Insurance: Limiting the Impact of Natural Catastrophes on the Balance Sheet. Dr. Oliver Kübler Dr. Matthias Schaub

Transcription

1 Insurance: Limiting the Impact of Natural Catastrophes on the Balance Sheet Dr. Oliver Kübler Dr. Matthias Schaub

2 This has only been possible by insurers. They are the ones who really built this city. With no insurance, there would be no skyscrapers. No investor would finance buildings that one cigarette butt could burn to the ground (Henry Ford) Engineering Insurance Finance Insurance enables technological progress 2

3 Losses in USD bn Costs of Natural Catastrophes & the Protection Gap Protection gap 3

4 Global Insurance Industry Losses in USD mn 15 yr average annual loss burden 15 yr highest annual loss burden Man-Made 6,406 9,432 1) Nat Cat 43, ,595 1) excl. terror Variance or volatility of Nat Cat loss is much higher than man-made, so called long-tail distribution for cat events Because of high volatility and sometimes very low frequency of events, sophisticated models are require to better understand the solvency events 4

5 (Re)insurance makes Society more Resilient Christchurch, New Zealand 2011 Extensive offshore reinsurance will fund a substantial share of the rebuild costs and thus has helped reduce the financial impact on New Zealand. Comparisons with other major natural disasters suggest that the widespread coverage of insurance, particularly accompanied by reinsurance overseas, has helped to mitigate the longer-term adverse economic effects of the earthquakes. Reserve Bank of New Zealand 5

6 (Re)insurance makes Society more Resilient Country Chile 2010, M8.8 Haiti 2010, M7.0 Shake map maps shown in same scale Fatalities ,570 Economic loss: USD 30 bn (12% of GDP) USD 10 bn (136% of GDP) GDP (2011): USD 249 bn USD 7.3 bn 6

7 Nat Cat Modelling and Control of Losses 7

8 NatCat risk assessment: Premium income vs. losses Fire: Natural catastrophes: 8

9 The 4-Box Principle - Earthquake Hazard Vulnerability Value Distribution Insurance Conditions How often? How strong? What degree of damage? What is covered - where? What is covered - how? 9

10 Hazard Vulnerability Value Distribution Insurance Conditions Historic earthquakes in Japan Magnitude > 5.0 Depth < 70km Years 0 to 2013 Visualized in SwissRe CatNet

11 Hazard Vulnerability Value Distribution Insurance Conditions Generating a Probabilistic Event Set Fault Interface Background 240 fault models Model parameters (geometry, max magnitude, frequency) consistent with JSHIS M9-class event incorporated Stochastic background events being consistent with historical catalogue New probabilistic event set combines latest knowledge on Japanese Earthquake hazard with latest earthquake modeling technology. 11

12 loss Hazard Vulnerability Value Distribution Insurance Conditions Hazard Uncertainty Ground motion equations include hazard uncertainties (inter and intra event) ln I = g M, R + ε inter + ε intra, ε normally distributed Expected loss is a function of the hazard and the vulnerability/loss function E L = Ω L im f IM im dim 12

13 Hazard Vulnerability Value Distribution Insurance Conditions Hazard Comparison to JSHIS JSHIS Swiss Re JMA Intensity, at 475 year return period on amplified soil 13

14 Hazard Vulnerability Value Distribution Insurance Conditions figure: Weatherill, Silva, Crowley, Bazzurro (2015) The vulnerability curves define the relationship of hazard and damage/loss The vulnerability is defined by: Hazard intensity Coverage Risk category (Occupancy) Quality/age (Protection)/Preparedness Construction type Building height Vulnerability Region etc. 14

15 Hazard Vulnerability Value Distribution Insurance Conditions Structure types perform differently during earthquakes, compare e.g. steel and unreinforced masonry Source: Kam et al. 2011, Data source: Christchurch City Council 15

16 Hazard Vulnerability Value Distribution Insurance Conditions Value distribution is the driver for correlation between assets accumulation for insurer relevance of protection measures. Accuracy of provided geographic information (latitude/longitude) is key 16

