Catastrophic Risks - Do We Have Enough Protection Reinsurers View - IV. International Istanbul Insurance Conference - Jürgen Brucker (2014)

1. Catastrophic risks – do we have enough
protection reinsurers view
IV. International Istanbul Insurance Conference
Istanbul, 25th September 2014
Jürgen Brucker
Image: used under license from Shutterstock.com

2. 1. Insurance in the Turkish market versus Eastern European markets
2. Future scenario of the Turkish market
3. Loss events worldwide 1980 – 2013
4. Loss examples and their economical impact/effect
5. Current position - cession rates / equity
6. Current catastrophic coverage
7. Nat cat models and their limitations
8. Summary and outlook
Agenda
22/09/2014 2Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker

3. Insurance in the Turkish market versus Eastern
European markets
Image: -Oxford- / GettyImages

4. Development of Eastern European markets with
respect to primary insurance penetration in a global
perspective
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 4Source: Munich Re Economic Research
Per-capita income and primary insurance Non-Life penetration
Belarus
Austria
Belgium
Brazil
Bulgaria
China
Croatia
Czech Republic Denmark
Finland
France
Canada
Germany
Australia
Greece
Hungary Estonia
India
Ireland
Italy
Japan
Latvia
Mexico
Poland
Portugal
Russia Slovakia
Slovenia
South Africa
Spain
Israel Sweden
Turkey
Romania
Ukraine
United Kingdom
United States
0,5
0,0
1,0
1,5
2,0
2,5
3,0
3,5
4,0
4,5
5,0
0 10.000 50.000
PenetrationNon-Life(%)
20.000 30.000 40.000
GNI per Capita in purchasing power parities (PPP-US$)
year: 2013

5. Nearly 7% of the global gross domestic product arises
from Eastern Europe, in 2013 more than € 3.7 tn
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 5
Regional split of global GDP 2013, in % Regional split of population
2013, in %
MENA 4.8
Sub-Saharan
Africa 2.0
LatinAmerica
8.0 NorthAmerica
24.9
Western
Europe 22.6
Eastern
Europe 6.7
MatureAsia/
Pacific 11.9
Developing
Asia 19.0
Eastern
Europe 6.0
Western
Europe5.7
North
America 4.9
MENA 6.3
Sub-Saharan
Africa 12.3
LatinAmerica
8.6
Mature Asia/
Pacific 3.5
Emerging
Asia 52.6
Total: € 56,232 bn Total: 7.1 bn
Source: Munich Re Economic Research, IHS Global Insight

6. Russia accounts for more than 40% of total Eastern
European GDP with the second largest economy,
Turkey, lacking far behind
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 6
Hungary 2.6
Poland 10.2
Czech Republic 4.0
Slovakia 1.9
Rest of Eastern Europe
22.8
Russia 42.0
Turkey 16.6% or
€627bn
GDP share within Eastern Europe 2013, in %
Total: € 3,774 bn
Source: Munich Re Economic Research, IHS Global Insight

7. Poland is remarkably strong in Life business, but
Russia is still dominating Eastern European insurance
markets in general
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 7
8,2 3,8
19,1
30,1
3,0
13% or
€9.4bn
22,9
Hungary
Russia
Turkey
7,4
2,5
15,0
35,3
2,0
14,7
23,1
Czech Republic
Hungary
Poland
Russia
Slovakia
Turkey
Rest of Eastern
Europe
11,9
7,9
34,0
7,0
6,5
10,6
22,1
Czech Republic
Hungary
Poland
Russia
Slovakia
Turkey
Rest of Eastern
Europe
Regional split of primary insurance premiums 2013 Eastern Europe, in %
Life: € 19 bn
P&C: € 48 bnTotal: € 72 bn*
Czech Republic
Poland
Slovakia
Rest of Eastern Europe
* Including Health insurance
Source: Munich Re Economic Research

