpe Ratio
Return on Capital
4.5
Optimal Portfolio
4.0
3.5
Profit
3.0
Initial Portfolio
2.5
B
2.0
1.5
1.0
0.5
0.0
8.0%
8.2%
8.3%
8.4%
8.5%
8.6%
8.7%
8.8%
8.9%
Economic Volatility
3
Optimisation of Asset Strategy
Having selected the optimal insurance portfolio, the
next stage is to investigate how the asset strategy
can be improved within the remaining risk and
capital budget for the firm. Overall, the level of
insurance volatility has increased by 3 bps and the
non-life Solvency II capital has increased by EUR0.1m.
As the total budget for risk is 10.0% and the firm is
targeting a 165% Solvency II ratio, this imposes two
constraints on the asset portfolio:
t 5IFDPOUSJCVUJPOPGBTTFUSJTLUPPWFSBMMTVSQMVT
volatility must be such that overall surplus volatility
does not exceed 10.0%. This will be computed as
part of the optimisation as it is dependent on
economic liability correlations
t 5
IFDPOUSJCVUJPOPG4PMWFODZ**NBSLFUSJTLTIPVME
be such that the overall SCR remains at the current
level of EUR69.56m: through calculation this
implies that the SCR_Mkt should be EUR29.86m
In assessing the overall level of surplus volatility for
the optimised insurance strategy alongside candidate
asset portfolios, it is important to consider the impact
that liability volatility has upon economic risk.
7
Solvency II Revealed
Figure 2b: Optimisation of Insurance Risk Under Economic Risk Measure
Portfolio
Initial
1
2
3
4
5
6
0QUJNBM
8.62%
8.0%
8.2%
8.4%
8.5%
8.65%
8.77%
Profit
3.3
2.6
3.2
3.4
3.6
3.8
4.0
4$3@/-
56.8
54.1
55.0
55.7
56.3
56.86
57.3
4IBSQF3BUJP
10.2%
22.3%
30.6%
31.1%
31.1%
31.0%
31.0%
3FUVSOPO$BQJUBM
5.9%
4.8%
5.9%
6.2%
6.5%
6.7%
6.9%
.PUPSWFIJDMFMJBCJMJUZ
33.2%
28.0%
28.0%
28.0%
28.0%
28.0%
28.0%
.PUPSPUIFSDMBTTFT
18.0%
18.0%
15.5%
15.5%
15.5%
15.5%
15.5%
.BSJOFBWJBUJPOBOEUSBOTQPSU
3.7%
2.5%
4.5%
4.5%
4.5%
4.5%
4.5%
'JSFBOEPUIFSEBNBHFUPQSPQFSUZ
30.1%
25.5%
25.5%
26.9%
29.0%
31.1%
33.0%
General Liability
11.5%
8.5%
8.5%
10.5%
12.1%
13.7%
14.5%
$SFEJUBOETVSFUZTIJQ
3.5%
2.5%
4.2%
4.5%
4.5%
4.5%
4.5%
100.0%
85.0%
97.3%
89.9%
93.6%
97.3%
100.0%
Allocation
Statistics
&DPOPNJD7PMBUJMJUZ
Total
Source: Aon Benfield
In performing the asset strategy optimisation in the
context of the overall insurance balance sheet, the
following key characteristics are incorporated into
the asset liability model:
t Interaction of liability uncertainty with
economic risk: unavoidable market risk arises
due to liability volatility interactions with interest
rate risk. For example, if the liabilities increase by
50% then impact of interest movement will also
increase by 50%.
t E
conomic liability correlation: some insurance
risks, such as credit and surety, are highly
correlated to the economy. Ignoring economic
liability, correlation understates true level of
overall risk, leading to incorrect allocations
Using the asset liability model under our
optimisation framework, a constrained efficient
frontier of asset portfolios is determined for which
the Solvency II market risk capital requirement does
8
not exceed EUR29.86m. The optimal asset portfolio
for the company is then determined by the portfolio
lying on the efficient frontier that achieves an overall
surplus volatility of 10.0%.
However, while this portfolio will provide optimal
return characteristics within the risk and capital
budget, it lacks a number of desirable qualitative
features. The asset strategy is refined by overlaying
qualitative constraints for insurance:
t .
JOJNVNDBTIFRVJWBMFOUBTTFUTPGGPS
liquidity purposes (e.g. cat events)
t .
BYJNVNBTTFUTMJBCJMJUJFTNJTNBUDIPGœ
years at each key rate duration
t .
BYJNVNBMMPDBUJPOUPSFBMFTUBUFBOESFUVSO
generating assets of 10%
This will help ensure that the asset portfolio is robust
during economic downturns and has good asset
liability characteristics for non-life insurance.
Aon Benfield
Figure 4: Optimal Asset Portfolio Composition
100%
Initial
2.5%
60%
2.3%
50%
40%
2.2%
30%
2.1%
Excess Return
2.4%
70%
$POTUSBJOUT
80%
Allocation
Portfolio
2.6%
90%
20%
Optimal
.JO$BTI&RVJW
-
20%
.BY,FZ3BUF%VSBUJPO.JTNBUDI
-
±1 year
.BY3FUVSO(FOFSBUJOH
-
10%
.BY3FBM&TUBUF
-
10%
10.0%
0WFSBMM4VSQMVT7PM
2.0%
.BY4$3
0%
1.9%
&YDFTT"TTFU3FUVSO
2.12%
2.50%
&DPOPNJD4VSQMVT7PM
3.54%
3.46%
4$3
30.00
29.86
4VSQMVT4IBSQF3BUJP
32.68%
43.06%
30$
17.41%
20.02%
0.96
0.95
Initial
Optimal
Em Eq
AA Credit 5
Equities
Gov Bonds 1
FoHF (Hedged)
Gov Bonds 3
A Credit 10
Excess Return
Real Estate
Cash
AA Credit 10
A Credit 5
Private Equity
Gov Bonds 5
Statistics
10%
29.86
%VSBUJPO.JTNBUDI
Source: Aon Benfield
The optimal asset strategy shown in Figure 4 has provided a 38 bps increase in return compared to the initial portfolio,
while meeting quantitative constraints for risk and capital budgeting and insurance.
Conclusion
Multi-line Plc’s economic and financial characteristics
have been transformed under Aon Benfield’s proprietary
optimisation framework. Underwriting performance has
been significantly enhanced by optimising premium
volumes across each class of business, while applying
realistic constraints to limit significant deviation from
the initial underwriting strategy. The recommended
insurance strategy was selected as the portfolio of
insurance risks that:
t -JFTPOUIFJOUFSTFDUJPOPGUIFFDPOPNJDBOEDBQJUBM
efficient frontier
t 1SPWJEFTUIFIJHIFTUFDPOPNJD4IBSQFSBUJPBOE
return on capital
This portfolio provides the greatest profit per unit of risk
and capital among all possible allocations of insurance
risk within the specified constraints.
After allocating risk and capital to the optimal insurance
strategy, the remaining risk and capital budget was
allocated to an optimal asset strategy. The selected asset
strategy fully utilises the remainder of the risk and capital
budgets and provides optimal return while meeting
bespoke qualitative constraints specific to insurance.
As shown in Figure 5, the overall financial and economic
impact of the business strategy optimisation is an
increase to expected profit of EUR1.4m, an improvement
of shareholder return from 13.3% to 14.5%. In addition,
there has been no increase in volatility or capital
requirement under Solvency II.
Figure 5: Overall Comparison of Initial and Optimal Business Strategy
17.00
Vol.
SCR
Sharpe
Ratio
ROE
Initial
3.34
8.62%
64.37
24.45%
2.91%
0QUJNBM
3.81
8.65%
64.46
31.03%
3.32%
Initial
11.89
3.43%
30.00
32.17%
10.36%
Liabilities
Assets
0QUJNBM
12.77
Initial
15.23
$PNQBOZ
0QUJNBM
Source: Aon Benfield
16.59
3.46%
29.86
9.97%
69.56
43.06%
11.13%
29.15%
13.27%
36.07%
14.45%
Expected Profit
Profit
Optimised
ROE of 14.45%
Initial
ROE of 13.27%
16.00
15.00
14.00
8.00%
9.00%
10.00%
11.00%
12.00%
Volatility
9
Solvency II Revealed
$IBOHJOHUIF-BOETDBQFPG
Insurance Asset Strategy
3FWFBMFE
Solvency II will change the investment behaviour of insurance companies. It introduces an
economic balance sheet and capital charges for assets that reflect the degree of asset risk and
asset liability matching. Under the Standard Formula, the calibration of some capital charges is
inconsistent with an economic view of risk. It is important to understand what potential market
dislocations could occur if a significant number of insurers choose to alter their investment
strategy accordingly.
Solvency II also encourages a holistic view of risk and capital across insurance and investment.
Allocating risk and capital across underwriting and investment more dynamically provides an
opportunity to deliver a more stable return to shareholders through the underwriting cycle.
Introduction
Solvency II is a major catalyst for insurance companies to
revisit their asset strategy, driven by capital requirements
that reflect the riskiness of each asset class and how well
assets and liabilities are matched in a fair value
accounting world. This is in contrast to the current state
of play under Solvency I, where the same level of capital
is required whether assets are held in cash or private
equity and no consideration is given to the sensitivity of
the firm’s valuation to movements in economic variables
such as interest rates and credit spreads.
The capital charge under Solvency II for asset and
economic risks is called the Market Risk Solvency
Capital Requirement and represents the potential
deterioration in the net asset value of the firm
following a 1 in 200 year event over a one year time
horizon across all asset and economic risks. This
includes the potential loss in asset values and increase
in liabilities due to changes in the discount rate. The
market risk charge is decomposed into contributions
from each underlying economic risk that drives
changes in asset and liability valuation: this consists of
a number of sub-modules that are described in Table
1. The capital charge for each sub-module is calibrated
to the 1 in 200 year return period over a 1 year time
horizon. The overall market risk charge is computed
by aggregating together each sub-module using a
prescribed correlation matrix to provide the 1 in 200
level of loss across all sources of market risk.
10
The transition into Solvency II raises a number of
important questions for insurance companies and this
article reveals how these can be addressed:
t )PXNVDIDBQJUBMTIPVMECFEFQMPZFEUPXBSET
market risk relative to underwriting and reserve risk?
t 8 IBULFZDIBOHFTBSFSFRVJSFEUPUIFJOWFTUNFOU
strategy under Solvency II to achieve capital
efficiency whilst targeting attractive returns?
t 8 IBUJNQBDUXJMM4PMWFODZ**IBWFPOUIFJOWFTUNFOU
markets and what steps could be taken to avoid
potential market dislocations?
Capital Allocation at the Enterprise Level
Historically non-life insurance companies have tended
to manage underwriting risk and investment risk as silo
activities under the Chief Underwriting Officer and the
Chief Investment Officer without joined up
measurement of risk and capital for the purposes of
setting strategy. Solvency II changes the way insurers
think about risk, capital, volatility and value generation
through unified risk management processes. Many
companies are introducing the role of Chief Risk Officer
who is responsible for managing the overall level of risk
and capital utilisation in the organisation across both
sides of the balance sheet.
Having a more holistic view of risk and capital provides
the non-life insurance industry an opportunity to
achieve more consistent levels of return on equity
Aon Benfield
bearing capacity that can be redeployed to support
higher yielding investment strategies until the market
turns, at which point investments can be de-risked and
a more aggressive underwriting strategy can be
followed. From this perspective, the objective of
investment strategy for non-life insurance should be to
enhance the firm’s return on equity within the risk and
capital budget remaining after following the optimal
underwriting strategy.
throughout the underwriting cycle by dynamically
allocating capital between underwriting risk and
investment risk. As illustrated in Figure 1, by continually
monitoring and forecasting the pricing cycle, business
plans can be adjusted to target business classes that
provide maximum profit per unit of risk and capital.
