Reinsurance Where Do My Premiums Go? INS304

Transcription

1 Reinsurance Where Do My Premiums Go? INS304 Presenters Clive Tobin Chief Executive Officer for XL Insurance operations Scott Cooper Vice President Risk Management Solutions Newark, CA RIMS Annual 2007 Conference Tuesday, May 1, 2007 Tuesday, 10:45 am - 12:15 pm New Orleans, Louisiana Room MCC-242 Dennis J. Baltz, CPCU, ARM Director, Risk Management Coca-Cola Enterprises Inc. Atlanta, GA 1

2 Agenda Introduction Dennis Baltz, Coca-Cola Enterprises Inc. A Reinsurer s View Clive Tobin, XL Capital Ltd. A Modeler s View Scott Cooper, Risk Management Solutions A Risk Manager s View Dennis J. Baltz, Coca-Cola Enterprises Inc. Q&A 2

3 A Reinsurer s View Clive Tobin CEO for XL Insurance operations XL Capital Ltd 3

4 Agenda What am I buying? Reinsurance functions, types & structure What do I need to know? Post-Katrina/Rita/Wilma (KRW), challenges How am I buying it? Options, choosing the right company Case Study: Bermuda Market advantages, complementary capacity Conclusion 4

5 What Am I Buying? Functions Increase capacity Stabilize underwriting results Protection against catastrophic losses Form of financing Basic Types Treaty = covers broad groups of policies Facultative = covers specific individual risks Structure Pro Rata (proportional) Excess-of-Loss (non-proportional) Source: Reinsurance Fundamentals & New Challenges, 4 th edition, Insurance Information Institute 5

6 Types of Reinsurance Agreements Source: Reinsurance Fundamentals & New Challenges, Insurance Information Institute 6

7 Example: Reinsurance Program $20M Limit of Liability Source: Reinsurance: Fundamentals & New Challenges, Insurance Information Institute 7

8 What Do I Need To Know? Changes post-krw: New rating agency models Long-tail casualty exposures Greater capital requirements New capital/start-ups Alternative instruments Florida legislation 8

9 KRW Losses By Geography Current KRW Loss Breakdown By Geography Bermuda, 24% Europe, 13% Lloyds, 9% Other, 1% US Reinsurance 11% US Insurance, 41% Source: IBNR WEEKLY #25 (Volume XIII), June 26, 2006, Dowling & Partners 9

10 Reinsurance Challenges Pricing Risk exposures Catastrophes Loss experience ROE/Financial Results Below average compared to other industries Impact from Market Changing Events Payouts exceed that of Primary Insurers 10

11 Share of Losses Paid by Reinsurers,, by Disaster* 70% 60% 60% 50% 45% 40% 30% 20% 30% 25% 20% 10% 0% Hurricane Hugo (1989) Hurricane Andrew (1992) S e pt. 11 T e rro r A t t a c k (2001) 2004 Hurricane Losses 2005 Hurricane Losses *Excludes losses paid by the Florida Hurricane Catastrophe Fund, a FL-only windstorm reinsurer, which was established in 1994 after Hurricane Andrew. FHCF payments to insurers are estimated at $3.85 billion for 2004 and $4.5 billion for Sources: Insurance Information Institute, Wharton Risk Center, Disaster Insurance Project 11

12 Combined Ratios: Benfield Global Top 10 Reinsurers 250.0% 200.0% 150.0% % % 0.0% Munich Re Swiss Re Lloyds Hannover Re NIC General Re Group GE Insurance Solutions T/P Re ACE XL PartnerRe Note: 1) NIC and General Re represent Berkshire, who ranks fifth on Global Top 10; 2) GE Insurance Solutions has no listed 2006 C/R as it was acquired by Swiss Re; 3) T/P Re represents Transatlantic Holdings 12

13 How Am I Buying It? Choosing the Right Company: Strong Ratings Substantial Capital Base History Expertise/ Intellectual Capacity Claims-paying Record 13