17 Hazard Vulnerability Value Distribution Insurance Conditions Insurance conditions (deductible, limits, sub-limits) will be applied to each simulated event This will drive the shape of the loss distribution function and hence the credit on premium 17

18 Known Limitations of Earthquake Models All models have limitations, Many limitations are known (by model developers and users) Until recently none of the vendor models considered Tsunami! Most models neglect or do not consider aftershocks resulting in underestimation of risk Earthquake models, in general, produce more reliable results in assessing risk to a population of structures and/or with a simpler coverage (e.g. physical damage) compared to a single risk with a complex coverage (e.g. business interruption) Exchange between model developers and underwriters is key! 18

19 Event set based Accumulation Control Event 1 Event 2 Event Event 1'000'000 We use event-based simulations All insurance conditions can be applied where appropriate (coverage, location, policy, ). Output is a huge loss table called the event loss table By doing so correlation can be considered! Risk 1 Risk (multi-location) 345 BU l Desk m Acceptance n 479 Risk 100 BU o Desk p 43 Acceptance q 76 (large treaty) BU i Desk j Acceptance k BU r Desk s 120 Acceptance t Risk 1'000'000..

20 Tsunami and Volcano Hazard Tsunami Global volcano hazard layer First-in-Industry Calculated inundation for Tohoku earthquake reflects observations. New Tsunami model is fully-coupled with earthquake shock model. Model was available for 2012 renewable and especially helped clients with coastal exposure Global Volcano ash fall hazard layer,

21 CatNet Swiss Re s Natural Hazard Platform M w 7.0, Earthquake, Kumamoto, Kyushu, Japan, source: CatNet, USGS 21

22 Flood Risk & Risk Awareness 22

23 The 10 largest Flood Events (Insured Losses ) In Billion USD (in 2015 prices) Insured Loss Total economic loss 2011 Thailand Germany & Czech Republic Germany & Czech Republic UK Switzerland Australia Poland & Czech Republic UK Australia US Source: Swiss Re Economic Research and Consulting 23

24 Don Muang Airport in northern Bangkok, Nov. 3, 2011 Duration: July - November 2011 Economic loss: USD 48.4bn (Swiss Re: Sigma-explorer 2016) Insured loss: USD 15.8bn (Swiss Re: Sigma-explorer 2016) 24

25 Flood Central Europe, Germany, June 2013 Duration: 27 May 2013 till 20 June 2013 Economic loss: USD 16.8bn (Swiss Re: Sigma-explorer 2016) Insured loss: USD 4.2bn (Swiss Re: Sigma-explorer 2016) 25

26 River / Flash Flood: Forecast on precipitation extremes Increase in 1-in-5 year return intensities for 1 day events Based on 10 regional climate models (including KNMI's RACMO2.1) Results imply a rising probability of more intense extreme precipitation events (in autumn, winter and spring) and extended dry spells in the summer months Source: Rajczak, J., P. Pall, and C. Schär (2013), Projections of extreme precipitation events in regional climate simulations for Europe and the Alpine Region, J. Geophys. Res. Atmos., 118, , doi: /jgrd

27 River / Flash Flood: Representative client's exposure by Flood Zone Limited assets within highly exposed flood risk zones However, 3% of the clients assets will be affected with high frequency and will drive the overall expected annual loss Suppliers often face the same issue and create a supply chain risk for your production process Sum insured by Zone 82% 3% 7% 8% Expected Loss by Zone 44% 25% 25% 50 year 100 year 500 year outside 50 year 100 year 500 year outside 6% 27

28 Increase flood protection of 3% of assets to 100yr level Increase flood protection to 10% of assets to 250 yr level Establish proper on-site risk management incl. BCP River / Flash Flood: Economics of flood protection and risk management Expected flood loss (no measures) Expected flood loss (various measures) -16% -22% -10% to -15% Insurance Self-insured Economical flood risk management entails investments into protection and includes risk management culture and insurance 28

