Recent natural disasters: A reinsurer s perspective

Transcription

1 Recent natural disasters: A reinsurer s perspective Dr. Anselm Smolka Geo Risks Research Munich Re, Munich 13th Slovenian Insurance Day Portoroz, June 1-2, 2006

2 Contents 1. Natural disasters losses and trends 2. Event portraits: Hurricane Katrina, the Kashmir earthquake, the South Asian tsunami 3. Sharing the risk 2

3 Great Natural Disasters Economic and insured losses Economic losses (2005 values) Insured losses (2005 values) Trend Economic losses Trend insured losses US$ bn NatCatSERVICE, Geo Risks Research, Munich Re 3

4 Great Natural Disasters ! Decade comparison Decade Decade Decade Decade Decade last Number Economic losses The comparison of the last ten years with the 1960s shows a dramatic increase Factor last 10: Insured losses Losses in US$bn values 2006, NatCatSERVICE Geo Risks Research, Munich Re 4

5 The frequency and size of losses due to natural disasters are increasing dramatically all over the world The reasons 160 >178bn US$ Rise in population Better standard of living Concentration of people and values in large conurbations 80 - Settlement in and industrialization of extremely exposed regions 60 - Susceptibility of modern societies and technologies to natural hazards 40 - Change in environmental conditions 20 - Increasing insurance density

6 Megacities 2015 Urban Explosion Tokyo 2015 Mexico City Los Angeles Chicago New York Sao Paulo Istanbul Paris London Rhine-Ruhr Dhaka Mumbai Delhi Kolkata Karachi Beijing Tianjin Moscow Cairo Lahore Kabul Baghdad Seoul Shanghai Osaka Jakarta Ho Chi Minh City Guatemala City Toronto Bogotá Rio de Janeiro Belo Horizonte Abidjan Lagos Luanda Tehran Jeddah Surat Yangon Bangkok Bandung Lima Santiago Buenos Aires Source: U.N. Population Division 6

7 The expansion of Mexiko City 7

8 Example Tokyo 8

9 Hurricane Katrina Satellite Image at Landfall New Orleans Biloxi Source: NASA 9

10 Cancún/Mexico after hurricane Gilbert 1988 since 1988 hotel capacity has increased by a factor of >6 10

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12 The Dec 26 th, 2004 Tsunami One of the biggest EQs recorded! How big? 12

13 Aftershocks define rupture zone Ø 1200 km of rupture Ø various minutes of rupture Ø M= Ø Up to 15 m offset of ocean floor -> Simulation 13

14 Eearthquake March 28th, 2006 and aftershocks Ø M= 8.7 Ø Very large! Ø 400 km of rupture (same as 1861!) Ø But no ocean wide Tsunami! Ø WHY? Source: USGS 14

15 Earthquake April 10th, 2006 Epicenter of M6.5 event on April 10th Within rupture zone of 1833 EQ / Tsunami 15

16 The Dec 26th, 2004 Tsunami Event characteristics > victims Economic loss US$ 9.6 bn (World Bank) Local economies affected variably World economy unaffected Insured losses < US$ 1bn (source: MR) Enormous international response more ad-hoc response than proactive prevention 16

17 The 2004 Tsunami A wake-up call... a global event a multi-line event - Personal lines - Property/Casualty Although insured losses were low, questions arose regarding the significance of truly rare disasters. 17

18 The 2004 Tsunami loss aspects Insurance losses The 2004 tsunami a global event local primary insurers (affected areas) multinational primary insurers reinsurers local primary insurers everywhere a new phenomenon 18

19 The 2004 Tsunami - loss aspects Insurance losses The 2004 tsunami a multi-line event property marine motor life health personal accident workers compensation travel insurance 19

20 Tsunami risk destruction is high 20

21 Tsunami hazard wave heights differ a lot! 21

22 What if?... tsunami scenarios worldwide 22

23 What if?... - The local risk Hazard modelling 1. tsunami generation 2. offshore topography 3. coastal topography 4. radiation pattern 5. run-up effects 6. sediment and debris impact and field (and historical) research! reconstructing past events Vulnerability assessment What is an average loss (in%)? Thai coast 2004: 4% Tsunami risk 23

24 Tsunami scenarios From an insurer s perspective the most relevant scenario may be the Eastern Mediterranean. Why? Intensive coastal development Partially high degree of insurance coverage Historical precedences. EQ 365 A.D.. EQ and several local events 24

25 Tsunamis in the Mediterranean 25

26 Earthquake and tsunami 365 AD 26

27 The Kashmir earthquake, Oct 8,

28 The Kashmir earthquake Magnitude 7.6 Victims 88,000 Injured 200,000 Homeless 3,000,000 Economic loss 5.2 bn US$ Insured loss 0 28

