Surviving the Next Crisis,
A Risk Management Perspective
Presented by Michel M. Dacorogna
SCOR Scientific Advisor

Seminar of the Institute of Actuaries of Japan, Tokyo, Japan, February 17, 2014

Disclaimer
Any views and opinions expressed in this presentation or any
material distributed in conjunction with it solely reflect the views of
the author and nothing herein is intended to, or should be deemed,
to reflect the views or opinions of the employer of the presenter.

The information, statements, opinions, documents or any othermaterial which is made available to you during this presentation arewithout any warranty, express or implied, including, but not limited
to, warranties of correctness, of completeness, of fitness for any
particular purpose.

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 20142

1The 2008/09 financial crisis – an analysis fromthe risk management point of view

2

Preparing for the next negative surprise to come3Consequences of financial crises on insurance
capital requirements

4

Giving the regulatory system enough flexibility torespond to the next crisis to come5Conclusion

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

3

The current developments in the financial industry
line up amongst the worst economic crises in history
S&P index annual returns from 1791 to 20131)

What is next???
We are here!

1937
2008
1907
1857
1917
1931 ‐47.0% 1854

to ‐50%‐38.6%‐38.5%‐33.2%‐31.0%‐30.6%‐30.2%

to ‐40%

1974
1930
1920
2002
1893

‐29.7%‐28.5%‐24.5%‐23.4%‐20.0%

to ‐30%

1884
1903
1842
1876
1941
1973
1814
1940
1932
1846
1957
1913
1890
1841
1966
2001
1873
1853
1839
1910
1929
1946
1962
1836
1977
1837
1969
1859
2000

‐18.8%‐18.4%‐18.1%‐17.9%‐17.9%‐17.4%‐16.7%‐15.3%‐15.2%‐14.5%‐14.3%‐14.3%‐13.5%‐13.3%‐13.1%‐13.0%‐12.7%‐12.7%‐12.3%‐12.1%‐11.9%‐11.9%‐11.8%‐11.7%‐11.5%‐11.5%‐11.4%‐10.7%‐10.1%

to ‐20%1) source: globalfinancialdata.com

1981
1803
1877
1914
1883
1865
1811
1819
1953
1887
1990
1934
1825
1939
1822
1805
1804
1875
1816
1848
1818
1851
1827
1960
1882
1894
1888
1896
1810
1861
1994
1923
1829
1833
1948
1801
2011

‐9.7%
‐9.6%
‐9.4%
‐8.6%
‐8.5%
‐8.5%
‐7.5%
‐7.5%
‐6.6%
‐6.6%
‐6.6%
‐6.0%
‐5.8%
‐5.4%
‐4.8%
‐4.4%
‐4.3%
‐4.1%
‐3.8%
‐3.6%
‐3.2%
‐3.2%
‐3.1%
‐3.0%
‐2.9%
‐2.5%
‐2.5%
‐2.3%
‐2.1%
‐1.8%
‐1.5%
‐1.5%
‐1.1%
‐0.9%
‐0.7%
‐0.1%
‐0.1%

to ‐10%

1965
2004
1959
1886
1800
1845
1968
1830
1921
1871
1993
1802
1872
1899
1864
1878
1821
1926
1870
1840
1824
1832
1820
1806
1992
1807
1856
1866
2007
1889
1812
1916
1906
1835
2005
1881
1831
1912
1874
1815
1956
1987
1892
1869
1838
1867
1855
1984
1902
1847
1813
1978
1809
1911
1895
1970
1808
1823
1826
1828
1849
1947

9.1%
9.0%
8.5%
8.5%
8.1%
8.1%
7.7%
7.4%
7.4%
7.3%
7.1%
6.8%
6.8%
6.5%
6.4%
6.1%
6.1%
5.7%
5.6%
5.5%
5.1%
4.8%
4.7%
4.6%
4.5%
4.4%
4.4%
3.6%
3.5%
3.5%
3.5%
3.4%
3.1%
3.1%
3.0%
3.0%
3.0%
3.0%
2.8%
2.7%
2.6%
2.0%
1.8%
1.7%
1.6%
1.6%
1.5%
1.4%
1.3%
1.2%
1.1%
1.1%
1.1%
0.7%
0.5%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%