During soft markets, underwriting strategy can be
more cautious and premium volumes reduced
temporarily for less profitable lines. This will free-up risk
Table 1: Standard Formula: Overview of Market Risk Capital Changes
Risk
Capital Change
Implications
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capital change
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Property
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Spread
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income assets
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Solvency II
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Capital Charge by Duration
Duration
Factor
1
3
5
10
AAA
0.9%
0.9%
2.7%
4.5%
9.0%
AA
1.1%
1.1%
3.3%
5.5%
11.0%
A
1.4%
1.4%
4.2%
7.0%
14.0%
BBB
2.5%
2.5%
7.5%
12.5%
25.0%
BB
4.5%
4.5%
13.5%
22.5%
45.0%
B or lower
7.5%
7.5%
22.5%
37.5%
60.0%
Unrated
3.0%
3.0%
9.0%
15.0%
30.0%
Rating
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markets
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FHCPOEJTTVFS
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concentration threshold
t $
IBSHFPOMZBQQMJFTUPIPMEJOHTJOFYDFTTPGPGUPUBM
assets for credit ratings A or above and 1.5% of total assets
GPSSBUJOHT###PSMPXFS
Source: Aon Benfield
11
Solvency II Revealed
Figure 1: Dynamic Risk and Capital Allocation
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Capital Efficiency of Investment Strategies
The capital requirements for different asset classes
under Solvency II vary considerably and are not always
set in line with economic principles. This creates
inconsistencies between optimal strategies as viewed
from an economic risk measure and the Solvency II
Standard Formula capital requirements. It is important
therefore to develop a framework for setting
investment strategy that can incorporate the
management’s own view of risk alongside the
constraint of the Solvency II capital requirements:
while achieving capital efficiency is important, it
should not override the importance of careful risk
management. Where significant disparities exist
between the Standard Formula and economic
principles, one option is to develop a partial internal
model covering market risk or specific asset classes
where greater risk granularity is desired. For example,
the Standard Formula assigns a capital charge of 49%
12
to Other Equity which includes a wide range of
alternative assets. In the case of risky flavours of
private equity such as venture capital this is quite
sensible but for a diversified fund of hedge funds, this
would be overly cautious: hedge funds have historical
levels of volatility significantly lower than listed equity.
In setting investment strategy it is instructive to
understand the relative capital efficiency of different
asset classes. One approach for comparing the capital
efficiency is to consider the return on capital achieved
for each investment under current market conditions
from a silo perspective (i.e. ignoring its contribution
to diversification). This comparison can be helpful in
identifying whether the existing strategy is overweight
in less capital efficient assets. In Figure 2 key asset
classes’ return on capital under the Standard Formula
is compared to the economic view replicated using an
internal model view (based on current market
conditions).
Aon Benfield
Figure 2: Comparison of Return on Capital Across Asset Classes
6.0%
5.0%
ROC
4.0%
3.0%
2.0%
1.0%
d)
Eq
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(H
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HF
iv
at
Fo
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B
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it
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it
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B
BB
BB
B
Cr
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5
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it
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it
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Asset Class
ROC (Standard Forumla)
ROC (Economic)
Source: Aon Benfield, Aon Hewitt
The Standard Formula significantly overstates the risk
bearing capital required for longer duration credit and
hedge funds. It is also noteworthy that the riskiest
asset classes provide the highest return on capital,
despite having relatively high capital charges. Return
generating assets can still make an important
contribution to return on equity despite the 49%
capital charge — the impact of the additional expected
yield is greater than the marginal increase in capital
relative to less risky asset classes.
For non-life insurers an important consideration under
Solvency II is the capital charges for interest rate risk.
Currently most categories of non-life insurance
liabilities are accounted for on an undiscounted basis.
This means that the management and investors of
many non-life firms are focused on achieving positive
investment return in their income statement, rather
than considering the asset return achieved relative to
the return of the liabilities. Solvency II is encouraging
insurers to think about the economic balance sheet
and has significant capital charges for interest rate
duration mismatching. However, until IFRS 4 Phase 2
is implemented, the general accounting view will
continue to be based on undiscounted liabilities. An
important consideration will therefore be the trade-off
between capital efficiency and managing earnings
volatility on current accounting principles: will non-life
insurance investors understand that negative
investment returns do not necessarily represent an
economic loss when assets and liabilities are matched?
13
Solvency II Revealed
Impact of Solvency II on the
Investment Market
An important question is whether the new regulatory
framework could itself have an impact on the
investment market through changing the investment
behaviour of the insurance industry. We have already
seen that in many cases there is a disconnection
between the basis on which the capital charges have
been set under the Standard Formula and economic
reality. The insurance industry plays a significant role
in institutional investment and is a major participant in
European bond markets.
Changes in investment behaviour attributable to
Solvency II may originate from a number of sources
including:
1. Matching the components of the liability discount
rate to reduce balance sheet volatility
2. Capital constrained insurers who need to improve
their Solvency II ratio
3. Insurers who target an investment strategy that
maximises their return on equity under the
Solvency II Standard Formula for market risk
1. The Liability Discount Rate
Under the current proposals, liabilities are
discounted using a rate derived from the risk-free
rate plus an illiquidity premium. The risk-free rate is
swap based with an adjustment for credit risk and
the illiquidity premium is variable depending on
the level of illiquidity implicit in the liabilities: for
annuities in payment which cannot be altered this
will normally be 100% of the illiquidity premium
and other more liquid liabilities will have a low
percentage applied. The illiquidity premium itself is
based on the observed spread between a basket of
corporate bonds (using the iBoxx index) and the
swap rate that cannot be explained by credit risk.
Some insurers will be motivated to invest the assets
backing their technical provisions more closely to
the liability discount rate under Solvency II as this
will help to stabilise their Solvency II ratio.
14
2. Capital Constrained Insurers
Under Solvency II, the capital constrained insurer’s
concern will be primarily to take steps to reduce
the capital requirement. This means reducing
exposure to return generating assets that attract
the 39% and 49% charges and any other assets
that have large capital charges. As illustrated in
Table 1, long duration corporate bonds are capital
intensive and for credit rating BBB or lower are in
line with return generating assets. It is therefore
likely that insurance companies will reduce their
exposure to equities and longer duration bonds
rated BBB or lower. In addition, there is an
interesting secondary effect for life insurers.
Currently, life companies will invest in long
duration corporate bonds to match the duration of
their liabilities (typically 10 – 12 years). This works
well as the strategy provides a good yield that
enables competitive annuity pricing and the
liability discount rate is usually asset based so there
is no additional balance sheet volatility. As noted
previously, under Solvency II the liquidity premium
component of the discount rate is based on a
basket of corporate bonds, which supports
investment in matching bonds. However, under
QIS 5, the calculation of the spread risk stress test
has been disconnected to the illiquidity premium
stress so assets and liability valuations are stressed
separately. While an implicit link between spread
risk and illiquidity risk has been maintained
through a negative 50% correlation in the
aggregation calculation, this acts as a disincentive
to match the spread duration of the liabilities. The
more capital efficient strategy is to invest in shorter
duration corporate bonds which have a lower
spread duration, and hence capital charge, and to
utilise an interest rate swap to increase the rate
duration of the assets to that of the liabilities.
Aon Benfield
3. Maximising Return on Equity
As discussed earlier, the Standard Formula is not
consistent with an economic perspective which
means that firms aiming to maximise return on
equity may design an investment strategy that
differs substantially to their current asset allocation.
In particular, Figure 2 shows that long duration
credit BBB or lower is less capital efficient and
hedge funds also do not achieve a good return on
equity under the Standard Formula. In general, the
Standard Formula will encourage holding assets
classes that provide maximum yield for the capital
category they fall into: for example, within Other
Equity the most capital efficient assets will be risky
forms of private equity investments. While many
insurers are not expected to focus purely on capital
efficiency, it is likely to be a consideration that will
tilt the average insurance asset allocation away from
less capital efficient asset classes such as high yield
debt that feature low quality credit exposures.
Conclusion
Solvency II is driving non-life insurers to think
holistically about risk, capital, volatility and value
generation across insurance and investment. We
believe that bringing together the management of
insurance and investment risk through the Chief Risk
Officer provides a valuable opportunity for insurers to:
t *NQMFNFOUCFUUFSNBOBHFNFOUQSBDUJDFTCZWJFXJOH
risk and capital holistically across both insurance
and asset risk
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underwriting and investment more dynamically
throughout the underwriting cycle to provide a
more stable return to shareholders
There are many challenges for European insurers
during the transitional period to Solvency II and
beyond to the new international accounting
standards. To achieve attractive returns on equity
under the new capital regime for market risk,
significant changes to investment strategy will be
required to manage asset liability risk. Moving to an
economic view of the balance sheet has significant
implications for companies who report on an
undiscounted basis and careful communication with
senior management and investors is required to
carefully manage this transition.
Finally, in the current draft of the Standard Formula,
there are many areas of economic disconnect that
could have broader implications for the investment
market. Until the Standard Formula is finalised, it is
difficult to judge at what point insurers will start to
switch their portfolios, but it is important to be aware
of the potential market dislocations and consider how
to position your firm’s investment portfolio to
minimise the impact of the new regulatory framework.
15
Solvency II Revealed
Capital Relief Through Reinsurance
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Insurers do not necessarily have to choose between a reinsurance programme which
makes business sense and one which reduces capital requirements — even if the
company appears thinly capitalised under QIS 5. Non-proportional reinsurance often
provides the best solution for the business by removing frequency risk and tail risks at a
cost that makes economic sense. Under the Standard Formula significant capital relief
can be obtained for non-proportional reinsurance, making it an attractive solution from
both a business and capital perspective.
Introduction
Standard Formula risk mitigation techniques under
Solvency II have already become a hot topic for
actuaries, CROs and CFOs. For most companies,
regulatory capital requirements have historically played
a relatively small role in the decision to purchase a
particular reinsurance contract, where managing the
volatility of shareholder returns and economic and
rating agency capital requirements have typically had
the upper hand. However, QIS 5 indicated that
regulatory capital requirements under Solvency II are
likely to increase significantly for most non-life insurers.
Although unlikely to become the dominant factor in a
reinsurance purchasing decision, the impact of the
reinsurance on Solvency II capital should be explored.
In the Solvency II framework, an insurer can choose to
use the Standard Formula or its own internal model to
estimate its Solvency Capital Requirement (SCR). The
Standard Formula is a non entity-specific risk-based
formula designed by EIOPA, the European insurance
regulator. Alternatively, the undertaking can build an
internal model and submit it for approval by the
regulator to determine their SCR. For the vast majority
of companies the investment required to develop and
submit an internal model is too great and so a good
understanding of how the Standard Formula recognises
the risk mitigation effect of reinsurance is essential. This
case study uses the QIS 5 version of the Standard
Formula to estimate the impact of a specific reinsurance
structure on a notional company’s non-life
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16
The non-life underwriting risk module comprises three
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This case study considers the impact of the reinsurance
structure on both Premium Risk and Cat Risk which
must be calculated separately and then combined
together using a prescribed correlation coefficient.
Under the Standard Formula, the premium risk by class
of business is calculated as the product of a prescribed
underwriting volatility and the company’s premium
volume. For proportional reinsurance, such as quota
share, the capital relief can be easily determined by
multiplying by the ceded percentage. For nonproportional reinsurance, the capital saving effect is less
immediately apparent under Standard Formula.
However, as this case study will demonstrate, nonproportional reinsurance can offer significant capital
savings without requiring a partial or full internal model
to be developed.
Notional Insurer and Reinsurance Structure
The case study is based on a notional Swedish monoline company whose property portfolio has a premium
volume of EUR130m and is protected by existing risk
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attachment of a 12 year return period. The focus of the
study is the capital benefit of adding an aggregate
protection to the existing retention.