29 MR-Anteil (in USD)

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31 31

32 Hurricane Katrina, Aug 25-30, 2005 New Orleans Biloxi Source: NASA 32

33 Coastal Storm and Storm Surge Impacted Areas as Defined by FEMA Sources: ESRI, FEMA

34 Storm and surge damage at Biloxi, Mississippi l l 34

35 Storm and surge damage at Biloxi, Mississippi l l l l 35

36 Hurricane Katrina: Loss Examples Casino Barges 36

37 New Orleans Flooded Areas 37

38 Offshore and Onshore Energy Losses 38

39 Modelling Offshore Oil Platform Losses: Distribution of Insured Values Insured Values (in m US$) - 2 >2-5 >5-10 >10-20 >20 Shell Platform 39

40 Hurricane Katrina: The biggest natural disaster in the US since Earthquake Hurricane Katrina 2005 Loss of GDP 1.8 % 1 % Loss of property premium? 10 % Loss bn US$ (in today`s values) 125 bn US$ Insured loss bn US$ 60 bn US$ (incl. 15 bn NFIP) 40

41 Hurricane Katrina: The case for large loss amplification - Physical loss drivers - Non physical loss drivers - Insurance-specific loss drivers 41

42 Hurricane Katrina: Physical loss drivers - Storm surge Highest surge since the beginning of observations in Levee breaks - Vulnerability 42

43 Hurricane Katrina: Non physical loss drivers - Repair cost inflation + labour cost ( demand surge ) - Economic disruption - Lifeline damage - Loss of work force - Inaccessability - Oil industry ripple effects 43

44 Hurricane Katrina: Insurance specific loss drivers - Claims handling -> High number of claims -> Wind or water damage? - Scope of coverage -> Contingent business interruption -> Customers and suppliers extension -> Loss of market 44

45 Risk financing and risk control The principle of risk partnership A holistic risk management requires sharing the risk between 160 >178bn US$ Insured Insurer State Reinsurer Capital market, banks

46 Risk Partnership The insured s tasks - Loss prevention - Loss minimization - Self-participation 46

47 Risk Partnership The insurer s tasks - Separate insurance with clear conditions - Adequate price - Separate accounting - Accumulation control - Technical underwriting guidelines - Limitation of liability (retention of insured; reinsurance) - Formation of natural perils reserves 47

48 Risk Partnership The role of reinsurance - Capacity for rare, large-scale catastrophic losses through global balance of risks. Single objects (industrial plants). Accumulation losses (natural disasters) - Education and knowledge transfer - Technical support and innovation in insurance solutions for catastrophe risks, drawing on the unique and long-term experience regarding catastrophe losses - Maximizing the role of the private sector in catastrophe insurance 48

49 Risk Partnership Capital markets - Supplementary (rather than alternative) capacity => ART. Cat bonds betting against disasters. SWAPs - earthquake Tokyo against windstorm Europe. Weather derivatives Mortgage banks - Code compliance and disaster insurance as a precondition for housing loans (Israel, Colombia, Greece.) 49

50 Risk Partnership The state s tasks - Land use regulations and building codes - Ensure that regulations are observed - Measures to protect the infrastructure (e.g. dams/dykes, water-retaining basins) - Favourable tax treatment of natural perils reserves 50

51 The principle of risk partnership A holistic risk management requires sharing the risk between Loss State Capital Market Reinsurer Insurer Insured ,000 10,000 Return period (years) 51

52 Risk control Insurance measures Adequate pricing 160 Substantial deductibles, based on the respective exposure Liability limits 140 Accumulation control 120 clear policy wording 100 Improved claims settlement Exclusion 80 of particularly exposed areas Exclusion of certain hazards 60 >178bn US$ 40 Reinsurance, retrocession Catastrophe reserves 20 0 Loss prevention

53 Risk evaluation The risk model MRHazard Risk = Hazard Vulnerability Values Hazard information Grofl st dte L ndergrenzen Fl sse Seen VGV - EUE < > in TDM keine Daten Hamburg Bremen Individual exposure Berlin Hannover Duisburg Dortmund Essen Leipzig D sseldorf Kˆ ln Frankfurt am Main Value distribution Set of scenarios Expected loss or loss occurrence probability Stuttgart M nchen 0 Vulnerability function Risk curve 150 Kilometers Statistics 53

54 Great historical earthquakes in Slovenia Year Region max. Intensity 1000 SE IX? 1081 E Ljubljana VIII 1508 Ljubljana VII Idrija IX 1575 Ljubljana VII Ljubljana VII Ljubljana VII Krsko VIII 1684 Ljubljana VII Ljubljana VIII-IX 1917 Krsko VIII 1998 Bovec VII-VIII 54

55 The Idrija fault source of large earthquakes The Idria fault: source of large earthquakes 55

56 Conclusions The lessons of recent disasters: Think the unthinkable! A great earthquake in Slovenia could cause a total economic loss in the bn range A case for large loss amplification? 56