29 Japan Earthquake BCE Cover (Business Continuity expense) 29

30 Commercial EQ Insurance 3 Standard Components Claims payable for loss derived from Physical Damages caused by EQ, volcanic eruption and/or Tsunami EXISTING COVERAGE Claims payable for Loss of Profit caused by the business interruption or suspension due to predetermined events Business Physical Continuity Damage Expense (BCE) Loss of Profit Claims payable for various expenses required for business recovery after an EQ event REMARKS: Basis Risk: miss match between actual loss and amount paid Declaration of expected expenses for policy limit before inception of coverage 30

31 Introduction to BCE Insurance Pre-Event Conditions (to be agreed) Declaration Expected expenses (=policy limit) Determination JMA stations & parametric payout Contractual Define application & Premium Post-Event Conditions (to trigger the immediate payout) Examples for business continuity expenses Debris removal and cleanup Temp. closing & reopening costs, emergency advertisments, announcements Temporary building instalment, temporary furnishing Relocation to alternative facilities, evacuation of stocks Travel and accommodation of supporting staffs Proof of Loss Physical damage to property exceeds the "franchise amount" EQ Intensity Trigger JMA stations recorded the preagreed SHINDO Intensity 6 Damage evaluation 7 Alternative transit, logistics 8 Emergency response to customers / supply chains. and more 31

32 Tokyo Osaka Aichi Fukuoka Kanagawa Hyogo Hokkaido Kyoto Chiba Shizuoka Miyagi Hiroshima Saitama Okayama Tochigi Ishikawa % of Total Annual Gross Profit Cumulative Gross Profit % JMA Station Selection Criteria 0. Approx. 600 JMA stations all over Japan 1. Determine areas of largest exposure (90% profit earnings) 2. Select JMA stations near the largest profit earning markets 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Top 90% 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 32

33 Non-Physical Damage Business Interruption (NDBI) Multiperil cover Swiss Federal Railways (SBB) Swiss Insurance Innovation Award 2015 by Schweizer Versicherung

34 NDBI Cover An Overview Client Swiss Federal Railways (SBB) major Swiss national railway company Client s Needs The client identified several 'black swan' type scenarios based on real life past incidents or as potential risks that could materialize Clients internal risk assessment indicated substantial exposure to core businesses being interrupted for several days or even weeks. Insurance Solution Multiperil Non-Damage Business Interruption Cover Coverage: Business Interruption due to Imminent Natural Catastrophes Non-Performance of Information Systems (Cyber) Regulatory Abandonment of Rolling Stock 3 year policy with an aggregate term limit 34

35 NDBI Coverage Covers Imminent Natural Catastrophes Perils covered Windstorm, Strong Precipitation, Avalanches, Mudflow, Rockfall, Landslide Risk assessment Nat Cat risk assessment is based on analytical loss models (frequency and severity), i.e. comprehensive exposure and scenario analysis as well as actuarial modelling Example of scenarios to be considered: Small flood may trigger imminent natural catastrophe coverage through this policy. (large flood expected to trigger traditional PD coverage - covered through separate policy) Risk for Rockfall / Landslide / Avalanche Impact on Power Generation and Distribution and others 35

36 Wrap up (Re)insurance and engineering make society resilient The world sustains significant Nat Cat losses every year Nat Cat risks can be modelled, assessed and controlled Taylor made insurance solutions 36

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38 Legal notice 2015 Swiss Re. All rights reserved. You are not permitted to create any modifications or derivative works of this presentation or to use it for commercial or other public purposes without the prior written permission of Swiss Re. The information and opinions contained in the presentation are provided as at the date of the presentation and are subject to change without notice. Although the information used was taken from reliable sources, Swiss Re does not accept any responsibility for the accuracy or comprehensiveness of the details given. All liability for the accuracy and completeness thereof or for any damage or loss resulting from the use of the information contained in this presentation is expressly excluded. Under no circumstances shall Swiss Re or its Group companies be liable for any financial or consequential loss relating to this presentation. 38