Since the company has existing risk and catastrophe
9-SFJOTVSBODFQSPUFDUJOHUIFJSQSPQFSUZCPPLGSPN
large individual and catastrophe claims, the additional
Aon Benfield
structure they are interested in purchasing is a risk and catastrophe aggregate reinsurance to provide more
sideways protection on their retention. With this new structure in place, the insurer is protected by the following
reinsurance contracts:
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&63NSFUFOUJPOPGUIFDBU9-XJUIBOJOEJWJEVBMMPTTFWFOUEFEVDUJCMFPG&63N
Table 1 shows the combined effect of these reinsurance protections for an example set of large individual claims:
Table 1: Combined effect of reinsurance protections
Gross Loss
Net of Risk XL
Loss below
Retention
Presented to
Aggregate
Recovery from
Aggregate
Overall Net
3JTL-PTT
30
10
10
9
0
10
3JTL-PTT
80
20
10
9
1.5
18.5
3JTL-PTT
40
10
10
9
9
1
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5
5
5
4
4
1
EURm
Source: Aon Benfield
Undertaking Specific Parameters
Under QIS 5, companies have the choice of two methods
to estimate the impact of non-proportional reinsurance
on their non-life insurance risk (on top of the effect of the
reduced premium volume) — both involve customisation
of the volatility factor.
The first approach is the Non-Proportional Adjustment
Factor for reinsurance. Most insurers failed to apply this
adjustment in their QIS5 submissions for a number of
reasons, including: (1) it can only be applied for standard
9-USFBUJFT‰TQFDJBMGFBUVSFTTVDIBTBOOVBMBHHSFHBUF
limits or deductibles are excluded, (2) the assumption
made by the adjustment calculation that individual large
loss severities follow a lognormal distribution may be of
questionable appropriateness giving results which are
hard to believe.
The second method is known as Undertaking Specific
Parameters (USPs). Non-life premium risk USPs allow
insurers to determine the volatilities to apply in the
premium risk calculation using their own historical losses
and one of three prescribed methods. The final premium
risk USPs are weighted averages of the insurer’s
calculation and the Standard Formula where the
credibility weights depend primarily on the number of
years of available data and the line of business. For
example, for property (fire) the weighting is 100% for 10
years or more of data.
To apply one of the USP methods, the historical losses are
first adjusted for elements such as inflation and then the
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annual losses on an as-if basis. After all of these
adjustments have been made, the volatility to use for the
premium risk calculation is derived. The appeal of this
method is that the impact of any reinsurance structure
can be taken into account. Also, in comparison with
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approval by the supervisors.
17
Solvency II Revealed
Historical Loss Data
Premium Risk Results
A credibility mechanism should be used when applying
USPs. The credibility factors to be applied should be
chosen according to the length of historical loss data. In
this case study of USP on the Premium Risk, USP Method
3 will be applied to 10 years of historical loss data from
the notional Swedish company.
By applying the reinsurance programme to the 10 years
of historical data, the USP method can estimate both
the gross and net volatilities as a percentage of gross
and net premiums respectively. Figure 1 shows the
average large loss for each year before and after the
reinsurance programme.
Figure 1: Effect of Reinsurance
5.5
5.0
4.5
Millions
4.0
B
3.5
3.0
2.5
2.0
1.5
1.0
2001
Gross
2002
2003
Net of XL
2004
2005
2006
2007
2008
2009
2010
Net of XL & AGG
Source: Aon Benfield
The volatility of the losses decreases significantly after the reinsurance programmes are applied.
Table 2 shows the premium volatility and premium SCR charges obtained from applying the USP method to the loss
EBUBOFUPGUIFFYJTUJOH9-BOEUPUIFMPTTEBUBOFUPGCPUIUIFFYJTUJOH9-BOEUIFBEEJUJPOBMBHHSFHBUFQSPUFDUJPO
Table 2: Premium Volatility and SCR Charges Using USP Method
ıUSP
1SFNJVN4$3&63
Net of XL
Net of XL & Agg
9.1%
8.5%
32
29
Source: Aon Benfield
Both of these volatilities are lower than the 10% prescribed for property (fire) premium risk under QIS 5. Since, in
this case, there is a property line with 10 years of data, a credibility weighting of 100% can be applied to the
insurer’s volatility calculation. The premium SCR decreases by approximately 9.5% due to the Aggregate Protection.
18
Aon Benfield
Cat Risk Model
Table 3: Two Hypothetical Years for Cat Scenario
Property catastrophe exposure in Sweden is purely
Natural Catastrophe of which 100% is windstorm. In
this case study the Catastrophe SCR is estimated based
on real company data using Cat Method 1 of QIS 5 for
this property exposure in Sweden. Using the Crestazone gross exposure data, the QIS 5 formula
determines the 1 in 200 year event loss for the peril.
To arrive at the 1 in 200 total peril loss (the CAT SCR)
(Table 5), the Standard Formula requires two
alternative hypothetical years to be created (Table 3).
This is first done on a gross basis and each is then
netted down for reinsurance, after which the maximum
net annual total of the two is taken (Table 4). For the
windstorm peril, the two hypothetical years are: 80%
BOEPGUIFJOZFBSFWFOUBOEBOE
20% of the 1 in 200 year event.
Cat Scenario (EURm)
1
2
(YHQW
72
89
&WFOU
36
18
Reinsurance (EURm)
XL
Agg
Attachment
15
16.5
Limit
75
20
Before Agg
After Agg
30
18.5
Table 4: The Cat Reinsurance
Table 5: The SCR Cat Results
&DW6&5(85P
Non-Life SCR Result
Figure 2 shows the result after the aggregation of the Cat risk and Premium risk by using the QIS 5 correlation matrix.
Figure 2: Aggregation of Cat and Premium Risks
49
50
38
40
30
32
30
19
20
Millions
29
10
0
-10
-9
-13
-20
CAT SCR
Before AGG
Premium SCR
Diversification
Non Life SCR
After AGG
Source: Aon Benfield
19
Solvency II Revealed
Since the aggregate contract protects both premium risk
and cat risk, some thought should be given to how the
aggregate deductibles and limits are shared between the
two risk categories. By applying the aggregate
conditions separately to the premium risk calculation
and cat risk calculation, as has been done in this study, a
conservative assumption has been made due to the
aggregate deductible being imposed twice. Conversely,
allowing for the full aggregate limit in both calculations
is an overly-generous assumption and therefore, a
further condition is imposed: the total reduction in SCR
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contract, in this case EUR20m. A reduction of only
&63NJTBDIJFWFEGPSUIF4$3/PO-JGFJOUIJTDBTFTP
no such cap is required.
Therefore the aggregate reinsurance programme
decreases the capital charge for Cat Risk by 38% and
Premium Risk charge by 9% under the USP method.
After diversification, the total Non-life SCR decreases by
22% from EUR49m to EUR38m.
Conclusion
This case study clearly demonstrates that, even for a
reinsurance contract that is structured primarily to
achieve very specific business benefits — such as the
sideways retention protection — the risk-mitigation
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significant even under the Standard Formula where it
may not be immediately apparent at first glance. As for
proportional reinsurance, non-proportional reinsurance
programmes with tailored characteristics can also
significantly reduce the Solvency II Non-life
underwriting SCR.
This is due to a combination of reduction effects
including the ability to fully recognise reinsurance in the
calculation of non-life catastrophe risk, as well as the
ability to capture the actual volatility of the company’s
net premium risk using the USP method.
For companies for whom Solvency II capital is a key
constraint, the reinsurance programme could be
designed from more of a capital management
perspective. This first requires a company to define its
risk appetite for insurance underwriting risk, upon which
an optimal reinsurance programme can be structured to
help the company to meet these objectives, whilst
achieving other desirable outcomes such as reducing
ceded profit and retained volatility.
Reinsurance has always been a valuable risk-mitigation
instrument. Different reinsurance programmes provide
different business and capital benefits, and this case study
demonstrates that the two can go hand in hand under
Solvency II without necessarily using an internal model.
20
Aon Benfield
Natural Catastrophe Capital
Requirement Under Solvency II
3FWFBMFE
A magnitude of difference can exist between the Standard Formula and an internal
model to calculate solvency capital for catastrophe risk. The discrepancies are revealed in
the case study which stresses the importance of making a strategic management
EFDJTJPOPOUIFDIPJDFPGNFUIPE3FHBSEMFTTPGNPEFM$BU9-SFJOTVSBODFSFNBJOTUIF
leading Cat risk mitigation tool and proves to be a cost effective source of capital, which
is now recognised by Solvency II.
Catastrophe risk is a key driver for capital under Solvency
II, with the benchmark to withstand a 1-in-200 year event
for natural and man-made disasters. There is a basic
calculation method that insurers can use to determine
their Solvency Capital Requirement. However the
methodology for the standardised scenarios for natural
catastrophe modelling overlooks key data features.
Standard Formula
As such, natural catastrophe (Nat Cat) calculations are
ignoring 15 years of critical evolution under the
currently proposed Solvency II Standard Formula,
which could lead to higher capital requirements for
insurers when the regulation comes into force. Insurers
need to choose between the Standard Formula and a
partial internal model to assign a more appropriate
capital charge. The article reveals the different
outcomes through a detailed case study.
Standard Formula parameters, such as damage factors
and correlations, as well as peril selection depending on a
country hazard profile, are based on the Catastrophe Task
Force (CTF) guidance. The CTF is a working group which
includes regulators, (re)insurance industry participants
and catastrophe modelling agencies. The Nat Cat
Standard Formula approach is currently under review after
some criticism following the QIS 5 industry exercise.
Figure 1: Process Options to Calculate Nat Cat SCR
Standardised scenarios are defined per European
country and peril. The Standard Formula approach is
designed to be applicable to the majority of companies
and will be a practical solution for smaller companies as
internal models can be costly and require a complex
regulatory approval process.
The factor-based method is used where standardised
scenario is unavailable or non-applicable, including:
t &YQPTVSFPVUTJEF&&"
NatCat SCR
t &YDFTTCVTJOFTT
Standard Formula
Method 1:
Standardised
Scenarios
Source: Aon Benfield
(Partial)
Internal Model
t *OXBSETOPOQSPQPSUJPOBMSFJOTVSBODF
Internal model
Method 2:
Factor based
Use of
Cat Models
Internal models based on catastrophe modelling software
output better reflect the risk profile of a company, which
is particularly critical in producing results that reflect the
company’s potential exposure to Nat Cat risk.
21
Solvency II Revealed
Table 1 outlines the differences between the data requirements and therefore data quality impacting risk sensitivity of the
possible approaches used in QIS 5 for the Nat Cat SCR.
Table 1: Impact of the Different Data Requirements for Nat Cat SCR
Parameters and metrics
Standardised scenario
Factor based
Internal model
(cat model)
Perils
8JOETUPSNJODM4UPSN4VSHF
&BSUIRVBLF'MPPE)BJM
Subsidence
8JOETUPSNJODM4UPSN4VSHF
&BSUIRVBLF'MPPE)BJM
8JOETUPSNJODM4UPSN4VSHF
&BSUIRVBLF'MPPE)BJM
7PMVNFNFBTVSF
(SPTT5PUBM*OTVSFE7BMVF
Gross Written Premium
%FUBJMFEFYQPTVSFQFSSJTL
5PUBMJOTVSBODF7BMVFT
EFEVDUJCMFTMJNJUTFUD
Geographic resolution
$3&45"
/PEJƅFSFOUJBUJPO
All levels of resolution
DPPSEJOBUFTUP$3&45"
Property coverage
OB
OB
#VJMEJOH$POUFOU#VTJOFTT
Interruption
Line of business split
'JSF.BSJOF"WJBUJPOBOE
5FSSPSJTN.PUPS1IZTJDBM
%BNBHF
OB
%FUBJMFEPDDVQBODJFT
$POTUSVDUJPO
OB
OB
%FUBJMFEDPOTUSVDUJPO
0UIFSDIBSBDUFSJTUJDT
OB
OB
/VNCFSPGTUPSJFTZFBSCVJMUBOE
other secondary characteristics
$PSSFMBUJPOT
t -0#TDPSSFMBUFE
*OEFQFOEFOU1FSJM&WFOUT
$PSSFMBUJPOTBUBMMMFWFMT
Single event
.PEFMMFETDFOBSJPT
7B3BUBOOVBM
7B3BUBOOVBM
t $3&45"DPSSFMBUJPOT
t 1FSJMDPSSFMBUJPOT
Loss scenario
t FWFOUTDFOBSJPTGPS8JOE
'MPPEBOE)BJM
t 4JOHMFFWFOUGPS&BSUIRVBLF
and Subsidence
Loss calibration
7B3BUBOOVBM
Source: Aon Benfield
Due to significant differences in data granularity between Standard Formula and partial internal model, the output
SCR will inevitably differ, with the former yielding a higher SCR in the majority of cases. Therefore companies will
base their choice of method on the approach which provides the more accurate representation of their risk in their
view. Significantly, an internal model offers several risk management applications in addition to the calculation of a
Solvency II SCR, and provides the opportunity to fully recognise the benefit of complex mitigation structures.
