m - bd - cfa uk from economic capital to erm - 20130417_sh_ev
TRANSCRIPT
Disclaimer
The views and opinions expressed in this presentation are those of the author and do not reflect the official policy or position of Prudential. Examples of analysis performed within this presentation are only examples. They should not be utilized in real-world situations as they are based only on very limited and dated open source information
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CFA UK 17 April 2013
VaR limitations - subaddivity
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CFA UK 17 April 2013
Risk 1Probability Loss
0.03 1 mln
0.97 0
95% VaR 0
Risk 2Probability Loss
0.03 1 mln
0.97 0
95% VaR 0
Risk 1 and 2
Probability Loss
One event 0.0582 1 mln
Two events 0.0009 2 mln
95% VaR 1 mln
QuizData:• Monthly capital return index S&P 500 returns from Dec
1927-Feb 2011• Dec 1927 index value 17.66, Feb 2011 1,327.22• Total number of 998 monthly returns
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CFA UK 17 April 2013
Question:When excluding 10 highest monthly returns (setting them to 0%) what would be the index value as at Feb 2011?
Answers
<250
250-500
500-750
750-1000
>1000
Results• Set highest 10 values to 0: 172.80 (-87%)• Set lowest 10 values to 0: 15,330.78 (+1.050%)
0
200
400
600
800
1,000
1,200
1,400
1,600
1927
1934
1941
1948
1955
1962
1969
1976
1983
1990
1997
2004
All inclusive
Top 10 excluded
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
1927
1935
1943
1951
1959
1967
1975
1983
1991
1999
2007
All inclusive
Bottom 10 excluded
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CFA UK 17 April 2013
“Risk mitigation” through dividends
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-
1.000
2.000
3.000
4.000
5.000
6.000
Valu
e to
tal r
etur
n
Date
S&P500 Total return
total return index
without top 10
CFA UK 17 April 2013
Nominal yield curves
Risk Management Hedging uses assets quoted on OISPricing (Guarantees) Funding for hedging based on OISProvisioning Solvency II based on LIBOR & UFR
– One-off surplus (based on current market environment)– Hedging efficiency and provisioning risk due to LIBOR-OIS basis
EUR 24 August 2012
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
3.50%
1 11 21 31Term (Years)
EUR / 24 August 2012 / Spot / Annual
Market LIBORMarket OISSolvency II Risk Free
Source: Bloomberg
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CFA UK 17 April 2013
?
The importance of discounting - 1• ILLUSTRATIVE EXAMPLE• 1 German and 1 Greek insurance company• Both selling an annuity product▫ 65 year old male▫ Life annuity of 1000 paid end of the year▫ Dutch mortality table 2010-2060▫ No other (life) risks▫ New business ensures liability mix is stable over time
• Balance sheet as per 30 June 2008▫ German insurance company invests in German government
bonds▫ Greek insurance company invests in Greek government bonds▫ Both companies have surplus of 120% as at 30-6-2008▫ Liability discounting on SII curves
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CFA UK 17 April 2013
The importance of discounting - 2
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CFA UK 17 April 2013
0%
20%
40%
60%
80%
100%
120%
140%
Solv
ency
ratio
Date
Solvency
German
Greek
The importance of discounting - 3
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114%115%116%117%118%119%120%121%122%123%
Solv
ency
ratio
Date
Effect different yield curves
SII curve 30
SII curve 20
SONIA
CFA UK 17 April 2013
Liquidity premium adjustments
12
050
100150200250300350400450500
LQP
in b
asis
poi
nts
Date
LQP development over time
USD
GBP
EUR
CFA UK 17 April 2013
Source: Itraxx
(100)
(50)
-
50
100
150
200
250
300
350
400
MP
in b
p
Date
MP development
UK
US
EUR
Putting the picture together
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0%1%2%3%4%5%6%7%8%9%
Yiel
d
Date
Solvency II discount curves
SII discountcurve
credit spreads
LQP discountcurve
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
12.000
14.000
16.000
18.000
20.000
22.000
24.000
26.000
28.000
Valu
e as
sets
and
liab
ilitie
s
Date
Effects of LQP
Corp bonds
TB no LQP
TB LQP
SII discount
corp bond
70%
75%
80%
85%
90%
95%
100%
105%
110%
115%
120%
Solv
ency
ratio
Date
Effects of LQP
no LQP
LQP
CFA UK 17 April 2013
Insurance Balance Sheet RiskDivergent discount rates between markets and regulations.