0‐10%

■ 2008 was the 3rd worst year after 1937 and 1931
with -38.5%■ After two years of recovery, 2011 showed 0.11% return for a year and 2012, 13.4% and1885 19.8%
2013 29.6% !!!
1852 19.6%

1999
1943
1976
1898
1963
1924
1850
1880
1891
1983
1951
1918
1901
1905
1972
1844
1982
1986
1858
1900
1909
1860
1919
1944
2006
2012
1834
1964
2010
1897
1942
1988
1979
1817
1952
1971
1868
1949

19.5%
19.4%
19.1%
18.9%
18.9%
18.8%
18.7%
18.7%
17.6%
17.3%
16.5%
16.4%
15.7%
15.6%
15.6%
15.5%
14.8%
14.6%
14.3%
14.1%
14.1%
14.0%
14.0%
13.8%
13.6%
13.4%
13.0%
13.0%
12.8%
12.6%
12.4%
12.4%
12.3%
11.9%
11.8%
10.8%
10.8%
10.3%

10‐20%

2013
1915
1936
1989
1998
2003
1955
1985
1991
1980
1904
1938
2009
1925
1961
1950
1922
1996
1967

29.6%
29.0%
27.8%
27.3%
26.7%
26.4%
26.4%
26.3%
26.3%
25.8%
25.6%
25.3%
23.5%
23.3%
23.1%
21.8%
20.9%
20.3%
20.1%

20‐30%

2009 showed a+23.5% return

1958
1863
1928
1908
1995
1975
1997
1927
1945

38.1%
38.0%
37.9%
37.4%
34.1%
31.5%
31.0%
30.9%
30.7%

30‐40%

1933
1954
1843
1879
1935

46.6%
45.0%
45.0%
43.0%
41.5%

40‐50%

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

1862

55.4%

50‐60%

4

The effects are eye-striking – but where is the cause?
 The 2008/09 financial crisis and its consequences has caused previously
unimaginable wealth losses:
The 100 largest banks of the world lost
384 billion USD by May 2008
(Citigroup: 43 billion, UBS: 39 billion,
Merrill Lynch 37 billion)

AIG lost 100 billion USD in
the last quarter of 2008 (300k
USD per minute!)
The GDP of OECD
countries dropped by 2%
in last quarter of 2008 andby 2.1% in the firstquarter of 2009…

The current program tohelp Greece to cope withits debts is already above
450 billion EUR

 This crisis has also caused the demise of elite financial institutions, and a global
recessionWhat are the causes of financial crises…
…despite the traditional post-crises themes of insufficient regulations, realestate bubbles, excessive leverage and capital flows, lax monetary policies
and so on…?
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

5

Financial crisis: naturally natural?
 since 1825 the volcano Mount Vesuvius had
9 periods of eruption-1)…
 …while 6 volcanic erruptions causing morethan 5‘000 death occured worldwide-2)…
 …and 10 earthquakes worldwide with morethan 50‘000 fatalities-3) happened,...
 …7 tsunamis with more than 25‘000 people
killed-4),…
 …while in the meantime there are 10 yearsof more than -20% loss in the S&P 500
index on record
History shows: there were many crises
before and likely there will be morecoming up in the future To be prepared for a future financial
crisis the companies‘ generalmindset has to change(1(2(3(4-Volcano Discovery
Wikipedia
US Geological Survey (www.usgs.gov)
Wikipedia

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

6

What is behind the 2008/09 severe financial crisis?
 The common measures have proven grossly insufficient to prevent
severe crisis from recurring and risk asphyxiating the development of
the financial system through excessive capital requirements anddeleveraging
 That is why it is important to focus the analysis on factors that are notpart of the core of the conventional wisdom
 We highlight here the importance of three key ingredients for severe
financial crises:

1. A significant negative surprise
2. Irresponsibly high risk appetite, advantaged by highfinancial leverage
3. The excessive concentration of aggregate risk in highly
leveraged financial institutions

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

7

The surprise in the present financial crisis was the
weak links in an immensely complex system The surprise was not the decline of realestate prices and the fact that subprime
were the first affected by this

1. A significant
negative surpriseUnexpected dependences: The surprise was the related distress ofmany parts of the financial system,
even those very distant from thesubprime market itself
 The data was available to recognize theproblem, but reality is immenselycomplex with millions of potential weaklinks
 “Ex-post”, it is easy to point out the onethat blew up, “ex-ante” it is a different
matter This change in paradigm from irrelevant
to critical linkages, triggers massive
uncertainty and unleashes destructive
flights to quality
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 20148

