Canadian Institute of Actuaries Conference CATASTROPHE MODELING 2012 AND BEYOND JUNE 21, Sherry Thomas Krista Lienau

Transcription

1 Canadian Institute of Actuaries Conference CATASTROPHE MODELING 2012 AND BEYOND JUNE 21, 2012 Sherry Thomas Krista Lienau

2 Catastrophe Modeling 2012 and Beyond Agenda Current landscape of Canadian catastrophe risk and modelling Model availability and usage for Canadian perils Catastrophe model enhancements expected in the future Catastrophe modeling result blending and customization Managing model change and uncertainty 1

3 Section 1 Current Landscape of Canadian Catastrophe Risk and Modeling

4 Current Landscape Canadian Catastrophe Risk and Modelling $2.7B Premium Ceded to Licensed Reinsurers ($ Millions) (22 Licensed Reinsurers in Now only 16 in 2011) $1.3B

5 Current Landscape 2011: Active Cat Year for Canada Alberta: July 18-19, 2011 Date Place Event Insured Loss (CAD) March 5-7 Quebec, Ontario Winter Weather, Heavy Rainfall 50,000,000 April 14 - May 31 Manitoba Assiniboine River Floods 160,000,000 April Ontario, Quebec Storms with winds up to 100km/hr 210,000,000 May Alberta Slave Lake wildfire 700,000,000 July Alberta, Manitoba, Saskatchewan Thunderstorms, heavy winds, hail 185,000,000 August 21 Ontario F3 Tornado 135,000,000 November 27 Calgary, Alberta Windstorm up to 149 km/hr 200,000,000 1,640,000,000 Source: Swiss Re 2011 Sigma Report Goderich: August 21, 2011 Calgary: November 27,

6 Current Landscape Unmodeled Perils Tsunami Risk Canada working on a National Hazard Map for Tsunami Expected to be an area of interest for commercial model development in the future Graphic from Natural Resources Canada 5

7 Current Landscape Unmodeled Perils Slave Lake $700-$750M CAD Insured Loss (2 nd Largest Cat Loss in Canada History) ~50% of Wildfires are Caused by Humans Photograph by: Caezer Ng/The Lakeside Leader, edmontonjournal.com 6

8 Current Landscape Unmodeled Perils Slave Lake Wildfires May Exposure i-axs RealCat 7 7

9 Current Landscape Unmodeled Perils Flood May/June 2011 Insured Loss $160M CAD Total Economic Loss $815M CAD The Assiniboine River threatens to breach the 18th Street Bridge in Brandon, Man. on May 11. The province has announced that a controlled breach of a dike is set to occur on May 12. (David Lipnowski/Canadian Press) 8

10 The Hard Catastrophe Market Current Landscape Events Shape Catastrophe Market Hard January 2011 Catastrophe Cover Renewals Soft Auto/Casualty Upward Pricing Limited Capacity Few Markets Catastrophe Downward Pricing Strong Capacity Many Markets Property Risk Downward Pricing Strong Capacity Many Markets 9

11 Hard The Hard Catastrophe Market Current Landscape Events Shape Catastrophe Market January 2012 Catastrophe Cover Renewals Soft Catastrophe Upward Pricing Limited Capacity Many Markets Property Risk Even Pricing Good Capacity Many Markets Auto Casualty Even Pricing Good Capacity Growing Markets The global market was well positioned to absorb big hits in 2011 Locally, Canada has hungry reinsurance players in a contracting market Cat pricing hardened in Canada more than some had anticipated Exposures were up, limits increased, and the cat spend grew 10

12 Hard The Outlook Current Landscape Events Shape Catastrophe Market Anticipated Mid 2012 to January 2013 Catastrophe Cover Renewals Soft Catastrophe Upward Pricing Limited Capacity Many Markets Property Risk Upward Pricing Limited Capacity Many Markets Auto Casualty Even Pricing Good Capacity Growing Markets 11

13 Section 2 Model Availability for Canadian Perils

14 What Questions Are Catastrophe Models Designed to Answer? Where are future events likely to occur? How intense are they likely to be? For each potential event, what is the estimated range of damage and insured loss? Catastrophe models are designed to estimate the probability of loss severity. They are not intended to forecast future events. 13

15 Cat Management Catastrophe Model Evolution Changing Risk Landscape 1992 Hurricane Andrew 2001 WTC 9/11 Poor Data / Limited Models 2005 KRW Capital Markets Enter into Reinsurance Models Go Worldwide / Influence Rate Adequacy Rating Agencies Empowered Financial Crisis 2008 Re-adjust Frequency, Severity assumptions Rating Agency Increases Capital Requirements Loss Correlation / Data Rapidly Improving ERM Increased Regulatory Oversight With each market turning event, the industry realized it had more exposure than previously believed 14

16 Catastrophe Modeling and Model Vendors Founded at Stanford University in 1988 World's leading provider of products and services for the quantification and management of catastrophe risks Grew in the 1990s, expanding services and perils covered Founded in 1987 Pioneered the probabilistic catastrophe modeling technology Founded in 1980s One of first catastrophe models in industry Other models Most large reinsurers and other risk management companies have developed their own in-house models 15

17 Current Canadian Licensed Modeling Capabilities Model Perils Available in Canada RMS Earthquake Fire-Following Earthquake Severe Convective Storm (Tornado, Hail, Lightening and Straight-Line Winds) Winterstorm (Freeze, Snow, Wind and Ice) North Atlantic Hurricane (new to RMS v11.0) EQECAT Earthquake Fire-Following Earthquake AIR Earthquake Fire-Following Earthquake (not for automobiles) Severe Thunderstorm 16