22
Aon Benfield
Natural Catastrophe Reinsurance
Under Solvency II
Both proportional and non-proportional reinsurance
are reasonably taken into account as mitigation
methods under QIS 5.
The QIS 5 technical specifications do not prescribe a
specific method to apply reinsurance to the proposed Nat
Cat scenarios, because a single method is unlikely to be
appropriate for all reinsurance programmes. Instead
companies are asked to apply their reinsurance
programme using an appropriate methodology which is
then explained to the regulator. Since most internal
models fully capture the details of reinsurance
programmes, they should provide a more accurate picture
of the company’s net position at a 1 in 200 year level.
Case study
We examine below the differences between Standard
Formula and internal model for a UK company writing
property business.
The reinsurance protection in place (proportional
SFJOTVSBODFJOVSFTUPUIFCFOFmUPG$BU9-
JTBTGPMMPXT
1) Surplus share one with occurrence limit GBP80m
4VSQMVTTIBSFUXPXJUIPDDVSSFODFMJNJU(#1N
'BDVMUBUJWFPCMJHBUPSZXJUIPDDVSSFODFMJNJU(1#N
$BU9-(1#NYT(1#NNYTNNYT
NNYTN
XJUIFBDIMBZFSSFJOTUBUFNFOU
@ 100%
The Standard Formula suggests that companies assume
two events for windstorm, flood and hail, which are
composed in such a way to test the adequacy of
reinsurance protection: a combination of a large and
small event for vertical cover, and two smaller events
for horizontal protection. This allows the Standard
'PSNVMBUPBDLOPXMFEHFUIFCFOFmUPG$BU9-
programmes with a reinstatement by providing capital
relief from the second limit. Internal models will of
course recognise all reinstatements.
23
Solvency II Revealed
All types of reinsurance in this case are adequately recognised by both the Standard Formula and internal model.
The steps for calculating Nat Cat SCR are described in Table 2:
Table 2: Process for Applying Reinsurance
Steps
Standardised scenario
Internal model
/BU$BU-PTT&TUJNBUFBUJOZS
(SPTTZS1.-QFS0DDVSSFODFCBTFEPO
QSFEFmOFETUBOEBSEEBNBHFGBDUPSTQFS1FSJM
$PVOUSZ$3&45"BQQMJFEUP5PUBM4VN*OTVSFE
$BUBTUSPQIFNPEFMMJOHBOBMZTJTPOBWBJMBCMFEBUB
(SPTT/BU$BU4$3
t 8JOEPGZS1.-QFSPDDVSSFODF
t ZS.PEFMMFE"OOVBM"HHSFHBUF-PTTQFSQFSJM
t 'MPPEPGZS1.-QFSPDDVSSFODF
ZS.PEFMMFE"OOVBM"HHSFHBUF-PTTBMMQFSJMT
combined
5PUBM(SPTT4$3BMMQFSJMTDPNCJOFE
DPSSFMBUJPOCFUXFFO8JOEBOE'MPPE
.JUJHBUJPO
"QQMZJOHSFJOTVSBODFTUSVDUVSFUISPVHIUXPFWFOU
TDFOBSJPTDPOTJEFSJOHSFJOTUBUFNFOUQSFNJVNT
.PEFMMFESFJOTVSBODFTUSVDUVSF
t FWFOUTDFOBSJPTGPS8JOE
‰ TUTDFOBSJPTUFWFOU‰
OEFWFOU‰PGZS1. ‰ OETDFOBSJPTUFWFOU‰
OEFWFOU‰PGZS1.t FWFOUTDFOBSJPTGPS'MPPE
‰ TUTDFOBSJPTUFWFOU‰
OEFWFOU‰PGZS1. ‰ OETDFOBSJPTUFWFOU‰
OEFWFOU‰PGZS1.-
/FU/BU$BU4$3
&RVBMUPNBYJNVNPGUXPTDFOBSJPTOFUBHHSFHBUF
loss per peril
5PUBM/FU4$3DPNCJOFEDPSSFMBUJPOCFUXFFO
8JOEBOE'MPPE
Source: Aon Benfield
24
ZS.PEFMMFE/FUBGUFS$"5"OOVBM"HHSFHBUF
Loss for all perils correlated
Aon Benfield
Table 3 compares Nat Cat SCR using the Standard Formula and internal model for the case study example.
Table 3: Nat Cat SCR Comparisons Between the Standard Formula and Internal Model
GBPm
Standard formula
Internal model
Wind + Surge
3JWFS'MPPE
Wind + Surge
3JWFS'MPPE
ZS(SPTT0DDVSSFODF1.-
340.90
185.41
243.40
153.03
(SPTT4$3QFSQFSJM
409.08
203.95
261.45
164.51
500.65
(SPTT4$3BMMQFSJMTDPNCJOFE
304.78
.JUJHBUJPOQFSQFSJM
SS 1
107.02
76.74
75.41
54.86
SS 2
58.11
32.17
35.60
29.74
'BD0CMJH
7.27
3.37
4.09
3.48
24
7.10
2.75
3.40
2.30
$BU9-
148.37
54.09
119.70
5PUBMNJUJHBUJPO
327.87
169.12
328.59
/FU4$3
81.21
34.83
57.04
/FU4$3BMMQFSJMTDPNCJOFE
96.04
57.04
adjustment **
+14.58
0.00
Source: Aon Benfield
** In the Standard Formula, there is a risk of double
DPVOUJOHSFJOTVSBODFSFDPWFSJFTQSPEVDFECZB$BU9-
5IJTEFSJWFTGSPNUIF$BU9-NJUJHBUJPODBMDVMBUJPO
being separate per peril and then correlating the net
results. Correlation mitigates double counting to some
FYUFOUIPXFWFSJUJTQPTTJCMFUPPWFSFTUJNBUF
reinsurance recoveries, especially on lower layers in the
case of exposure to multiple perils. In our case the
mitigation effect of the bottom layer exceeded the total
limit available by GBP14.58m after combining perils
with the effect of correlation.
This case study illustrates the magnitude of difference
that can exist between solvency capital calculated using
the Standard Formula and an internal model. If, as in this
case study, the company chooses the Standard Formula
route, it will need to maintain 94% more Nat Cat capital
to meet the SII requirement than if it uses a partial
internal model. This difference originates from the gross
DBQJUBMQPTJUJPOBUUIFTUBHFPGUIFPSJHJOBM$BU1.-
calculation. This might hint at a calibration issue with the
Standard Formula. However, the Standard Formula gives
higher capital relief due to the two-event scenarios, and
allows recoveries from reinstatements.
25
Solvency II Revealed
Figure 5: Comparison of Nat Cat SCR Using
Standard Formula and Internal Model
5IFJNQBDUPODBQJUBMBOEUIFFGmDJFODZPG$BU9-
reinsurance is assessed using CatMetrica, a template
developed in ReMetrica. In addition to capital relief,
CatMetrica provides measures of efficiency of
reinsurance such as the Ceded RoE (calculated in this
example as the ratio of reinsurance margin to capital
relief before diversification). In Table 4, CatMetrica
TIPXTUIBUUIF$BU9-QSPHSBNNFSFMFBTFTPG
capital at a Ceded RoE of 4.94% under an internal
model. Under the Standard Formula, the capital relief
for this programme is 60% at a ceded RoE of 3.59%.
500
400
300
200
100
0
-100
-200
Gross SCR
Standard formula
Conclusion
Net SCR
Internal model
As demonstrated, reinsurance is a competitively priced
source of capital, which is expected to have full
recognition under the Solvency II regime.
Difference
Source: Aon Benfield
Table 4: CatMetrica Reinsurance Evaluation
Premium
Expected
Recovery
Total
1@100%, 100% placed
0.6
0WFSUIF1SPHSBNNF
NYTN
Reinsurer
Reinsurer St Dev of
Margin to
Margin Recoveries
Std. Dev.
2.3
0.6
1.8
3.33%
0.82%
2.51%
3.4
1.3
2.1
6.77%
2.65%
4.12%
NYTN
4.3
17.39%
2.3
9.01%
2.1
8.37%
1@100%, 100% placed
Ceded
ROE
Capital
Benefit
Ceded
ROE
B
C
B
C
B
C
0.49%
3.78%
67.7
2.60%
7.3
28.36%
2.55
4.79%
1.39%
0.07%
0.01%
41.7
4.93%
50.9
4.04%
6.7
31.31%
1.93
15.90%
4.93%
0.83%
0.13%
31.4
6.67%
46.0
4.55%
16.8
176.7
35.15%
2.42
15.90%
0.49%
0.83%
0.00%
119.7
275.2
4.94%
164.6
11.2
15.2
57.0
110.6
Source: Aon Benfield
*Expected reinsurance recoveries are based on catastrophe model output.
26
Capital
Benefit
46.6
28.3
3FJOTVSBODF*NQBDU
2nd Limit
0.01%
0.00%
15.4
/FU
1st Limit
1.37%
0.49%
/FU1SF$BU
5.9
SII Standard
Formula (QIS 5)
4.08
8.8
4.2
Economic Capital
at 200 yr
30.53%
10.7
10.1
C
Probability of
Attach/Exhaust
5.8
3FUFOUJPO
$FEFE
B
11.7
1@100%, 100% placed
NYTN
Premium
Multiple
3.59%
Aon Benfield
Boosting Knowledge of
-JGF$BUBTUSPQIF3JTL
3FWFBMFE
Pandemic and terrorism risks incur the largest catastrophe capital charges under
4PMWFODZ**5PHBJOBCFUUFSVOEFSTUBOEJOHPG-JGFJOTVSFSTFYQPTVSFTBOJNQPSUBOU
requirement of Solvency II, catastrophe models are evolving. Impact Forecasting’s UK
terrorism model incorporates input from counter terrorism experts on elements such as
credible attack types and damage profiles. In addition, the average cost of a catastrophe
9-JTBSPVOE30-BOEIFODFSFNBJOTBDPTUFGGFDUJWFNFUIPEUPNJUJHBUFFYUSFNF
mortality events other than pandemic.
Introduction
Pandemic risk
6OEFS2*4-JGFJOTVSBODFDPNQBOJFTBSFSFRVJSFEUP
hold capital for the impact of 1 in 200 year extreme
mortality events. To grasp what this definition means,
in essence, this translates to not only considering one
specific scenario with the probability of 0.5%, but
thinking of holding enough capital to withstand the
cost of extreme events at the 99.5th percentile and
therefore consider multiple tail events. Such events
include, but are not limited to, pandemics, terrorist
attacks and natural catastrophes. The extent to which a
company is exposed to catastrophe risk depends on
various features of the underlying portfolio such as
demographic profile, geographical location and
product types.
Pandemic risk has many different definitions but the
common feature is the spread of infectious disease across
a large geographic region. The three major pandemic
influenzas in the last 100 years, namely the Spanish
"TJBO
BOE)POH,POHJOnVFO[BT
caused over 50 million of deaths in total. The latest
pandemic recognised by the WHO was the 2009 H1N1
which, although generating widespread public concern,
was not as lethal as feared. In fact, with a reported death
toll of less than 20,000 cases, it fell far short of WHO’s
expectation of 250,000-500,000 annual deaths arising
from seasonal influenza.