1. A significant
negative surprise

Surprises are changes in the environment itself
 Surprises that have the potential to trigger a severe financial crisis are
not simply bad realizations within a known probabilistic environment…
 …rather, they are changes in the environment itself

Example: In 2008, the first under-par redemption from a Money Market fund since
their creation in 1968 (Reserve Primary fund after Lehman bankruptcy)
caused investors to question the safety of the entire industry
 Money market funds had been considered extremely safe, and had indeed
benefited from the flight to quality the previous year, growing by about
USD 850 billion (34%) since mid-2007
 The week following Lehman’s default, there were USD 169 billion
redemptions from total invested USD 3.4 trillion (5%), as well as large shift
from prime funds towards fund investing exclusively in government debt

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 20149

In time of crisis small effects can generate huge
impacts – mainly driven by human behaviour

1. A significant
negative surpriseManagement failures in times ofcrisis

Effects (based on Lehman bankruptcy
example)Missing leadership: failing systematic In retrospect, the consequences of Lehman’s
demise on the Primary Fund could have been
predicted: Public filings showed large investments inLehman as early as November 2007

landscape monitoring

Missing analysis: Generally missing
systematic interpretation of actual
developments

Missing initiative: Sitting on cash cows
instead of proactively evaluating future risks

Missing coolness: Harsh anddisproportional reaction of market participants

 Anyone who took the trouble of connecting the dots
could, in principle, have foreseen what might
happen However, money market funds had a track record ofstability that had always made it unnecessary toinspect their holdings
 The realization that there might be further losses inpreviously unexamined places led investors tointensify their flight to quality

The main failure was not to understand that relatively “small effects” could generatehuge impacts and create a confusion on the entire system
Surprises quickly trigger a chain of unexpected events from the panic they engender

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201410

2. Irresponsibly highrisk appetite

What is the „right“ leverage for the „right“ risk appetite?
 On capital, there is very strong consensus that financial companies should in future run withmore capital and lower leverage than in the past – but how much more?
Business Model A:
Low financial leverage

Business Model B:
Medium financial leverage

Business Model C:
High financial leverageillustrative

Debt (Hybrid issuances,
bonds, etc…)
Equity Capital

Total Available Capital Preferred business modelby the regulatory boards
 Relatively low expected
ROE, but with low
volatility in the results

Total Available Capital

Total Available Capital Uncertain volatility
 Relatively speaking higher
cost of capital High volatility in results due
to irresponsibly high risk
appetite Generally higher risk
appetite since cost of capitalis higher

The relevant risk measure for the regulators is the ratio between theown capital and the companies’ total risk exposure
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201411

2. Irresponsibly highrisk appetite

A controlled risk appetite reduces the probability of ruin
Theoretical example: increasing the risk appetite has a highly multiplicative effect on acompanies’ probability of ruin if crisis scenario is integrated in the model
illustrative example

Expected change of Economic Value in € bn

2

0Actual Available
Capital level-2-4

ROE of
900 bps

14 times
higherprobabilityof ruin-6-8

Available Capital level
would have to be
doubled-10

ROE of
1800 bps

-12
1

10

100

1000

 Keeping the same businessrisk and doubling the
expected profit without
increasing the Available
Capital increases theprobability of ruin from an
extreme scenario by a factorof 14
 Doubling the profitability
target to 1 800 bps would
require the Available Capital
to be doubled accordingly inorder to cover the probabilityof ruin equally compared to
the lower risk profile

10000

Return period in years

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201412

Aggregate risks are a major cause for crisis

3. Excessive
concentration of
aggregate risk

 The third important cause for a severe crisis to develop is to what extent
the highly leveraged and interconnected sector of the economy, generally
the financial sector, is being exposed (directly or indirectly) to a surpriseof the kind discussed earlier Aggregate risks are those exposed to aggregate shocks to the entire
economy Investment in structured products exposed financial institutions to moreaggregate risk and surprises than in the past
 In the 2008/09 crisis, banks were holding mostly AAA-tranches of a large
variety of new ABS (Asset Backed Securities) (85% of assets held insecuritized form) Those tranches rely on the protection by the junior tranches and by thelaw of large numbers in order to reduce the risk of default enough toachieve AAA-rating