14 Choosing the Right Marketplace Consider: Regulation Expertise Location Foreign Exchange 14

15 Customer Concerns Benfield broker survey: observed concerns of customers during the buying process Coverage and conditions 28% Security/ratings 27% Cost 34% Spread 4% Willingness to pay 2% Other 5% Source: Benfield Industry Analysis and Research publication Pick n Mix, January

16 Case Study: The Bermuda Re-Factor History Hurricane Andrew in capital wave brought 8 Property CAT specialists (3 remain independent) Today 13 Bermuda Reinsurers in S&P Global Top 40 Bermuda Reinsurers account for 17% of total net premiums 3 rd leading country in total premiums written 16

17 Why Bermuda? Established (Re)Insurers Efficient regulatory environment Location Infrastructure Response to market events Market diversification Premium flow 17

18 Premium Flow For Five Largest Markets Source: Reinsurance Association of America, 2005

19 Conclusion Know the market Know your broker (if using one) Know the regulatory environment Check ratings Check history Check management Spread risk 19

20 A Modeler s s View Scott Cooper Vice President Risk Management Solutions 20

21 Modeling Methodology Overview Generate Stoch. Events Assess Earthquake Motion Calculate Damage Quantify Financial Loss 90% $ Loss Define Hurricane Assess Wind Speed Calculate Damage Quantify Financial Loss Stochastic Module Hazard Module Vulnerability Module Financial Module 21

22 Interpreting Model Results 22

23 Interpreting Model Results 23

24 Secondary Perils and Other Loss Considerations Fire Following Earthquake Storm (Ocean) Surge Earthquake Sprinkler Leakage (EQSL) Demand Surge/ Loss Amplification Allocated Loss Adjustment Expense (ALAE) & Claims Surge Tsunami Super-CATs Secondary Uncertainty Non-Property Coverage: Worker s Comp, Auto Physical Damage, Boats, Airplanes, Inland Marine. CAT Funds and Wind Pools 24

25 Reinsurer s Pricing Considerations Market Rates Historical Losses Use of Multiple Models Relative Metrics to other Treaties and Programs (Premium to Average Annual Loss, etc.) Existing Distribution of Risk Other DOI, Rating Agencies, Political Issues 25

26 Catastrophe Modeling: Lessons Learned from $25B in Claims data from 2004 and 2005 Frequency (US hurricane) Data Quality/ Valuation Vulnerability Secondary Perils / Loss Amplification Political Issues associated with Claims and Rate Filings 26

27 Claims Analysis Waterfall Data Quality Vulnerability Loss Amplification Non-Modeled Perils RCV Incurred Losses ZIP Code Modeled Loss Footprint Aspects ACV 27

28 North Atlantic Hurricane Frequency Climate change Sea Surface Temperatures (SSTs) 2006 El Nino Long-term view vs short-term 5 year view Dr Gray s 2007 Forecast Category 3-5 Atlantic basin hurricanes and 5-year running average 28

29 Academic Research on Hurricane Activity The recent increase in Atlantic hurricane activity: Causes and implications - Goldenberg et al Uncertainty in Hurricanes and global warming - Trenberth 2005 Pre 2005 Penetration of Human- Induced warming into the world s oceans Barnett et al Increasing destructiveness of tropical cyclones over the past 30 years Emanuel Gray 2005 on natural cycles and ENSO Chan 2005 on West Pacific activity trends Landsea 2005 response to Emanuel 2005 Pielke et al on trends damage Low frequency variability in globally integrated tropical cyclone power dissipation Sriver and Huber 2006 Trends in global cyclone activity over the past twenty years ( ) - klotzbach 2006 Changes in tropical cyclone number, duration and intensity in a warming Environment Webster et al Hurricanes and Global Warming - Pielke 2005 Gray 2005 on data quality prior to satellite era Atlantic Hurricanes and natural variability in Trenberth and Shea 2006 decomposition of contributions to activity 2006 Sea Surface temperatures and tropical cyclones in the Atlantic Basin Michaels et al Deconvolution of the factors contributing to the increase in global hurricane intensity. Hoyos et al 2006 Blue global warming linkage Agenda Setting Hurricanes and Global Warming Potential Linkages and Consequences Anthes et al 2006 Green AMO linkage Atlantic Hurricane Trends Linked to Climate Change Mann and Emanuel