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CFA UK 17 April 2013
LIBOR-OIS SpreadAnalysis of daily data points
Term 1-year 20-year 30-year0.5% percentile 44 bps 27 bps 17 bps
Median 66 bps 32 bps 26 bps
99.5% percentile 105 bps 39 bps 33 bps
EUR from 2 Jan 2012
0.00%
0.20%
0.40%
0.60%
0.80%
1.00%
1.20%
1 11 21 31Term (Years)
Source: Bloomberg / MillimanCFA UK 17 April 2013
Solvency II-OIS SpreadAnalysis of daily data points
Term 1-year 20-year 30-year
0.5% percentile 34 bps 17 bps 61 bps
Median 56 bps 22 bps 72 bps
99.5% percentile 95 bps 29 bps 93 bps
EUR from 2 Jan 2012
0.00%
0.20%
0.40%
0.60%
0.80%
1.00%
1.20%
1.40%
1.60%
1 11 21 31Term (Years)
Source: Bloomberg / MillimanCFA UK 17 April 2013
SII-OIS Basis Value Difference of ZCBAnalysis of daily data points
20-year 30-year
0.5% percentile 3.48% 18.38%
Median 4.46% 21.58%
99.5% percentile 5.73% 27.80%
EUR from 2 Jan 2012
Difference in Value ≈ Spread x Term of Zero Coupon Bond
0%
10%
20%
30%
40%
50%
60%
1 11 21 31Term (Years) Source:
Bloomberg / Milliman
CFA UK 17 April 2013
Issues For Risk ManagementSolvency II • Significant difference between market and Solvency II for discounting long-term fixed
cash-flows• Currently Surplus.
– But… this depends on UFR relative to prevailing market conditions
• SCR Capital Charge for this basis and risk of reversal?
Risk Management• Added complexity and potential inefficiency in current hedge strategies.• Are there solutions?
– LIBOR-vs-OIS basis hedge-able via swap• Active markets currently for EUR (liquid to c20 years) plus GBP and USD
• Full Solvency II – OIS more challenging
CFA UK 17 April 2013
Economic Capital (Insurance)
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We illustrate with a simplified balance sheet
of an insurer – so we are all on the same
page.
The asset side of the balance sheet contains mostly financial
assets.
Direct loans are possible and increasingly sought by some
firms.
Liabilities are mainly to policyholders – senior
liabilities being those at least equal in rank to
policyholders
“Economic Capital” is calculated using stresses to
assets and liabilities risk factors – and allowing for
diversification.
Own Funds in excess of the capital are what insurers need to control. But that
requires a large amount of computing power…
Historical Capital Analysis Daily Movements In Excess Capital – MA Added
Volatility in excess capital reduced by c70%
Including mitigation of SCR credit stresses reduces SCR by c15% providing a further boost to excess capital
Poor Risk Appetite
Why Do Insurers Fail?What should we be focussed on?
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Source: FSA 2003
Operational Risk
This FSA paper from 2003
concluded that insurance failures were the cause of a
interconnected series of events.
CFA UK 17 April 2013
Governance
Valuations
Risk Events (Not Just Quantitative Risk)
Poor Decisions
(Wrong Product @
Wrong Price)
Fixing Economic Capital with ERMCapturing why insurers fail in our risk assessment
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Poor Risk Appetite
Operational Risk
Governance
Valuations
Risk Events (Not Just Quantitative Risk)
Poor Decisions (Wrong Product @ Wrong Price)
Include the full set of risk events – not just those where there is data.