*OUIF6,PUIFSUIBO(SPVQ-JGFJOTVSFSTQBOEFNJD
SJTLBDDPVOUTGPSUIFNBKPSJUZPG-JGFDBUBTUSPQIFSJTL
followed by a much smaller share of terrorism risk.
Impact Forecasting, Aon Benfield’s model development
centre of excellence, has created models for pandemic,
UFSSPSJTNBOEFBSUIRVBLFSJTLTGPS-JGFCVTJOFTTFT
however the article focuses on pandemic and terrorism
risks as these incur the largest catastrophe capital
charge of a combined 90%.
In the QIS5 technical specification, the Standard Formula
SFRVJSFT-JGFJOTVSFSTUPIPMEDBQJUBMGPSUIFJNQBDUPG
additional deaths at 1.5 per thousand lives insured. A
case study will demonstrate how an internal model can
SFTVMUJOBMPXFSDBQJUBMSFRVJSFNFOUGPS-JGF$"5SJTLUIBO
the standard formula.
The impact of Spanish flu, if the history was to repeat
itself on today’s insured portfolio, has the potential to
threaten the survival of many otherwise well capitalised
insurers. Many may argue that an exact repeat of a
Spanish flu is unlikely due to lessons learnt from the past
such as the use of quarantine to contain the spread of
EJTFBTFTUPDLQJMJOHPGBOUJWJSBMESVHTNFEJDBM
BEWBODFNFOUFOBCMJOHGBTUFSMBCPSBUPSZUFTUTEJBHOPTJT
GPSNVMBUJPOPGWBDDJOBUJPOTUFDIOPMPHJDBMBEWBODFNFOU
facilitating rapid and effective communication of disease
VQEBUFTJNQSPWFEIZHJFOFTUBOEBSEWBDDJOBUJPOBOE
better access to medical assistance.
On the other hand, some may argue the prevalence of
international travelling, urbanisation and increased
population density in city centres provide a favourable
environment for the spread of infectious disease. In
addition to the changing landscape, we are constantly
under the threat of emerging pandemics with mutation
of pathogens or resurgence of past virus strains. The
outbreak of E-coli in Germany in 2011 had the world
XBUDIJOHUIFEFWFMPQNFOUPGUIJTEJTFBTFMVDLJMZUIF
situation was quickly contained. It is not a matter of if, but
when, the next major pandemic will strike.
27
Solvency II Revealed
Š
Figure 1: SIR Model
Š
Susceptible
Latent
Š Š
Š
Infectious
Hospitalized
Asymptomatic
Recovered
Dead
Source: Aon Benfield
Figure 2: W-shaped Excess Mortality
Flu Mortality
(per 100,000 population)
3000
1913-1917
1918
2500
2000
1500
1000
500
0
<1
1-4
5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84
Age (years)
Source: -VLFUBM$*%
28
>84
Figure 3: U-shaped Excess Mortality
1000
Flu Mortality
(per 100,000 population)
In order to understand the impact of pandemic risk on
insurers’ portfolios, Aon Benfield has developed an
influenza pandemic model based on the SusceptibleInfectious-Recovered (SIR) methodology, commonly
used by epidemiologists to model transmission of
infectious diseases. The model accounts for the
transition of healthy population (Susceptible) coming
into contact with the disease, developing symptoms,
requiring hospitalisation, recovering from illness or
dying. In turn this enables monitoring of: the
cumulative number of people becoming ill, admitted
JOUPIPTQJUBMPSEJFEEZJOHBTBSFTVMUPGBQBOEFNJD
with a given insured portfolio. As population density
JOnVFODFTUIFTQFFEBUXIJDIUIFWJSVTJTTQSFBEWJSVT
transmission rate is therefore adjusted. For each
simulation, three different mortality profiles (W-shaped
in Figure 2, U-shaped in Figure 3 and uniform
distribution) are considered, hence producing three
different estimates.
1952-1956
1957
800
600
400
200
0
<1
1-4
5-14 15-24 25-34 35-44 45-54 55-64 65-74 75-84
>84
Age (years)
4PVSDF-VLFUBM$*%
A probabilistic approach allows the financial impact to
be analysed by different return periods to form the
basis of reinsurance optimisation strategy. Standard
catastrophe cover is designed to remediate the tail risk
of portfolio but does not provide appropriate
protection against pandemic risk. This is mostly
because the “hours clause” attached to a catastrophe
DPWFSSFTUSJDUTEBNBHFTJODVSSFEUPBQFSJPEPG
hours. However, based on what has been observed in
the past, the full force of a pandemic can last for
months if not years. For this reason, the industry has
developed a range of specialist solutions including
traditional stop loss cover, pandemic reinsurance and
pandemic bond in the capital market.
At the height of H1N1 pandemic, some reinsurers
were quoting pandemic cover in excess of 10% rate
on line, which was prohibitively expensive. However,
in today’s market, without the over sensationalised
threat of pandemic, prices are more competitive and
below the cost of internal capital for insurers. Similar
UPCVZJOH-JGFJOTVSBODFCFGPSFEFWFMPQJOHBOZ
excluded medical conditions, pandemic risk
management is best considered at a time without
immediate major threat.
Aon Benfield
Terrorism risk
Terrorism has become an increasingly recognised risk
factor over the last two decades. In the wake of the
UFSSPSBUUBDLXIFSFBQQSPYJNBUFMZMJWFT
XFSFMPTUBOEUIFJOTVSFEMPTTFTUP-JGFJOTVSFST
XFSFFTUJNBUFEBU64%CO3PCFSU1)BSUXJH
IUUQXXXHMPCBMSFTFBSDIDBBSUJDMFT)"3"IUNM
Exhibit 2), insurers took a large hit on their balance
sheets but most survived by risk spreading through
SFJOTVSBODFSFUSPDFTTJPO4JODFUIFONPTUJOTVSFST
have focused more on their management of
concentration risk.
Terrorism is a major catastrophe risk event for Group
business providers, especially if their portfolios have
concentrated exposure in high risk areas. Similar to
other catastrophe events, terrorism is difficult to
predict when and where it will next strike. However,
the act of terror is usually carried out to maximise
DBTVBMUZQVCMJDJUZFDPOPNJDEBNBHFXIJDIFYQMBJOT
why the World Trade Centre and the Pentagon were
DIPTFOBTUIFUBSHFUTJOTUFBEPGTVCVSCBOBSFBT
In determining the exposure to terrorism risk, Aon
Benfield has drawn on the knowledge and experience
of Aon’s counter terrorism experts to develop a
Figure 4: Heat Map of Terrorism Risk Exposure
probabilistic terrorism model. Firstly, a list of potential
terrorism targets is identified, along with different types
of attacks ranging from nuclear devices to a shooting
rampage of a single gunman. For each type of attack,
UIFMJLFMZJNQBDUSBEJVTBOEDBTVBMUJFTGBUBMJUJFTJOUIF
hit zone is analysed. The probability of occurrence for
each attack or weapon type is also assigned.
Another major piece of the puzzle is in determining
the frequency of terrorist attacks. Historical records
have shown that attack frequency has increased over
UIFMBTUGFXEFDBEFTUIFSFGPSFFYQFSUPQJOJPOJTSFMJFE
upon in this rapidly changing environment with
reference to a range of frequencies indicated by the
Impact Forecasting database. As the model has been
calibrated at postcode level, client exposure is
illustrated by postcode to evaluate terrorism risk at
various return periods. The terrorism model is helping
insurers to better understand their exposure of
terrorism risk and possible financial impact. In
addition it can be adopted b as an integral part of an
internal capital model and as an enterprise risk
management (ERM) tool to negotiate optimal
reinsurance terms and demonstrate their ERM
strength to rating agencies.
Attack in the
City of London
Attack at
Canary Wharf
Concentric
Distance
from Impact
t (FPTQBUJBMNBQT
(exposure) for client data
t 3FQSFTFOUBUJWFQPSUGPMJP
JO$FOUSBM-POEPO
t &YQPTVSFIFBUNBQ
overlaid with two
possible event attacks.
Source: Impact Forecasting
29
Solvency II Revealed
Case study
To highlight the benefits of pandemic modelling to
TVQQPSUSFJOTVSBODFCVZJOHBIZQPUIFUJDBM-POEPO
QPSUGPMJPPG-FWFM5FSN"TTVSBODF-5"
JTFYBNJOFEJO
Table 1:
Table 1: Hypothetical LTA Portfolio
Age Group
Lives insured
Sum Insured
35-44
20,000
£3,000,000,000
bQFSMJWF
45-54
20,000
£4,000,000,000
bQFSMJWF
Total
40,000
For this portfolio, the models suggest that the 1 in 200
year influenza pandemic loss is GBP8.3m and terrorism
cost is GBP6.2m. The pandemic and terrorism events are
assumed independent of one another i.e. zero correlation.
6TJOHUIFBHHSFHBUJPONFUIPEBTQFS4$3PGUIF2*4
Technical Specifications, the combined 1 in 200 year
catastrophe loss will be GBP10.4m (=SQRT(8.3^2+6.2^2)),
which is consistent with the capital requirement under the
Standard Formula approach.
Table 2: Modelled Pandemic Losses in London
Pandemic PML Points
(£000)
Return Period
Modelled Losses
400
10,742
200
8,316
100
5,643
50
1,980
Average Annual Loss
144
£7,000,000,000
Source: Aon Benfield
Based on the Solvency II Standard Formula, the
-JGF$"5SFRVJSFNFOUDBOCFDBMDVMBUFEBUPG
the portfolio Sum at Risk (SAR). For the age profile of
this particular portfolio, best estimate reserve is
SPVHIMZPGUIFTVNJOTVSFE5IF-JGF$"52*4
capital requirement is therefore calculated at
GBP10.4million.
Source: Aon Benfield
Table 3: Modelled Terrorism Losses in London
Terrorism PML Points
(£000)
Return Period
Modelled Losses
400
14,347
200
6,193
Assuming lives insured are evenly distributed across
-POEPOQPTUDPEFTBOEBDSPTTBHFCBOETNPSUBMJUZ
cost is expected to be GBP10.3million for the next 12
months (based on TMC00 table).
100
4,774
50
2,016
Average Annual Loss
1,131
Source: Aon Benfield
Figure 5: PML of Pandemic losses in London
2.5%
Exceeded Probability
2.0%
1.5%
B
1.0%
0.5%
0.0%
2,000
4,000
6,000
8,000
Modelled Losses (£000)
Source: Aon Benfield
30
10,000
12,000
14,000
16,000
Aon Benfield
t "UUBDINFOUQPJOUBUPGFYQFDUFEBOOVBM
mortality loss
t -JNJUQSPWJEJOHDPWFSVQUPPGFYQFDUFEBOOVBM
mortality loss i.e. 90% excess 110%
t 3BUFPO-JOF30-
BUSPVHIMZ
This results in a pandemic cover with an attachment
QPJOUBU(#1NBOEBMJNJUPG(#1NBUBDPTU
PG(#1NUIFDPWFSEVSBUJPOJTBTTVNFEBUPOF
year for this example). The loss retained by the cedant
before the pandemic cover is triggered is GBP1m so
UIF-JGF$"5SFRVJSFNFOUXJMMCFDPNF(#1N
(=SQRT(1^2+6.2^2)) resulting in a capital saving
ofGBP4.1m compared to no pandemic cover.
5IFDFEFE3P&JT
XIJDIDPNQBSFT
favourably to an average cost of capital of 10% to
11%. Ceded RoE is the cost of reinsurance divided by
capital relief from buying reinsurance. Accretive risk
transfer implies that ceded RoE is less than internal
cost of capital.