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201413

The law of large numbers does not hold undermajor aggregate shocks

3. Excessive
concentration of
aggregate risk

 The law of large numbers implies that the loss on a pool with sufficientnumber of underlying assets, as was the case with most ABS, canonly occur when an aggregate shock takes place Furthermore, the higher up a given structure is situated, the larger theaggregated shock must be for it to pierce the protection offered by thejunior tranches
 Losses large enough to affect the AAA-tranche only occur in states ofsevere aggregate shocks, but this is exactly what large surprises do!
 Therefore holdings of AAA-tranches of structured products exposed
financial institutions to more systemic risks than their rating, whenmisinterpreted, would suggest and certainly more than similarly rated“single name” corporate bonds

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201414

Major financial institutions were bearing moreaggregate risks than anticipated

3. Excessive
concentration of
aggregate risk

 Corporate bonds are still affected by macroeconomic conditions but
idiosyncratic factors play a larger role
 Downgraded structured financial securities lost on average between 5
and 6 notches in the period 2007/2008
 By comparison, during the great corporate bond downgrade of
2001/2002 (30% of corporate bonds were downgraded) the averagenotch-loss was 1.8
 The systemic consequence of this risk was that highly leveraged
institutions were bearing more aggregate risks than would have beenthought from simply observing the average ratings of their assets
 Having the financial sector of the economy holding such risk withrespect to aggregate surprise proved to be a recipe for disaster

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

15

1

The 2008/09 financial crisis – an analysis fromthe risk management point of view

2

Preparing for the next negative surprise to come3Consequences of financial crises on insurance
capital requirements

4

Giving the regulatory system enough flexibility torespond to the next crisis to come5Conclusion

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201416

Surprise and aggregate risks are not going to disappear soon Surprise and aggregate risks are major causes for financial crises
 Both elements are not going to disappear soon. We can thus expectthat our economy despite all attempts will be again subject to shocks
 The right risk management policy is to prepare the organization to theoccurrence of such shocks and to make sure that the company cansurvive them
 Rather than trying to predict the next crisis or to avoid it, we should
concentrate on making sure that our risk management model
integrate the occurrence of crisis with a reasonable probability
 Only this way, our organizations will be prepared to face major
disruptions of the financial markets

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201417

Reinsurers and banks as risk bearers
 Banks have traditionally been taking credit risks on their books in theirwholesale lending operations, but also market risks through theirsecurities trading operations
 Insurers and reinsurers have been taking most other kinds of risks:mortality and interest rate risks for life insurers, natural disasters,
liability and accident risks for non-life insurers
 Reinsurers are confronted to extreme risks in their daily business andhave integrated them in their internal models
 The last dramatic event for reinsurance was the series of US
hurricanes Kathrina, Rita and Wilma, which cost the industry USD 50
billion for a total of reinsurance premium around USD 160 billion
covering all the reinsured risks
 Such large event caused only one reinsurer to fail. All the others
survived and profited from the hardening of the market

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

18

50

40

all in 2005

60

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 20142005 Hurricane Rita
2005 Hurricane Wilma
2005 Hurricane Katrina

2004 Hurricane
2004 Hurricane Charley2004 Hurricane Ivan

2001 Terror Attack

1999 Winter Storm

1994 Northridge

1992 Hurricane

1991 Typhoon Mireile

1990 Winter Storm

1989 Hurricane Hugo

1987 Storm in Europe

Worldwide Insured Natural Catastrophe Losses: By List of
Events
70

30

20

10

‐

19

Resilience comes from readiness to tackle extreme risks
 Before the crisis the sub-prime market was estimated at a value of
between USD 500 to 700 billion. This is to be compared to the total
value of US real estate market of around USD 11’000 billion

USD 50 billion
VersusUSD 160 billion

One bankruptcy
The industry seizes opportunityof hardening market

USD 700 billion
VersusUSD 11’000 billion

Most severe financial crisis
Losses in the Trillions
Huge bankruptcies

 Extreme events are part of the daily life of reinsurers. The financial
system must admit that extreme events can happen. It is the only way
to make it more resilient
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201420

Influence of the economy on a Reinsurance Company
like SCOR
Interest Rates

Investment Indices Value of bond investments
 Government bonds
 Corporate bonds (Re)Insurance business Life business Discounting of the reserves
 …