8. The Czech Republic has the highest insurance density
and penetration in P&C, Slovakia in Life respectively
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 8
18
14
166
148
223
211
0 100 200 300
Slovakia
Czech Republic
Poland
Hungary
Turkey
Russia
1,7
1,6
1,5
1,5
0,5 1,0 1,5 2,0
Slovakia
Poland
Hungary
Czech Republic
Turkey 0,2
Russia 0,1
0,0
1,8
2,4
0,0
1,3
1,2
1,1
1,1
1,0 2,0 3,0
Czech Republic
Poland
Slovakia
Hungary
Turkey
Russia 94
121
119
188
176
338
0 100 200 300 400
Czech Republic
Poland
Slovakia
Hungary
Russia
Turkey
Insurance penetration P&C 2013, in % Insurance density P&C 2013, in €
Insurance penetration Life 2013, in % Insurance density Life 2013, in €
Primary insurance penetration (premiums in % of GDP) and density (premiums per capita)
Source: Munich Re Economic Research

9. Country profile
Turkey
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 9
0
2.000
4.000
6.000
8.000
10.000
Development of premiums, in € mn
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Life Non-Life
Real growth of GDP and premiums, in %
Non-Life Line of business split 2012, in %
20
15
10
5
0
-5
-10
Forecast
51%
20%
6%
4%
12%
2%
0% 4%
1% 0% 1%
Property
Accident
WorkersComp.
Credit
Legal Exp.
Motor
Engineering
Health
General Liability
MAT
Other
2009 2010 2011 2012 2013 2014 2015 2016
GDP, real (% change, p.a.) Life premiums, real growth (in % p.a.)
P&C premiums, real growth (in % p.a.)
Source: Munich Re Economic Research
Insurance market Turkey

10. Future scenario of the Turkish market
Image: used under license from Shutterstock.com

11. 16,6
13,8
9,2
18,9
13,7
10,3
17,9
16,3
13,3
12,9
14,6
12,6
24,3
20,2 19,6
21,5
23,1
16,2
28,1
24,1
27,0 27,8
30,4
22,2
5,0
0,0
10,0
15,0
20,0
25,0
30,0
35,0
Czech Republic Hungary Slovakia TurkeyPoland Russia
1990 2000 2010 2020e
Strong growth of Gross national income per capita
since 2000 in all Eastern Europe countries
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 11
Gross national income per capita, in ‘000 PPP* USD (purchasing power parity)
* Purchasing Power Parity (PPP) - A rate of exchange that accounts for price differences across countries allowing for international comparisons of income
and prosperity levels. At the PPP US$ rate, PPP US$1 has the same purchasing power in the domestic economy as $1 has in the United States.
Source: Munich Re Economic Research, World Bank

12. Several Eastern European countries are top
global growth primary insurance markets over the
projection period
Source: Munich Re Economic Research
* Based on the 50 largest insurance markets in 2013 according to premium volume (for P&C and Life, respectively)
**Compound Annual Growth Rate (CAGR) = annual average growth rate 2014– 2020
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
India
Indonesia
China
Malaysia
Turkey
Colombia
Singapore
Mexico
Russia
Thailand
United Arab Emirates
Poland
Brazil
Israel
South Africa
South Korea
Argentina
Iran
Taiwan
Ireland
Norway
Australia
UnitedStates
Venezuela
Switzerland
10.1
9.5
8.3
6.8
6.5
6.2
6.1
5.9
5.7
5.5
5.3
5.0
5.0
4.6
4.5
3.7
3.3
3.2
2.8
2.6
2.5
2.5
2.4
2.3
2.2
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Indonesia
Brazil
China
India
Colombia
Thailand
Poland
Philippines
Malaysia
Chile
Mexico
Luxembourg
Portugal
Israel
Russia
Norway
Argentina
Singapore
Hong Kong
Taiwan
South Africa
South Korea
Sweden
Italy
United States
14.9
11.7
11.0
10.2
9.0
8.8
8.7
7.6
6.7
6.6
6.3
4.8
4.3
4.3
4.3
4.0
4.0
3.9
3.8
3.8
3.1
3.1
3.0
2.9
2.5
Top 25 countries* according to real (inflation adjusted) CAGR** 2014 - 2020, in %
P&C Life
22/09/2014 12

13. Stronger Growth in Life than in P&C business is
expected
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 13
Expected Life and P&C real (inflation adjusted) growth of PI premiums until 2020, in %
0,00
5,00
10,00
15,00
0,00 5,00 10,00 15,00
Real CAGR*
Life 2014-2020
Real CAGR* P&C
2014-2020
Poland
Slovakia
Czech
Rep.
Turkey
Russia
Size of bubble:
total (Life and Non-
Life) primary
insurance premium
volume 2013
*inflation adjusted compound average annual growth rate
Slovenia
Hungary
Estonia
Ukraine
Latvia
Lithuania
Source: Munich Re Economic Research