Assuming the same portfolio of lives insured is in
&EJOCVSHIJOTUFBEPG-POEPOUIFJOZFBSMPTT
CFDPNFT(#1NGPSJOnVFO[BQBOEFNJDBOE(#1N
GPSUFSSPSJTUBUUBDL5IF-JGF$"5SFRVJSFNFOUJTUIFSFGPSF
(#1NCFGPSFBOZSFJOTVSBODFQSPHSBN5IFMPTT
arising from a terrorist attack is significantly less in
&EJOCVSHIBTUIFSFBSFMFTTUBSHFUTDPNQBSFEUP-POEPO
If the Edinburgh portfolio has the same cost,
attachment point and limit for the pandemic cover as
UIF-POEPOQPSUGPMJPUIF-JGF$"5SFRVJSFNFOU
becomes GBP1.6m (=SQRT(1^2+1.2^2)) with a capital
TBWJOHPG(#1N8JUIBDFEFE3P&PG
it is clear, for this particular example, that pandemic
reinsurance is a cost effective risk mitigation solution
compared to holding capital.
Table 4: Summary of London and Edinburgh Portfolios
London
Edinburgh
-JGF$"5
10.4
7.7
-JGF$"5BGUFSQBOEFNJDDPWFS
6.3
1.6
$BQJUBMTBWFE
4.1
6.1
$PTUPG1BOEFNJDDPWFS
0.37
0.37
$PTU$BQJUBMTBWFE
9%
6%
Source: Aon Benfield
Figure 6: Illustration of Pandemic cover
25
200% of annual
mortality loss
20
Losses (£millions)
A typical structure of pandemic cover is considered
with the following features:
Limit £9.27m
15
Buffer
10
5
Attachment point
(110% of annual
mortality loss)
Expected annual mortality loss
£10.3m
0
Source: Aon Benfield
Terrorism risk can also be mitigated through
$BUBTUSPQIF&YDFTTPG-PTT$BU9-
DPWFS"PO
Benfield’s Global Death and Disability catastrophe
benchmarking study examines the catastrophe
reinsurance purchasing pattern between countries. The
TUVEZTIPXTUIBUUIFBWFSBHFDPTUPGBDBUBTUSPQIF9-
JTBSPVOE30-"MUIPVHIUIFDPNQFUJUJWFQSJDJOH
PGDBUBTUSPQIF9-SFJOTVSBODFEFQFOETPOBWBSJFUZPG
factors such as attachment point and the relative risk
BTTPDJBUFEXJUIUIFQPSUGPMJPDBUBTUSPQIF9-SFNBJOT
a very cost effective method to mitigate extreme
mortality events other than pandemic. In addition,
the cost of ceding the catastrophe risk to reinsurers
is well below the internal cost of capital of insurers.
Conclusion
Despite the relatively small capital requirement on
average for life cat risk in the overall SCR, reinsuring
life catastrophe risk with effective terms and conditions
is a very cost efficient tool to achieve a reduction.
31
Solvency II Revealed
Rating Agencies and Solvency II
3FWFBMFE
Ratings agencies are unlikely to change their core ratings processes, including capital
requirements and risk management expectations, as a result of Solvency II. However, the
new regulation will change how companies think about risk. Insurers that can demonstrate
an effective internal modelling process are likely to be at an advantage and may achieve
favourable capital adjustments under the rating agency models over time. This could
mean a reduction in the required capital needed to support their existing rating.
Rating agencies are just as focused on Solvency II as regulators and regulated companies. However, a rating looks
beyond a simple quantification of solvency (Table 1), considering ongoing financial performance, viability of
management and strategy, and other operating issues that support capital growth and sustainability over time.
Solvency II will significantly increase the prominence of regulatory capital but, ultimately, companies that wish to
maintain a strong rating and compete in the global marketplace will need to keep a focus on ratings and the
underlying capital considerations, beyond those of Solvency II.
Table 1: Drivers to Solvency II Versus Those of a Rating
Solvency II
".#FTU
Standard & Poor’s*
$BQJUBMNFBTVSFNFOU
$BQJUBMNFBTVSFNFOU
$BQJUBMNFBTVSFNFOU
4VQFSWJTPSZSFWJFX034"
#BMBODFTIFFUTUSFOHUIBOEUSFOET
0QFSBUJOHQFSGPSNBODF
%JTDMPTVSFSFRVJSFNFOUT
0QFSBUJOHQFSGPSNBODF
$PNQFUJUJWFQPTJUJPO
#VTJOFTTPWFSWJFX
.BOBHFNFOUBOETUSBUFHZ
&3.
&3.
*OEVTUSZTFDUPSDPOTJEFSBUJPOT
Investments
-JRVJEJUZ
'JOBODJBMGMFYJCJMJUZ
*OEVTUSZ4FDUPSDPOTJEFSBUJPOT
Source: Aon Benfield
*In Standard & Poor’s ratings rationale an opinion of strength is provided for each of the first seven areas listed
Capital Implications
With the implementation date for Solvency II
approaching and results from QIS 5 published, rating
agencies believe Solvency II will have a significant capital
impact on the insurance industry.
on the QIS 5 results, this would lead to a further 8% of
participants unable to meet their solvency target. S&P
stated that its overall concern is that approximately one
quarter of European insurers will see their capital position
challenged under Solvency II.
Standard and Poor’s (S&P) report entitled Solvency II
*NQMFNFOUBUJPO-PPNTCVU&VSPQFBO*OTVSFST4UJMM'BDF
Uncertainty after Fifth Quantitative Impact Study
published in April 2011 states that insurers are likely to
maintain a material buffer of 20% above the SCR. Based
With the macro-economic uncertainty and softening
underwriting cycle, risk-mitigation has become
increasingly important. Insurers will need to rationalise
the link between risk tolerance, capacity and reward in
order to enhance business strategy.
32
Aon Benfield
Fitch states in its June 2011 report, Solvency II Set to Reshape Asset Allocation and Capital Markets, that insurers will
make significant changes to asset portfolios in order to enhance their capital position. Fitch anticipates a shift from
long-term to shorter-term debt and a migration towards higher-rated corporate debt and government bonds.
Ultimately, insurers would consider adopting lower risk investment policies in order to reduce their exposure to
volatile assets.
Table 2: Selected Differences in Capital Quantification
Solvency II — Standard Formula
S&P Risk Based Capital Model
".#FTU#$"3
"QQSPYo
"QQSPYo
$SFEJU3JTL
Tier 1 and Tier 2 considerations
Largely factor-based
.BSLFU3JTL
Largely factor-based
Largely factor-based
$BUBTUSPQIF3JTL
DBMJCSBUFE
peril-based scenarios
%JWFSTJmDBUJPO$SFEJU
$BU3FJOTVSBODF
#BTFEPODPNQBOZSFQPSUFE
PDDVSSFODF1.-THSFBUFSPG
XJOEPSFBSUIRVBLF
#BTFEPODPNQBOZSFQPSUFE
BHHSFHBUF1.-‰BMMQFSJMT
$SFEJUVQUPUIF1.-SFQPSUFEPƅTFUXJUIBEEJUJPOBMDSFEJUSJTL
Source: Aon Benfield
Transitional Arrangements
Proposed legislation project Omnibus II that will amend
the original Solvency II directive will potentially reduce
the risk of insurers being unable to meet capital
requirements in the short term.
Omnibus II outlines maximum transition periods of
between 5 and 10 years for key aspects of Solvency II,
such as meeting the full SCR and the treatment of
hybrid instruments in solvency measures.
In its March 2011 report entitled Weighing Solvency II’s
Impact on A.M. Best’s Ratings, the firm explains that
due to the transitional measures, the level of market
disruption will be much less than if Solvency II was
enforced in its entirety from the start date. Insurers are
no longer at risk of having their market position
abruptly challenged with fast-approaching deadlines,
and transitional periods allow insurers a settling-in
period for when Solvency II is put into operation.
The proposed transitional periods may shift focus away
from the quantitative capital impact that the regulation
brings to the detailed, non-capital related specifics of
the implementation. However, there is still debate on
the ultimate content and outcome of the final terms of
Omnibus II. Regulators must agree to the proposals
and, if there is significant deviation from these then
rating agencies may have new concerns for insurers
with which to contend.
Future Rating Agency Capital
Model Considerations
S&P and A.M. Best are the two ratings agencies with
established capital models. Neither agency has
suggested that their respective models will be changed
in light of Solvency II. However, both have stated that
considerations for a company’s internal modelling
process will be taken into account when assessing
capital management and risk management.
*O+BOVBSZ41JOUIFJSSFQPSU"/FX-FWFMPG
ERM Analysis: Methodology for Assessing Insurers’
Economic Capital Models, confirmed it was refining its
methodology for assessing an insurer’s Economic
$BQJUBM.PEFM&$.
41UFSNFEUIFQSPDFTTJUT-FWFM
3 review, which is the next stage of its ERM focus. The
review will concentrate on the quantitative and
qualitative modelling considerations and specific risks
that an insurer embeds into its ECM framework.
41XJMMDPOEVDUGVMM-FWFMSFWJFXTJOUPJOTVSFSTUIBU
meet certain criteria. An insurer must have an existing
ECM which is incorporated into its decision making
process and which is sufficiently documented, in order
for the analysis to take place. It is also likely that only
insurers with ‘excellent’ or ‘strong’ ERM after
VOEFSHPJOHUIF-FWFMSFWJFXXJMMCFDBOEJEBUFTGPSB
GVMM-FWFMSFWJFX
33
Solvency II Revealed
41DPNNFOUUIBUJUEPFTOPUFYQFDUUIF-FWFM
review to have a significant impact on ratings. However
the review can highlight risk management issues and
also demonstrate whether the ECM adequately
quantifies risks. This in turn can impact ERM and capital
conclusions, as well as the assessment of an insurer’s
management and strategy.
.BOZBTQFDUTPGUIF-FWFMSFWJFXSFnFDUXIBUJT
expected for those undergoing an internal model
approval for Solvency II, including the following:
t %FNPOTUSBUJPOPGJOUFSOBMVTF
t .FUIPEPMPHZBSPVOEUIFNPEFM
t %PDVNFOUBUJPO
t %BUBRVBMJUZ
t " TTVNQUJPOTBOEQBSBNFUFSJTBUJPOSBUJPOBMFBOE
application
t 5FTUJOHBOEWBMJEBUJPOPGUIFNPEFMBOEJUTSFTVMUT
t (PWFSOBODFBOETUBOEBSETTVSSPVOEJOHUIF
modelling process
"OJOTVSFSXIPIBTVOEFSUBLFOB-FWFMSFWJFXBOE
who can demonstrate a proficient Economic Capital
Modelling process, is at an advantage over those who
have not. Notably, those insurers whose internal capital
modelling processes are viewed by S&P to be credible
may achieve favourable capital adjustments within
S&P’s proprietary model up to one ratings category.
This could mean reduction in the required capital
needed to support their current rating. The question
remains whether rating agency capital will remain more
important than regulatory capital once Solvency II is
effective? This is likely, but time will tell.
34
Aon Benfield
Reinsurance Assets: Individual vs.
Aggregate Valuation Methods
3FWFBMFE
Solvency II offers opportunities to include the effect of risk mitigation techniques in
regulatory capital calculations and will likely generate new reinsurance techniques that fit
within the Standard Formula. However a key step is accounting for the impact of historical
risk mitigation and ensuring the true value of past investment is reflected in available
capital. Insurers should look deeper into the merits of calculating the fair value of their
reinsurance assets, as there may be an opportunity to unlock greater value than expected.
Introduction
Case study
Reinsurance assets are one of the most complicated to
calculate within the Solvency II Fair Value Balance sheet.
Nevertheless, if the reinsurance bought is material,
correct calculations can have an important impact on
the Net Available Assets. The complexity of past and
present reinsurance programmes creates challenges to
actuaries to deliver accurate estimates. The Solvency II
directive has recognised the importance of a correct
calculation of reinsurance assets by requiring a separate
calculation for the gross best estimate claim provisions
and the amounts recoverable from reinsurance
DPOUSBDUTBOE4QFDJBM1VSQPTF7FIJDMFT"SUJDMF
The case study presents an insurer’s balance sheet that
is represented from three different angles.