 Value of Equity investments
 Hedge fund investments
 Real estate investments
 Structured products Index Derivatives
 …

World
EconomyInflation

Credit cycle

 Severity of (Re)Insurance
losses Prices of houses and goods
 Prices of services
 Value of stabilization (index)clauses in reinsurance
treaties
 …

 Severity of the credit andsurety business Value of corporate bonds(defaults and credit spreads)
 Defaults of reinsurers or retrocessionaires
 …

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201421

Some Dependencies of Economic Variables
Corporate yieldspreadYield spreads
are a proxy forthe credit cycle

Credit cycle

Low interest
rates can cause
inflation

Interest Rates
Federal banks
may react toinflationFederal banks
may fight
recession

Real GDP

Inflation

GDP is a proxyfor growth

Investment
Index

Inflation has an
impact on
investment
valuesAdapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

22

SCOR’s models capture full circle of dependencies
between assets, liabilities and the economy
Cash flow

AssetsLines of business (LoB)

Investments

Accounting

Cash & short-term
investments
Real Estate
Funds
withheldby cedants

LoB1

Economic
Indicators

Equities
Fixed
incomeLiabilities

Alternative
Investments

LoB2

LoB4
LoB4
LoB4
LoB4
LoB9

EconomyEquity indices
GDP
Yield curves
Insurance Risk
Manager of the Year
2008

Forex

Economic
Scenario
Generator
Key proprietary
technology
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201423

Realistic Economic Scenario Generators (ESG) Since many years, SCOR has built internal models to evaluate all its
risks: underwriting, market, credit risks
 Those models integrate a high probability of extreme events and ofchanging dependence in times of crisis
 At the heart of it there is an ESG that will explore many possible paths
including severe financial and economic crises
 This ESG is based on bootstrap methods making use of a large
number of time series of financial and economic indicators
 This ESG allows us to estimate the risk of a crisis and to analyze how
our balance sheet would react to it

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201424

SCOR ESG withstands extreme scenarios
Extreme scenarios are an integral
part of our ESG

Extreme rates of 0% or below

Extreme rates of around 40%

 The ESG calculates
scenarios with interest rates
of 0% or slightly below (notbelow -1%)

 The national banking institutions
have raised the amount ofmoney in circulation on levels
not seen for decades

 Historic data shows
examples of such occasions

 Expected inflation can only befought by high interest rates

 Yen – rates fell slightly below
Zero in the early 1990’s

 Historic examples show that
extreme rates can become
reality: Mexico, Argentine,
Turkey or other EMEA-countries,
26% US Fed rate in the 1980’s,
hyperinflation of the 1920’s inGermany Swiss national bank in the
1980’s used negativeinterest rates as a tool tomake investments in Swiss
Francs unattractive to fightthe strength of the currency

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201425

Backtesting the ESG distributions of USD Equity index during
the crisis

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

26

1

The 2008/09 financial crisis – an analysis fromthe risk management point of view

2

Preparing for the next negative surprise to come3Consequences of financial crises on insurance
capital requirements

4

Giving the regulatory system enough flexibility torespond to the next crisis to come5Conclusion

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201427

An efficient regulation in time of crisis
 In time of crisis, it is too late to correct the errors of the system. One
should analyse them in order to learn from them
 It is important to adapt the solvency rules to the new situation andrestore confidence in the system
 Good risk models would show an increased risk of the situation andthus come up with higher risk adjusted capital than in quieter times
 Requiring companies to keep the same level of security than before
the crisis would require a significant increase in capital Such an increase will in turn accentuate the lack of liquidity, which is
the main characteristic of financial crisis

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201428

Examples of increased risk:
Government yield developments
Some risks are directly linked to the fall of interest rate:

Historical 10Y Government Yields

 SCOR’s life model required 17% more capital for
mortality due to the drop of interest rate. Thistranslated in a 10% more capital for the whole
portfolio

In %
9.0

8.0

 Using the same yield curve as before the crisis
would have increased the risk bearing capital by
15%. This weakening of the risk bearing capitalis due to the drop of the benefit of discounting
P&C reserves