14. Loss events worldwide 1980 – 2013
Image: used under license from Shutterstock.com

15. Loss Events Worldwide 2013
Geographical overview
22/09/2014 15
Hydrological events
(flood, mass movement)
Geophysical events
(earthquake, tsunami, volcanic activity)
Natural
catastrophes
Selection of significant
loss events
880 Loss events
Earthquake
China, 20 April
Hailstorms
Germany,
27–28 July
Severe storms,
tornadoes
USA, 18–22 May
Winter Storm Christian (St. Jude)
Europe, 27–30 October
Typhoon Haiyan
Philippines, 8–
12 NovemberSevere storms, tornadoes
USA, 28–31 May
Hurricanes Ingrid &
Manuel
Mexico, 12–19 September
Floods
India, 14–30 June
Heat wave
India, April–June
Typhoon Fitow
China, Japan, 5–
9 October
Earthquake (series)
Pakistan, 24–28 September
Floods
Australia, 21–
31 January
Floods Meteorite impact
Europe, 30 May–19 June Russian Federation, 15 February
Floods
Canada, 19–24 June
Flash floods
Canada, 8–9 July
Floods
USA, 9–16 September
Meteorological events
(storm)
Climatological events
(extreme temperature, drought, wildfire)
Extraterrestrial events
(Meteorite impact)
Global Natural Catastrophe Update
Source: Geo Risks Research, NatCatSERVICE – As at January 2014, © 2014 Munich Re

16. Loss events worldwide 1980 – 2013
Number of events
NatCatSERVICE
200
400
600
800
Number
1000
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
Hydrological events
(flood, mass movement)
Geophysical events
(earthquake, tsunami, volcanic activity)
Meteorological events
(storm)
Climatological events
(extreme temperature, drought, wildfire)
© 2014 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at February 2014 22/09/2014 16

17. 100
200
300
bn US$
400
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
Loss events worldwide 1980 – 2013
Overall and insured losses
NatCatSERVICE
Overall losses (in 2013 values)* Insured losses (in 2013 values)*
*Losses adjusted to inflation based on country CPI.
© 2014 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at February 2014 22/09/2014 17

18. Source: Munich Re, NatCatSERVICE, 2014
Date Event Affected area
Overall losses
in US$ m
original values
Insured losses
in US$ m
original values
Fatalities
25-30.8.2005
Hurricane Katrina,
storm surge
USA: LA, New Orleans, Slidell; MS, Biloxi,
Pascagoula, Waveland, Gulfport; AL; FL
125,000 62,200 1,322
11.3.2011
Earthquake,
tsunami
Japan: Honshu, Aomori, Tohoku; Miyagi, Sendai;
Fukushima, Mito; Ibaraki; Tochigi, Utsunomiya
210,000 40,000 15,880
24-31.10.2012
Hurricane Sandy,
storm surge
Bahamas, Cuba, Dominican Republic, Haiti,
Jamaica, Puerto Rico, USA, Canada
68,500 29,500 210
6-14.9.2008 Hurricane Ike
USA, Cuba, Haiti, Dominican Republic, Turks and
Caicos Islands, Bahamas
38,000 18,500 170
23-27.8.1992 Hurricane Andrew USA: FL, Homestead; LA; Bahamas 26,500 17,000 62
1.8-15.11.2011 Floods
Thailand: Phichit, Nakhon Sawan, Phra Nakhon Si
Ayuttaya, Pathumthani, Nonthaburi, Bangkok
43,000 16,000 813
17.1.1994 Earthquake
USA: CA, Northridge, Los Angeles, San Fernando
Valley, Ventura, Orange
44,000 15,300 61
7-21.9.2004
Hurricane Ivan,
storm surge
USA, Caribbean, Venezuela, Colombia, Mexcio 23,000 13,800 120
22.2.2011 Earthquake New Zealand: Canterbury, Christchurch, Lyttelton 16,000 13,000 185
19-24.10.2005 Hurricane Wilma Bahamas, Cuba, Haiti, Jamaica, Mexico, USA 22,000 12,500 42
Significant loss events worldwide 1980 – 2013
10 costliest events ordered by insured losses
NatCatSERVICE
© 2014 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at February 2014 22/09/2014 18