In practice however, due to lack of time and knowledge
or data constraints, many companies calculate the
value of reinsurance assets using rules of thumb and
relying on the gross results. Sometimes these give
remarkably good results, but sometimes they can be
very misleading. This article aims to reveal more
accurate approaches, along with possible pitfalls that
can easily be identified upfront, to indicate the
accuracy of rule of thumb approaches.
The first approach (base scenario) is the current
accounting view. Gross claim liabilities are valued on a
case by case basis taking a conservative approach. The
reinsurance assets are valued on an individual claim
basis, based on the latest information available.
Within Option 1, the actuary has valued the best
estimate of the gross claim liabilities using actuarial
techniques. Given the conservative approach each
DMBJNNBOBHFSUBLFTUIFSFTVMUJTBTVSQMVTPGPG
gross technical claims. For valuing the reinsurance
assets, the actuary is lacking individual data and
decides to use a net-to-gross ratio derived from
accounting data. The reinsurance assets are hence
WBMVFEBUY%VFUPUIFDIBOHFJO
valuation on both sides of the balance sheet, the Net
Asset Value has changed from 20 to 35.3.
Table 1: Sample Balance Sheet in Different Approaches
Assets
110
10
Liabilities
0UIFSBTTFUT
3*BTTFUT
/"7
$MBJN-JBCJMJUJFT
120
#BTF4DFOBSJP
Assets
Liabilities
20
110
0UIFSBTTFUT
100
8,3
3*BTTFUT
120
118,3
/"7
$MBJN-JBCJMJUJFT
Assets
35,3
83
118,3
0QUJPO
110
13
Liabilities
/"7
40
$MBJN-JBCJMJUJFT
83
0UIFSBTTFUT
3*BTTFUT
123
123
0QUJPO
Source: Aon Benfield
35
Solvency II Revealed
Figure 1: Incurred Position Towards
Its Last Known Incurred Value
250.00%
200.00%
150.00%
100.00%
50.00%
99.64%
95.17%
82.04%
73.42%
64.30%
88.49%
35.42%
100.00%
0.00%
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Source: Aon Benfield
In Option 2, the actuary has analysed the large losses
individually and discovered a trend that is seen
amongst many insurance companies. Figure 1 explores
the development of the incurred position towards its
last known incurred value. The development periods
are represented in the x-axis. The y-axis shows (using a
box-plot) the spread of the observed ratios (current
JODVSSFEMBTULOPXOJODVSSFE
*OUIJTQBSUJDVMBS
example the claims were reported if their last known
incurred value exceeded EUR1.5m (note that the
example is based on a European country’s market
motor book in Euros).
After the first year of development, the median of all
claims in the database have reached only 42% of their
last known incurred value. This number increases over
time to top 90% after eight years of development. After
13 years of development, the uncertainty drops and
only a limited number of claims have an uncertain
ultimate value. Based on this, the actuary decides to do
a detailed analysis of the reinsurance assets. Applying a
net-to-gross ratio as in Option 1 will undervalue these
assets materially, hence leading to a calculated Net
Asset Value that is understating the true available
capital. The best estimate of the reinsurance assets is
now calculated at 13, which is 30% higher than the
current accounting value. The Net Asset Value increases
further to 40.
36
Aon Benfield
Solvency II requirements
The Solvency II directive does not give any guidance on how these reinsurance assets need to be valued. They have
to follow the same principles as the gross claim liability which can be summarised and detailed in the below table:
Table 2: Guidance on the Calculation of Reinsurance Assets
Directice
Specific remarks for the calculation of Reinsurance Assets
"SUJDMF$BMDVMBUJPOPGUFDIOJDBMQSPWJTJPOT
/POQSPQPSUJPOBMSFJOTVSBODFDPWFSTIBWFNBOZDIBSBDUFSJTUJDTPGOPOMJOFBSJUZ"
DMBJNXJMMPOMZDSFBUFBSFJOTVSBODFBTTFUPODFJUFYDFFETUIFBUUBDINFOUQPJOUPGUIF
reinsurance program. Also the various clauses in the contract can increase the level
BOETPQIJTUJDBUJPOPGOPOMJOFBSFƅFDUT'SPNUIBUQFSTQFDUJWFUIFUSVFCFTUFTUJNBUF
can only be calculated from the probability weighted average.
“The best estimate shall correspond to the probability
weighted average of future cash-flows, taking into
BDDPVOUUIFUJNFWBMVFPGNPOFZFYQFDUFEQSFTFOUWBMVF
PGGVUVSFDBTInPXT
VTJOHUIFSFMFWBOUSJTLGSFFJOUFSFTU
rate term structure.”
i5IFCFTUFTUJNBUFTIBMMCFDBMDVMBUFEHSPTTXJUIPVU
deduction of the amounts recoverable from reinsurance
contracts and special purpose vehicles. Those amounts
shall be calculated separately, in accordance with
Article 81”
“The risk margin shall be such as to ensure that the value
PGUIFUFDIOJDBMQSPWJTJPOTJTFRVJWBMFOUUPUIFBNPVOU
UIBUJOTVSBODFBOESFJOTVSBODFVOEFSUBLJOHTXPVMECF
FYQFDUFEUPSFRVJSFJOPSEFSUPUBLFPWFSBOENFFUUIF
insurance and reinsurance obligations.”
"MMGVUVSFDBTInPXTOFFEUPCFUBLFOJOUPBDDPVOUUPWBMVFUIFDMBJNMJBCJMJUJFT5IJT
JNQMJFTUIBUBOBDDVSBUFDBMDVMBUJPOPGUIFSFJOTVSBODFSFDPWFSBCMFDBTInPXDBO
only be done once an accurate gross cash flow estimateJTNBEFTJODFJUXJMMCF
UIFmOBMVMUJNBUFHSPTTWBMVFJODMVEJOHBOZPƅTFUUJOHCZTBMWBHFBOETVCSPHBUJPO
UIBUXJMMEFUFSNJOFUIFWBMVFPGUIFSFJOTVSBODFSFDPWFSBCMFDBTInPXT"MTPUIFTQMJU
JOEJƅFSFOUTPVSDFTPGHSPTTQBZNFOUTFHMFHBMJOUFSFTUDBTInPXTOPUDPWFSFE
CZUIFSFJOTVSBODFDPOUSBDU
NJHIUCFSFRVJSFEUPBDIJFWFBDDVSBUFSFTVMUT'JOBMMZ
SFJOTVSBODFDPNNJTTJPOTBOEQSPmUTIBSJOHDMBVTFTDBOIBWFBNBUFSJBMFƅFDU
3FJOTVSBODFBTTFUTTIPVMEJOUIFPSZCFDBMDVMBUFETFQBSBUFMZGSPNUIFHSPTTMJBCJMJUJFT
5IJTDBOCFXJEFMZJOUFSQSFUFETJODFBOFUUPHSPTTBQQSPBDIBTEFTDSJCFEJO
0QUJPODBOBMTPCFJOUFSQSFUFEBTBTFQBSBUFDBMDVMBUJPO5IFSFHVMBUPSDPVMECF
TUSFTTJOHUIFGBDUUIBURVBMJUBUJWFDBMDVMBUJPOTPGSFJOTVSBODFSFDPWFSBCMFTDBOPOMZ
be obtained if a separate calculation is done for both as the techniques, data
and contract issues are different: gross calculations should reflect the insurance
QPMJDZDPOEJUJPOTXIFSFBTSFJOTVSBODFSFDPWFSBCMFTDBMDVMBUJPOTTIPVMESFnFDUUIF
reinsurance policy conditions.
5IFSJTLNBSHJOTIPVMESFnFDUUIFDBQJUBMDPTUUPXIJDIBUIJSEQBSUZXIJDIJTXJMMJOH
UPUBLFPWFSUIFMJBCJMJUJFTJOBOBSNTMFOHUIEFBM
JTFYQPTFE*ODBTFUIFMJBCJMJUJFT
are protected by reinsurance, the risk mitigating effect of the reinsurance
programme should be included in the calculation of the risk margin. Also the
counterparty risk that arises should be included.
"SUJDMF3FDPWFSBCMFTGSPNSFJOTVSBODFDPOUSBDUTBOE
special purpose vehicles.
“When calculating amounts recoverable from reinsurance
contracts and special purpose vehicles, insurance and
reinsurance undertakings shall take account of the time
EJƅFSFODFCFUXFFOSFDPWFSJFTBOEEJSFDUQBZNFOUTw
“The result from that calculation shall be adjusted to
UBLFBDDPVOUPGFYQFDUFEMPTTFTEVFUPEFGBVMUPGUIF
counterparty. That adjustment shall be based on an
assessment of the probability of default of the counterparty
and the average loss resulting there from (loss-givenEFGBVMU
w
The timing of the payment of the reinsurance contract can deviate from the gross
QBZNFOUEFQFOEJOHPOUIFTUBUVTPGUIFDMBJNJTJUEJTQVUFE UIFDFEBOUBOE
UIFDPOUSBDUEPFTJUIBWFBOZDPOUSBDUVBMMJRVJEJUZDMBVTFT BOEUIFSFJOTVSFSB
DPNNFSDJBMMZBDUJWFPSSVOPƅmSN *OOPSNBMDPOEJUJPOTUIFEJƅFSFODFTIPVMEUBLF
no longer than three months.
The calculated recoverables should be reduced to reflect the credit position of
UIFDPVOUFSQBSUZ*UTIPVMECFOPUFEUIBUUIFBEKVTUNFOUUIBUJTSFRVJSFEIFSFJTB
reduction of assets due to expected counterparty default5IFEFGBVMUJOFYDFTT
PGUIFFYQFDUFEEFGBVMUJTUSFBUFEJOUIFSFRVJSFEDBQJUBMDBMDVMBUJPOT
Source: Aon Benfield
Within the scope of this document we will only focus on the calculation of the claim cash flows on a gross and net basis.
37
Solvency II Revealed
Aggregate methods
The most common approach to calculate the best
estimate for reinsurance assets is based on aggregate
triangle techniques. Historical triangles of paid and
incurred claims data, gross of reinsurance, are modelled
and projected to ultimate by using a variety of different
mathematical curves. Assuming that past developments
are a reasonable indicator of future developments the
Bornhuetter-Ferguson (BF) method incorporates prior
estimates of ultimate claims into the modelling process.
It is particularly appropriate for recent years of account
where the development factor modelling method may
produce unreliable results. Unlike development factor
methods, the BF method can additionally take into
account collateral information, such as initial loss
FYQFDUBUJPOTGSPNUIFVOEFSXSJUFSTWJFXTBOEPSBOZ
pricing models that may exist, and benchmark
development patterns. The prior estimates are adjusted
using development factor projection methods under a
weighted average approach: the fewer the years of
development, the higher the weighting placed on the
prior estimate.
2. Change in reinsurance programme attachment
and limits: It is assumed that the reinsurance
programmes are stable and future trends can be
derived from past trends. Since claims triangles span
many years, they can cover reinsurance cycles. These
cycles have an effect on the pricing and this is
compensated in the cedant book by retaining more
or less risk by changing the priorities of the
programme. Figure 2 details the payment pattern of
European motor losses that exceed a threshold value.
The higher the threshold value, the slower the
payment pattern becomes.
Figure 2: Payment Pattern of
European Motor Losses
100%
600 000
1 250 000
2 500 000
80%
60%
40%
20%
Net results are then obtained by netting down the
calculated gross results using net-to-gross ratios. These
ratios are calculated from analysing the net incurred
claims to the gross incurred claims or by a separate
estimate of the ultimate retained percentage after
examination of the reinsurance programme.
When using such a method, one implicitly makes many
assumptions:
1. Stable incurred patterns: When bringing the
incurred values to ultimate, the development ratios
show the release or increase of reserve surplus. In
practice (as shown higher) large losses tend to be
under-reserved whereas attritional losses carry the
bulk of reserve surplus. This means that within the
incurred triangle, two trends are aggregated.