Consider the governance structure, reporting lines, incentives as much as the
capital.
Develop operational models that capture operational uncertainty – i.e. that can show operational risk events not in the event set.
Project the economic balance sheet forward so it capture the business plan of the insurers
– as well as the business sold to date.
Capture the true economic valuation of (adverse) financial outcomes – fair value.
See next section…
Risk Appetite DesignQuantitative Criteria Examples
Avoid regulatory intervention due to a capital requirements breach.
(typically any regulatory intervention is considered undesirable)
Maintain capital at least high enough to maintain a AA rating
with 9 years out of 10.
(though of course rating is not just a function on capital)
Deliver an (economic) profit 7 years out of 10.
Ensure that economic profit and loss volatility is within a range of
+/10%
(In practice P&L measures may well differ in how “economic” they are – IFRS
Earnings, EEV Earnings are often referred to.)
Some statements can be mapped to the probability of future capital-at-risk (own funds).
These statements may well impose some tough constraints on the
distribution of Capital at Risk. There may need to be push-back from
finance / risk on what is achievable.
CFA UK 17 April 2013
Risk Appetite DesignTypical Statements
Always have enough cash to meet financial obligations.
Maintain sufficientcapital to achieve at least a AA rating (19
in 20 years).
Zero tolerance forany kind of
reputational risk.
Ensure earnings volatility is in line with shareholder
expectations.
Risk Appetite ResearchThe Risk Appetite Problem
Need to find a link between the operational indicators (including the non-quantitative ones for things like process, people and reputation)
and…
… the probability of the desires expressed in risk appetite statement being true or within the stated probability.
They identified that the mapping was complex and therefore turned to some on the tools of complexity science for a solution. Tools used were concept mapping and Bayesian Networks.
CFA UK 17 April 2013
Risk Appetite ResearchStage 1 – Cognitive Mapping
Key Nodes
Gaps
Source: Milliman
• Experts are able to map the way the business works and how risks in their area of the business emerges and is propagated.
• Complex maps are created but can be distilled down to a manageable size extracting the important nodes.
• Gaps in the “story” can be identified and explored in more depth.
CFA UK 17 April 2013
Risk Appetite ResearchStage 2 – Convert Concept Map to Bayesian Network
Implemented in AgenaRisk
After simplifying the concept map (using some well established mathematical techniques) … linking the risk appetite statements to the measurable indicators … the simplified concept map is converted to a
Bayesian Network.
The Bayesian Network is parameterised through conditional probabilities which have proven cognitively straightforward for stakeholders (including boards!) to relate to – aiding estimation and validation of the
probability of risks propagating.
CFA UK 17 April 2013
Risk Appetite ResearchStage 3 – Mapping Appetite to Operational Indicators
Once the network is developed the high level risk appetite variables are set to have the probabilities set out in the risk appetite statement.
The propagation properties of the Bayesian Network are used to derive the resulting distributions of the indicators.
CFA UK 17 April 2013
Risk Appetite ResearchStage 4 – Propagate Evidence
The network can be reversed too.
Operational indicator values can be propagated back through the Bayesian Network to the risk appetite variables.
The risk appetite variable distributions can be inspected to check they are in-line with the statement.
CFA UK 17 April 2013
About us
Servaas Houben heads the risk scenario generation team at Prudential, London. He
studied econometrics in the Netherlands and worked in life insurance for the first four
years of his career. Following this, he worked in Dublin and London. Besides actuarial,
Servaas completed the CFA and FRM qualifications, and regularly writes on his blog,
for CFA digest and Dutch actuarial magazines.
Email: [email protected]
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Elliot Varnell is a consulting actuary at Millman in London. He is a UK Qualified
Actuary and hold the Chartered Enterprise Risk Analyst qualification. He is a member
of the governing board of the UK Actuarial Profession and Chairman of the ERM
Research and Development Committee of the UK Actuarial Profession. He consults on
Economic Capital, ALM and ERM.
Email: [email protected]
LinkedIn: http://www.linkedin.com/in/elliotvarnell