30 Data Quality Challenges Geocoding resolution Un-modeled exposures For some portfolios, represented 50% of actual loss, and greater Undervalued Exposures old data Basis risk in coding of data Bulk, default, coding Location, Occupancy, Construction, Year, number of stories Optimistic coding of commercial vulnerabilities i.e. Steel Frame vs. Light Metal Default to Unknown construction tends to increase risk When coded, secondary modifiers reduce risk Policy terms and conditions 30

31 Vulnerabilities What significant classes of atrisk structures need to be recognized? Data capture Guidance on coding Model refinement? Photo: SunHerald.com 31

32 Insurance Industry Dynamics in Flux Risk increasing (modeled risk, more risks) Capital requirements increasing (even for same risk) Re/insurance rates increasing Insurers are taking action to manage their exposures Insureds retaining more risk New capital entering the market, and ART We remain of the opinion the amount of capital required by a re/insurer in peak zones will increase by 50%+. We believe that demand for coverage will increase as the new models are introduced, new PMLs are calculated, and rating agencies require more capital - Dowling and Partners,

33 A Risk Manager s s View Dennis J. Baltz Director, Risk Management Coca-Cola Enterprises Inc. 33

34 Agenda Coca-Cola Enterprises Inc. (CCE) : At a glance Designing property programs (with reinsurance in mind) Property restrictions driven by reinsurance Catastrophe Modeling: Insured impact Models and impact on Risk Managers 34

35 Coca-Cola Cola Enterprises Inc. (CCE) : At a Glance 2006 Revenue: $19.8B $10B market cap We are the world s largest bottler, producing and selling 21% of The Coca- Cola Company s total global volume. Operations in U.S., Canada, and Western Europe (8 countries) We have 73,000 employees who distribute the world s most popular beverage brands 35

36 Designing Property Programs With Reinsurance In Mind Be aware of the major reinsurance treaty renewal dates (1/1 and 7/1) Dublin-based captive insurer: Fronting for reinsurance panel for layered (syndicated) global program Excellent choice for European Union (EU) footprint Build capacity by targeting large reinsurers with direct access points (SR, MARP, London) Know your insurers strengths and occupancies likely for reinsurance: Examples 36

37 Designing Property Programs With Reinsurance In Mind Preparing submissions accuracy is expected Focus on PD values (replacement cost) Location Location Location Get the data! Primary and secondary characteristics How good is your COPE? Signed authorization for statement of values: Use disclaimer Focus on BI values (actual loss sustained) Hiring a forensic accounting firm becoming the norm Impact of recovery strategies and BCP Models impact on pricing and terms Buying limits based on models 37

38 Property Restrictions Driven by Reinsurance Mold Asbestos Nuclear/ biological/ chemical (NBC) Cyber/network risk Flood in Netherlands Zone A Flood EQ in critical zones Tough business classes Chemical Petroleum Plastics Builders risk 38

39 Cat Models and Impact on Risk Managers Get organized early competing for underwriter time in the new six-month market Run your own models and share results with underwriters RMS, AIR, EQE It s all in the data Data - Data - Data Primary and secondary characteristics Impact of recovery and BCP strategies Pricing drivers: TIV, deductibles, and spread of risk Buying limits based on models 39

40 Reinsurance Where Do My Premiums Go? INS304 Presenters Henry Keeling Chief Operating Officer XL Capital Ltd. Hamilton, Bermuda Scott Cooper Vice President Risk Management Solutions Newark, CA RIMS Annual 2007 Conference Tuesday, May 1, 2007 Tuesday, 10:45 am - 12:15 pm New Orleans, Louisiana Room MCC-242 Dennis J. Baltz, CPCU, ARM Director, Risk Management Coca-Cola Enterprises Inc. Atlanta, GA 40