38
0%
1
2
3
4
5
6'
7
8
9 10 11 12 13 14 15 16 17 18 19 20
Source: Aon Benfield
Therefore, changing the reinsurance retentions not
only has an effect on the net-to-gross approach but
also affects the payment pattern.
3. Overall change in reinsurance program:
Historically lines of business can be protected by
many reinsurance programmes: individual line of
business protection by means of proportional or
non-proportional treaties, portfolio protection by
means of aggregate covers protecting the overall
portfolio retention. In an incurred net triangle, these
various programmes can have a material impact on
the netting process and — probably even more
importantly — are a result of recovery allocation
rather than a true recovery of an individual loss.
Aon Benfield
In many cases, when a closer examination of the
(individual) claims data or the reinsurance policy
wordings is made, even more practical issues arise:
1. Individual claims that have a substantial increase or
decrease of reserves can have an important impact
on the incurred development pattern. If the netting
is done on aggregated data, the effect of such a
change in incurred can lead to misleading results if it
is assumed to be ‘normal’ and hence projected
forward.
2. How should insurers reflect the various clauses in the
reinsurance programmes in such a modelling
technique?
3. How should insurers deal with issues such as layering
of reinsurance and clash covers?
Individual models
In individual models, each claim that has a potential to
create a reinsurance asset is projected to its ultimate
position and gross and reinsurance recoverable cash
flows are calculated. Such techniques have the major
advantage that the actual reinsurance programme can
be applied and hence all uncertainty of the results is
due to the uncertainty of the gross (individual) model.
Many assumptions are actually hidden in aggregate
modelling (e.g. if one assumes that the past experience
can be projected into the future), while in individual
modelling many assumptions need to be defined
explicitly. For example:
t "UXIJDIUISFTIPMEMFWFMXJMMIJTUPSJDBMDMBJNTCF
selected and modelled to ultimate and how should
these levels be changed to reflect claims inflation?
t )PXTIPVMEJOTVSFSTEFBMXJUITNBMMDMBJNT
(unreported or below the selected threshold) which
have the potential to create a reinsurance asset when
they are developed to ultimate?
t )PXTIPVMEJOTVSFSTEFSJWFVMUJNBUFT
Applying such a modelling technique makes the results
much more transparent and allows for individual stress
testing on elements such as the impact of one
individual claim and parameters.
Current industry practices include both deterministic
and stochastic approaches to quantify the reinsurance
asset. Due to the non-linear effects caused by
reinsurance, the stochastic approach is preferred. In the
case study described below the technique of ’nearest
neighbour’ has been applied to calculate the value of
reinsurance assets.
Individual models are not the magic trick that solves all
problems when dealing with limited data, noise and a
large volatility in outcomes. However, they do offer a
much more transparent and robust analysis with the
biggest advantage that each individual (large) claim
can be discussed with the claims manager. This
probably makes this technique much more defendable
from a ‘use’ perspective. For each individual claim
ultimate paths can be created and discussed with the
claims manager, reinsurance manager and legal
department to assess the quality of the modelled
results. Experience, non-quantitative data (e.g. medical
reports, court uncertainty) can be used to discuss the
feasibility of modelled results.
Which approach to take?
The use of aggregate methods to calculate the value of
reinsurance assets is defendable as a proxy method but
only when all above considerations have been evaluated
and in case the reinsurance assets are minimal compared
to gross estimates. In other cases it is worth analysing
individual methods and comparing the results between
aggregate and individual models. Certainly when the
impact on the Net Asset Value (and hence the solvency
ratio) is material, it is advised to apply individual
methods to have a more accurate result.
Case study
The case study was conducted on a European Motor
book for a company which had an individual line of
CVTJOFTTQSPUFDUJPOUISPVHI&YDFTTPG-PTTQSPHSBNNFT
but where the priority changed every year. The analysis
was done using a stochastic ‘nearest neighbour’
method where each (potential) large loss was projected
to ultimate and then sent to the various reinsurance
programmes to calculate the netting effect. The
modelling was done using ReMetrica, Aon Benfield’s
dynamic financial analysis modelling tool. No discount
effect was introduced.
39
Solvency II Revealed
Figure 3: Accounting for Reinsurance Assets
119.4
-12%
100.0
105.0
+31%
-9%
91.2
D. Impact of interest sharing
clause added
C. Ultimate effect added. The scenario’s left and right
were obtained by assuming fgu losses were 5% lower
(left) or higher (right) then assumed in the best estimate.
B. Accounting value of Reinsurance assets
including effect of stabilisation clause
A. Accounting value of Reinsurance Assets
based on reported claims
Source: Aon Benfield
The first bar (A) reflects the current accounting situation
of the reinsurance assets. Accounting valuation was done
on paid recoverables + EOY estimate of the recoverable
based on the incurred value as at EOY.
If the company has valued the reinsurance assets using
the gross incurred value but kept account of the effect
of the stabilisation clause and the payment pattern of
large losses, the value of the reinsurance assets would
drop by 9%. This is reflected in bar B. In reality
however, inflation will have an impact on the ultimate
cash flows and — in general — large losses tend to
increase over time due to incomplete information (as
shown in one of the above graphs).
After conducting a (stochastic) ultimate calculation of
all individual gross losses that have the potential to
breach the reinsurance programme, the best estimate is
changed to 119.4 which is above the accounting value.
40
Two stress tests were conducted to calculate the effect
on the value of the reinsurance asset in case From
(SPVOE6QDMBJNTXPVMEDIBOHFCZQFSDFOU
Finally the accounting value of reinsurance assets did
not include any effect of a legal interest sharing clause
which made the final best estimate drop to 105% (from
the original 100%).
The impact of clauses and individual claims data (and
their relative position towards settlement) causes a roller
coaster on the best estimate assumption. The example
was chosen as each individual effect has a large impact
and therefore demonstrates the importance of taking
each into account. The fact that the final result was close
to the initial accounting value should not be generalised
since the ultimate is well below or above accounting
value in many analysed portfolios.
Aon Benfield
Risk and Capital Modelling for
Solvency II: A Pillar of Strength
3FWFBMFE
Many insurers have chosen to reap the benefits of using an internal model for Pillar 1,
albeit in consideration of the investment in time and resources. However, internal models
can also play a positive role under Pillar II as part of the Own Risk and Solvency
Assessment (ORSA) to demonstrate to regulators that risk is being effectively managed.
Introduction
Solvency II is putting the spotlight on capital modelling
and creating both opportunities and challenges. There
is significant growth in the adoption of partial or full
internal models as insurers seek a more representative
capital assessment than the Standard Formula. But
there is also an increase in complexity as companies
using internal models need to ensure their models can
satisfy each pillar of Solvency II as well as existing and
emerging accounting standards. In addition, they must
ensure that these models are actually used in making
key decisions about the business.
So far in the Solvency II project, both regulators and
insurers have focused much of their attention on Pillar I
to calculate solvency capital requirements. Efforts are
now well advanced, with firms having stepped through
several Quantitative Impact Studies and have chosen
either the prescriptive Standard Formula or a bespoke
internal capital model using a Dynamic Financial
Analysis tool such as Aon Benfield’s ReMetrica.
Onus on the ORSA
Attention is now shifting towards demonstrating
wider risk management and governance capabilities to
the regulator to satisfy Pillar II and, in particular, the
completion of the Own Risk and Solvency Assessment,
XJUI-FWFMHVJEBODFGSPNUIF&VSPQFBOJOTVSBODF
regulator (EIOPA) due imminently. EIOPA has
previously defined the ORSA only in broad, nonprescriptive terms, defining it as ”the entirety of the
processes and procedures employed to identify,
assess, monitor, manage, and report the short and
long term risks a (re)insurance undertaking faces or
may face and to determine the own funds necessary
to ensure that the undertaking’s overall solvency
needs are met at all times.”
For firms that have chosen to build partial or full
internal capital models, the ORSA necessitates a longer
term view of risk. Whereas Pillar I requires risks to be
considered on a one-year time horizon, insurers prefer
to model the total risk emerging in run-off when
making risk management decisions.
With this in mind, Aon Benfield updated ReMetrica to
allow firms to generate both one year and longer-term
views using a single model and thereby avoid
duplication of effort.
In addition, Pillar II requires firms with internal models
to prove to the regulator that adequate model
governance processes exist around the model and its
data. To help address this requirement, ReMetrica’s
Enterprise Edition incorporates new components to
help companies keep track of their models as they
move one from iteration to the next. Enterprise Edition
allows companies to control which users have access to
the which parts of a model, record who has changed
what and when, and compare one iteration of a model
with another with reporting functions.
The ORSA has sometimes, mistakenly, been viewed as a
simple box-ticking exercise, supplementing the Standard
Formula with a handful of template documents and
forms. Although understandable given the lack of
prescriptive guidance from EIOPA, this approach misses
a principal aim of Pillar II – to prove to the regulator that
a risk management culture permeates the organisation,
and influences both everyday decision-making and
longer-term business strategy. A regulator could impose
a capital loading if they do not see sufficient evidence of
a strong risk mitigation strategy.
41
Solvency II Revealed
To this end, some firms using the Standard Formula for
calculating capital are also turning to tools such as
ReMetrica to model and analyse their key risks for Pillar II
under a range of business scenarios and time frames.
This particularly applies where risks, such as natural
catastrophes, are not adequately captured by the
TUBOEBSEGPSNVMBUIFSJTLQSPmMFJTEJGGFSFOUGSPNUIF
Standard Formula assumptions or the risk interactions
are complex.
Modelling key risks in such cases allows firms to
demonstrate these are being analysed, measured and
monitored. In turn, this provides a tangible, quantitative
output to inform business decisions, thereby allowing a
firm to realise real business value from the investment in
meeting the requirements of Solvency II. It also provides
a less burdensome entry point into capital modelling,
with some firms likely to evolve these models into a
partial or full internal model.
Conclusion
Solvency II is increasing both the take-up of models and
the range of decisions influenced by models. Tools such
as ReMetrica are well-suited to the disciplined, analytical
approach to risk management required for Pillar II, with
a clear direction towards wider usage and acceptance of
modelling key risks.
42
Aon Benfield
Contact Information
Gareth Haslip
Head of Risk & Capital Strategy EMEA
+44 20 7522 8137
gareth.haslip@aonbenfield.com
Marc Beckers
Head of Aon Benfield Analytics EMEA
+44 7931 472 999
marc.beckers@aonbenfield.com
John Moore
Head of International Analytics
Aon Benfield Analytics
+44 20 752 3973
john.moore@aonbenfield.com
Scan here to access Aon Benfield’s thought leadership publications including the Solvency II Revealed report.
About Aon Benfield
Aon Benfield, a division of Aon Corporation (NYSE: AON), is the world’s leading reinsurance intermediary and full-service capital
advisor. We empower our clients to better understand, manage and transfer risk through innovative solutions and personalized
access to all forms of global reinsurance capital across treaty, facultative and capital markets. As a trusted advocate, we deliver
local reach to the world’s markets, an unparalleled investment in innovative analytics, including catastrophe management,
actuarial and rating agency advisory. Through our professionals’ expertise and experience, we advise clients in making optimal
capital choices that will empower results and improve operational effectiveness for their business. With more than 80 offices in
50 countries, our worldwide client base has access to the broadest portfolio of integrated capital solutions and services. To learn
how Aon Benfield helps empower results, please visit aonbenfield.com.
This document is intended for general information purposes only and should not be construed as advice or opinions on any specific facts or circumstances.
The comments in this summary are based upon Aon Benfield’s preliminary analysis of publicly available information. The content of this document is
made available on an “as is” basis, without warranty of any kind. Aon Benfield disclaims any legal liability to any person or organization for loss or damage
caused by or resulting from any reliance placed on that content. Aon Benfield reserves all rights to the content of this document.
43
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