7.0

6.0

5.0

4.0
EUR‐10Y
EUR‐10Y
3.0

GER‐10Y

Historical falls of
Government Yields

FR‐10Y
2.0

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

Oct‐11

Jun‐10Jan‐09Sep‐07

May‐06

Dec‐04

Aug‐03Mar‐02

Nov‐00Jul‐99Feb‐98Oct‐96

Source: Bloomberg a s of 06 Aug 12

May‐95

Jan‐94

Aug‐92

Apr‐91

1.0

29

Examples of increased risks:
Volatility of financial markets
 Some risks are linked to the increased volatility of financial markets
and increased credit risk:
 During the crisis the volatility of stock return more than doubled
 Credit spread sky rocketed for reinsurance to 2000 basis
points Those cumulated effects reduce significantly the solvency ratio ofcompanies. In the Swiss Solvency Test (SST), we experienced in2009 a significant drop of more than 20% in our solvency ratio eventhough there was no significant changes in our portfolio of liabilities
and our asset portfolio was significantly de-risked

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201430

Examples of increased risks: Inflation-1)

SCOR’s Economic Scenario Generator(ESG) reflected the uncertainty on
inflation at the onset of the crisis
 In an economic situation as we experienced,
with credit markets deteriorating rapidly andliquidity being dried up and countered bymassive liquidity injections by government
bodies, the risk of inflation is much higher
than in times of certainty
 A good model reflects this and implicitly
should ask for more capital to keep thesolvency level, as SCOR‘s ESG does
 If both the risk bearing capital goes down andthe risk increases  this combinationinfluences strongly the solvency margin
The empirical distribution of the simulated inflation is: Out of phase because the current interest rates are lower, Wider because the current volatility is bigger (GARCH effect)(1- Data: Number of historical data: 83 (relatively
small). Number of simulations: 60’000

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201431

Consequences of not changing the rules
 Insisting on the same level of security even if the economic situation
is rapidly deteriorating could force companies to declare insolvency
for claims they would have to pay far in the future It would also require uniformly higher capital from insurances andreinsurances forcing them to de-leverage their balance sheet andthus fueling the crisis
 At the same time this would immobilize huge amount of
supplementary capital, which in turn would pointlessly increase thecost of protections provided by insurers and reinsurers
 Moreover, it would dry out the capital available for the rest of theeconomy weakening further non-financial companies, which would, inturn, reduce the quality of the asset portfolio of insurers andreinsurers, reinforcing the vicious circle

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201432

Regulators and companies come up
with ad hoc changes in the rules
 Several proposals are put forward to come out of the dilemma ofpro-cyclicality
 Use of the swap rate for discounting instead of the risk free rate.
The argument being that this allows to account for liquidity risks
 How liquid are 30 years swap rates ? Why would swap rates bemore liquid than government bonds ? We have seen the interbank
money market collapse
 Some propose to give companies negative capital add-ons, but
nobody knows how such add-ons would work in practice other thanarbitrarily
 Some propose to suspend all together the solvency rules based onrisk models and leave it up to the regulators to let company
surviving, thus defeating the very purpose of risk-based solvency
regulation
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

33

1

The 2008/09 financial crisis – an analysis fromthe risk management point of view

2

Preparing for the next negative surprise to come3Consequences of financial crises on insurance
capital requirements

4

Giving the regulatory system enough flexibility torespond to the next crisis to come5Conclusion

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201434

Recognizing the riskiness of the situation
 The EIOPA (European Insurance and Occupational Pensions
Authority) answer to the crisis is to put forward an indiscriminate
increase of the target capital for insurance companies
 Such requirements, if they go through, would have severe social
consequences by drying even more up the liquidity of the markets
and increasing the price of insurances What is required in such situations is simply the recognition of its
riskiness and that companies have to adapt to survive it One cannot ask a ship not to pitch when sailing through rough sea
due to a storm
 Contrary to EIOPA, we think regulators should relax the rules intime of crisis and make them more stringent during good times
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201435

Efficient regulation should be contingent to the economic
situation
 Capital requirements should be adaptive and change according to theeconomic situation
 Studies-1) have shown that value-at-risk (VaR) are actually reduced
during the crisis because the probability of rebounds increases
 Currently, the risk measure adopted by Solvency II is the VaR at athreshold of 99.5%
 This threshold is arbitrarily chosen in the tail of the distribution. Thereis no convincing argument why it should be 99.5% instead of 99.4%
or 99%
 Why not then changing it according to the economic situation?