18 Current Model Versions Model / Peril RMS AIR RiskLink CLASIC/2 EQECAT Earthquake Fire Following Severe Storm NA Winter Storm 2008 NA NA Hurricane 2011 NA NA 17

19 Catastrophe Model Use in Canada by Peril Model / Peril RMS RiskLink AIR CATRADER AIR CLASIC/2 EQECAT Earthquake 100% 8% 42% 8% Severe Convective Storm 83% 8% 33% 0% Winterstorm 100% NA NA NA Hurricane 67% NA NA NA 18

20 Section 3 Catastrophe Model Enhancements Expected in the Future

21 Upcoming Model Changes RMS No Canadian model updates currently planned Next Generation Platform scheduled for 2014 Respond to 2015 GSC update EQECAT No Canadian model updates currently planned RQE scheduled for late 2012 Research efforts underway on liquefaction, underwater landslide, tsunami, windstorm, hail, and flood AIR Earthquake, Severe Storm, and Winter Storm likely in 2014 New Hurricane model likely in

22 The 2015 Canadian GSC Report Source: John Adams, Seismic Hazard Maps for the National Building Code of Canada past, present and future. Canadian Seismic Risk Network Workshop, Institute for Catastrophic Loss Reduction 21 21

23 Section 4 Catastrophe Model Result Blending and Customization

24 Guy Carpenter s Customized Cat Modeling Approach CLIENT EXPOSURES DATA QA AND AUGMENTATION MODELED PERILS NON-MODELED PERILS (NMP) MULTI-MODEL ANALYTICS Obtain available views of risk Superior Documentation CAT REPORT Superior Understanding of Models MODEL SUITABILITY ANALYSIS (MSA) Develop appropriate view of risk with objective testing MSA REPORT PARAMETERIZATION & SCENARIO ANALYSES Complement view of risk for non-modeled perils NMP REPORT CLIENT S OWN COMPREHENSIVE VIEW OF RISK 23 23

25 Guy Carpenter s Model Suitability Analysis (MSA) SM Client s View of Risk EVALUATION INTEGRATION COMMUNICATION COMPONENT 1 SENSITIVITY TESTING COMPONENT 2 LOSS VALIDATION COMPONENT 3 SCIENTIFIC APPRAISAL COMPONENT 4 MSA GRID COMPONENT 5 MODEL ENHANCEMENT COMPONENT 6 RISK CUSTOMIZATION COMPONENT 7 DOCUMENTATION COMPONENT 8 KNOWLEDGE SHARING 24 24

26 Guy Carpenter s Model Suitability Analysis (MSA) SM Client s View of Risk INTEGRATION COMMUNICATION COMPONENT 4 MSA GRID COMPONENT 7 DOCUMENTATION GC + Client Defined C1: ST C2: LV C2: LV C3: SA C3: SA MODEL 1 Relative RC Bldg Code GOOD Klaus Loss Validation 10% ERROR Hi-Freq EP Validation SO-SO MATCH Agreement Dmg Funcs MATCHES RESEARCH Agreement Event Ftprts MATCHES UK MET MSA C3: SA CHAPTER MODEL 2 GOOD 200% ERROR POOR MATCH NO MATCH MATCHES UK MET MODEL 3 NO LATEST AGE BAND 50% ERROR SO-SO MATCH MATCHES CLAIMS NO MATCH UK MET 25 SII 25

27 Section 5 Managing Catastrophe Model Change and Uncertainty

28 Uncertainty Abounds Loss Modeling is Highly Sensitive to Many Factors 27

29 Major Sources of Uncertainty Cat Models Data Address Information Multi location Insurance to value and other coverage issues Imperfect sight into risk characteristics Engineering Limited claims data for catastrophic events Lack of understanding of structural behavior under severe loads Financial Supply chain dynamics that impact commercial business interruption Simulated financial transactions with probability distributions Courtesy of AIR Worldwide / EERI 28

30 Major Sources of Uncertainty Cat Models Hazard Lack of history of large earthquakes limits our ability to simulate them We rely on indirect sources of information, like GPS measurements or paleo-seismology (e.g. historical liquefaction) We know relatively little about seismicity potential in areas of low seismicity (like in Eastern Canada) Even in areas of high seismicity like southwestern Canada, there is a limited amount of data and there is room for the unexpected (Japan M9.0 in 2011, for example) 29

31 Distribution Assumptions Commercial Vendors Frequency Distribution Severity Distribution AIR CLASIC/2 EQECAT WCe RMS RiskLink AIR CLASIC/2 EQECAT WCe RMS RiskLink Storm Negative Binomial Negative Binomial Poisson Gamma Beta Beta Flood Poisson Poisson Poisson Gamma Log Normal Beta Quake Poisson Poisson Poisson Gumbel Beta Beta 30

32 Conclusion Some Basic Things to Remember Regarding Cat Risk Widespread and deep usage of models is relatively young Models are models: there are many uncertainties in them Data and scientific hypotheses all matter a lot Suitability analyses of models will be increasingly important Don t assume a catastrophe model is useful prove it useful yourself or rely on another to help 31 31

33 Recent Briefings and White Papers Responding to Catastrophe Model Change GC Briefing, October 2011 Managing Catastrophe Model Uncertainty: Issues and Challenges GC Analytics White Paper, December 2011 Beyond PML: A 360 Degree View of Risk GC Analytics White Paper, February 2012 Spring Conditions Suggest Tempered Atlantic Hurricane Season GC Analytics White Paper, May

34 Questions? Q & A krista.lienau@guycarp.com sherry.l.thomas@guycarp.com 33

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