19. The most expensive natural catastrophes ever
“recorded” took place in the largest economies in
absolute terms
19
214
151 147
91 112
250
200
150
100
50
0
Japan 2011
(earthquake and
tsunami)
Japan 1995
(earthquake)
USA2005
(Hurricane Katrina)
China 2008
(Earthquake
Annual average 1980-
2012
The four natural catastrophes with the highest overall losses in US$ bn (in 2012 values)
The four natural catastrophes with the highest insured losses in US$ bn (in 2012 values)
73
31 30 28 29
80
60
40
20
0
USA2005
(Hurricane Katrina)
Japan 2011
(Earthquake and
tsunami)
USA, Karibik 2012
(Hurricane Sandy)
USA1992 Annual average 1980-
(HurricaneAndrew) 2012
Source: Munich Re Geo Risks Research, Economic Research 22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker

20. Loss examples and their economical impact/effect
Image: Munich Re

21. The overall economic effect results from both the direct
and the indirect effects
21
Economic effects of natural catastrophes
Overall effect
Direct losses
 Direct consequences of
the forces of nature
 Usually not directly
evident from the
development of GDP*
 Personal injury
 Direct economic losses,
e.g. damage to capital
assets and resources
Indirect effects = “positive” + negative indirecteffects
 All effects not caused directly by the natural catastrophebut
by the resultant direct losses
 Indirect effects are usually changes in GDP comparedwith
the hypothetical development of GDP in the absence of a
natural catastrophe
“Positive” indirect effects,
e.g. through
 Reconstruction stimulus
 “Prosperity incentives”, e.g.
construction of new, better-
quality houses
 “Creative destruction”, e.g. the
destruction fosters innovation;
new production facilities are
more modern than those
destroyed
Negative indirect effects,
e.g. through
 Loss of production due to
destroyed installations
 Degradation of human capital
 Damaged and destroyed
infrastructure
 Often higher inflation
 Frequently, an increase in
government debt
*) Exemptions are droughts and heat waves which directly impair GDP
Source: Munich Re Economic Research 22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker

22. Industrialised economies Emerging economies Developing economies
Natural catastrophes represent a great economic
challenge, particularly for emerging economies
22
Distribution of direct losses* across country groups
3,0%
Average percentage of direct
losses with respect to GDP
2,5%
2,0%
1,5%
1,0%
0,5%
0,0%
*) Only natural catastrophes included in Munich Re’s catastrophe classes 4-6 are shown here. Emerging economies are those countries whose inhabitants have a “middle” per-
capita income on average. According to the World Bank, middle income is between US$ 1,036 and US$ 12,615 (based on 2012 figures). Countries with lower average income are
referred to as developing economies here, and countries with higher income as industrialised economies; source: Munich Re NatCat SERVICE, Economic Research

23. The Marmara earthquake in Turkey in 1999
caused widespread damage including to 32% of the
production facilities
23
 Direct economic losses:
US$ 12bn
 Of the 1,062 companies
located in the Kocaeli
region, 345 (32%) were
damaged
 On average, these
companies were out of
production for 35 days
 It was not until 18 months
after the earthquake that
capacity utilisation returned
to levels roughly similar to
those seen prior to the
catastrophe
Source: Munich Re Geo Risks Research, Economic Research, Claas Menny (2011): Effects of natural catastrophes on
companies: An empirical study of the Maramara earthquake from 17 August 1999, dissertation, KIT;
Image: dpa Picture Alliance / Pierre Verdy
22/09/2014

24. 24
Example: Although the earthquakes in Haiti and New Zealand were of
roughly similar strength, the effects in Haiti were far worse, i.a. due to the
relatively lower level of insurance penetration
Haiti earthquake (2 Jan. 2010)
Magnitude 7.0
New Zealand earthquake (4 Sep. 2010)
Magnitude 7.1
-0.4% of GDP
100,000
0
Cumulative indirect
effect**
Houses damaged
Fatalities
US$ 200m (2.5%*)
285,000
222,570
(2.5% of the population)
Insured losses
Houses destroyed
Fatalities
US$ 8bnOverall losses US$ 6.5bnOverall losses
-3.5% of GDP
Cumulative indirect
effect**
US$ 5.2bn (80%*)Insured losses
*) Ratio of insured losses to overall losses, **) Calibration based on von Peter, von Dahlen and Saxena (2012): Unmitigated Disasters? BIS Working papers No. 394.
Source: Munich Re Geo Risks Research, Economic Research; source right-hand photo: National Geographic, UN Development Programme, IFRC;
Image: Benjamin J. Myers / Corbis Image: dpa Picture Alliance / David Alexander
22/09/2014