(1-

F. Beck and C. Gollier (2009)

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201436

Changing the risk measure threshold Moving from 99.5% to 99% is a simple and transparent way torecognize the reality of the economic situation: nobody can be sosafe anymore when the whole world is in turmoil
 Moreover, this change of threshold will mainly compensate in termsof capital the increase due to the recognition by the model of theincrease of the risks due to the crisis
 In SCOR’s model, it would represent a decrease of roughly 10% of
the required capital compensating the increase due to the higher
market volatility and lower interest rates
 It is important that the law sets a threshold sufficiently remote toinspire confidence in the system by all stakeholders But, it would be logical to allow the supervisory authorities to change
this, within predefined range, when times are difficult
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201437

A clear and transparent trigger A rule allowing the regulators to change the threshold of the risk
measure should be simple and based on an objective assessment of
the crisis situation
 It is always hard to set a trigger for a rule when a mere financial turmoil
turns into a crisis
 We suggest to use one of the elements in the internal model that
produces higher risks: market volatility Market volatility will affect the risks generated by the economic
scenario generator (ESG) and thus end up requiring higher capital fromthe model
 It is a measurable quantity that is highly affected by the state offinancial markets
 We propose to use twice the average yearly volatility of a chosen stock
market index
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201438

Market volatility has reached such values
only twice in the past 140 years
Yearly volatility of US stock market since 1870 (monthly data)

Return and volatility of US stock market (1870-2009)120%

120.00%100%

80%

Y e a r ly v o la tilit y (m o n t h ly d a ta )100.00%80.00%

60.00%

40.00%

20.00%

60%

0.00%-150.00%-100.00%-50.00%

40%

0.00%

50.00%

100.00%150.00%

YoY return20%

Source : IMF (2009)

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201427.02.2009

28.02.2005

28.02.2001

28.02.1997

26.02.1993

28.02.1989

28.02.1985

27.02.1981

28.02.1977

28.02.1973

28.02.1969

26.02.1965

28.02.1961

28.02.1957

27.02.1953

28.02.1949

28.02.1945

28.02.1941

26.02.1937

28.02.1933

28.02.1929

27.02.1925

28.02.1921

28.02.1917

28.02.1913

26.02.1909

28.02.1905

28.02.1901

31/02/1897

31/02/1893

31/02/1889

31/02/1885

31/02/1881

31/02/1877

31/02/1873

0%39

A simple rule
 Regulators will declare that companies would be allowed to use a VaR
at 99% for measuring their solvency for the next year if the stock index
yearly volatility reaches twice its historical average measured on a very
long period A year later, if the volatility is below this index, the regulators would
then reestablish the 99.5% threshold and ask companies to refurbish
their capital to comply with it Such a rule would allow insurance and reinsurance to use part of theircapital to face up the bad economic situation without risking to become
insolvent for liabilities they would have to pay in a distant future Given this flexibility to the system combines three advantages:
1. It works against the famous pro-cyclicality
2. It reduces the need to lock up useless extra capital
3. It is transparent by recognizing an objective situation
Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 2014

40

1

The 2008/09 financial crisis – an analysis fromthe risk management point of view

2

Preparing for the next negative surprise to come3Consequences of financial crises on insurance
capital requirements

4

Giving the regulatory system enough flexibility torespond to the next crisis to come5Conclusion

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201441

Prepare for the next crisis to come
 There will always be crisis and we will always be surprised bythem, because they reveal links that were underestimated We undoubtedly need to learn the lessons of this one to
reduce the risk of the same causes producing the same effects
 As risk manager, we need to integrate in our models areasonable probability for crisis to happen and prepare for it The Romans used to say: “si vis pacem para bellum” (if you
want peace prepare for war)
 I’ll paraphrase them: “if you want to survive a crisis you have tobe prepared for it”

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201442

Adapt the solvency regulation to it It is essential to adapt the solvency regulation to the occurrence ofcrises and to make them dynamic
 For the system to remain credible, it is important to put forward simple
adaptive rules that everybody understands and not compromising withprinciples
 Recognizing the situation and adapting the threshold of the risk
measure to it, is a simple way of fighting against the rigidity of rulesthat could destabilize the industry even further without any realjustification
 Using an independent indicator like the extreme volatility of financial
markets, avoids the blaming of any stakeholders for the decision andputs forward the objective situation

Adapting Solvency Regulation in Time of Crisis
Michel M Dacorogna
IAJ,Tokyo, Feb. 17, 201443