25. 25
Example: Hurricane Gustav caused higher absolute damage in the USA,
but lower relative damage than in Jamaica. This is explained, in part, by the
countries’ respective absolute economic strength and economic level of
development
USA Jamaica
US$ 4.3bn
0.03 %
11
Overall losses*
Overall losses
(relative to GDP)
Fatalities
US$ 14,292bn
US$ 43,161
GDP 2008*
GDP per capita
2008**
US$ 0.21bn
1.5%
15
Overall losses*
Overall losses
(relative to GDP)
Fatalities
US$ 14bn
US$ 7,437
GDP 2008*
GDP per capita
2008**
*) In original values, **) In 2005 values and purchasing power parity; source: Global Insight, “Tropical Cyclone Report:
Hurricane Gustav” from the National Hurricane Center; Munich Re Geo Risks Research, Economic Research;
Image: dpa Picture Alliance / Landov Bates Image: dpa Picture Alliance / Collin Reid
22/09/2014

26. 26
In emerging economies, government debt often rises
significantly following natural catastrophes*
Per-capita debt in
industrialised economies
Years after
catastrophe
“Confidence
band” for
estimate
60%
40%
20%
0%
Hypothetical development without
catastrophe = trend =baseline50%
0%
-50%
-100%
-150%
Per-capita debt
in emerging economies
 Figure on the left: for industrialised economies there is no statistically significant deviation inper-
capita debt versus its trend (=“baseline”) after the natural catastrophe takes place in “year 0”
 Figure on the right: emerging economies must expect on average a statistically significantincrease
in per-capita debt (nearly 30% after fiveyears)
Source: Melecky M. et Raddatz C.(2011): How Do Governments Respond after Catastrophes? World Bank; Munich Re Economic Research;
*) In this analysis, only weather-related (climatic) natural catastrophes is accounted for 22/09/2014

27. Example: In Chile, government borrowing increased by
around 70% in the earthquake year of 2010
27
-40
-20
0
20
40
60
8016000
14000
12000
10000
8000
6000
4000
2000
0
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Government debt (left axis))
Growth rate of government debt (rightaxis)
Government debt Chile
in bn pesos
Start of 2010:
Earthquake in Chile
Source: Munich Re Economic Research, IMF 22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker

28. Insurance cover significantly helps economic recovery
following a natural catastrophe
22/09/2014 28Source: MR Economic Research; graph based on Hallegatte S. et al. (2010): "The Economics of Natural Disasters“.
 Besides the direct losses from anatural
catastrophe (e.g. buildings destroyed),
there are also indirect losses (e.g. loss
of production in a destroyed factory),
which can seriously impact economic
output in subsequent years
 "Positive" indirect effects (e.g.
reconstruction boosting the economy)
cannot usually compensate for the
"negative" indirect effects
 Insurers provide funds, thus limiting
indirect losses
 Three scientific studies of recent yearsall
came to the same conclusion: Higher
insurance market penetration helps to
overcome the indirect consequences of
natural catastrophes
Illustration of indirect effects in the short
and medium term
Hypothetical GDP development without catastrophe
GDP development in countries with low insurance market penetration
GDP development in countries with high insurance market penetration
GDP
level
Time
Occurrence
of catastrophe
End of
reconstruction
Several years
Increase in GDP from the
economic stimulus of
reconstruction
(= indirect positive
effects)
GDP losses following the
catastrophe
(= indirect negative
effects)

29. Current position - Cession rates / equity
Image: used under license from Shutterstock.com

30. Business model appears to be more relevant than
company size in explaining cession rate
22/09/2014 30…
US personal
US commercial
Global diversified
Bermuda
Bancassurer
EU diversified
Lloyds
Emerging markets
Japanese
Chinese
Other
60%
50%
100
40%
30%
20%
10%
0%
3020
Quantitative analysis: Size vs. cession per business model
Non-Life cession rate
40 50 60 70 Size
Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker
US Comm.
US Pers.
EU divers.
Global divers.

31. Equity development does historically not reflect
business growth – Equity to NWP-Ratio declines
over time
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 31
Turkey Equity position of NL insurance companies
6,3
6,7
10,0
12,4
5,7 5,6 5,1
110%
83%
103%
51%
41%
47%
0%
20%
40%
60%
80%
100%
120%
4,0
6,0
8,0
10,0
12,0
14,0
16,0
2007 2008
5,0 5,1
2009 2010 2011 2012 2013
BnTRY
Equity vs Net Written Premium
14,5
NWP
6,9
Equity
Equity / NWP in %
Source: Hazine

32. The current Turkish cession behavior currently
does not reflect capital intensity following Solvency II –
22/09/2014 32
excl. Cat
Cession Ratios vs Solvency II Capital intensities
22%
96% 96%
78%
4% 4%
Fire & Gen Dmg* MoD
Retained
MTPL
Cession
Ceded and retained Business
SII Capital necessary per premium unit written
* Including Engineering and Subsidized Agriculture Insurance ** per 100 TRY, 3 yrs development, after Diversification
Source: Hazine, Munich Re analysis
21% 26% 22%
12%
28%33%
54%
28%
6%
Fire and Gen Dmg* MoDMTPL
Premium Reserve

33. Current catastrophic coverage
Image: used under license from Shutterstock.com

34. NatCat Capacity
(without faculative and int. Programs)
 Additional € 2-3bn for
facultative covers and int.
programs to be added
 EQ Japan - €55bn w.o.
Government scheme
 Demand for RI is smaller as
some programs from int.
comp. are placed with H.O.
 Low retention levels in
proportional covers
 Low attachment pointsfor
Cat XL covers
 Further substantialincrease
expected from TCIP
(currently 6,5mio insured –
2017:9 - 10mio)
 Subdued growth rate due to
depreciation of TRY vs €
Others
Fire prop.
Eng. prop.
Others
Fire prop.
Eng. prop.
Others
Fire prop.
Eng. prop.
M
M M
TCIP
TCIP
TCIP
Cat XL
Total
Cat XL
Total
Total
12
0
2
4
6
8
10
12
Cat XL
Total
20152012 2013 2014
Split of Nat Cat capacity requirements
€ bn
14
Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 22/09/2014 34

35. Nat cat models and their limitations
Image: used under license from Shutterstock.com

36. Vendor models
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 36
Multi-Model Comparison

37. Seismic Hazard Vulnerability Exposure
Model components
22/09/2014Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 37

38. Seismic Hazard
Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker 22/09/2014 38
Ground Motion Prediction Equation (GMPE):
selection, applicability, calibration,
uncertainty…
Site effects:
global and regional studies, Vs30 maps
(resolution)

39. Vulnerability
 Regional differences
 Building stock (building height distribution). Ground motion response
(pga, 1 s…)
 Construction year, building codes
 Retrofing, special seismic devices
 Mean damage ratio (converting damage to economical loss)
 Historical losses/calibration
 Construction/reconstruction labor costs
 Uncertainty
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40. Vulnerability
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Construction year, building codes

41. Exposure
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 Distribution of insured values
 GIS information
 Building stock: distribution
per regions/countries,
differences rural and urban
areas. Use of Cadaster
information. Distribution of
building heights.
 Cultural/regional differences
 Detailed information fromour
clients

42. Exposure
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Building stock: distribution per regions/countries, rural and urban areas differences.
Example:
% of buildings with masonry walls and wood
by municipalities (no main cities)
Source: DANE, dane.gov.co

43. Summary and outlook
Image: used under license from Shutterstock.com

44. Summary and outlook
 Overall  strengthen capital position of Turkish insurance companies
 Following the introduction of a new solvency regime  re-thing cession practice
 Standard Turkish EQ model (vendor or own) is needed and to be used
 Currently  nat cat model uncertainties are to be considered
 Lower model uncertainties be means of improved data quality
 Improve risk assessment and risk management procedures especially for highly
exposed risks and industries
 Consider additional balance sheet protection cover
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22/09/2014 45Catastrophic risks – do we have enough protection reinsurers view / Jürgen Brucker