GIRO D4: Commercial Property



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GIRO Conference 2014 Large Commercial Property Risk Loss Estimation: A Practitioner s Application to the Netherlands John Buchanan (Verisk/ISO) Enrico Biffis (Imperial College Business School) 25 Sept 2014 GIRO D4: Commercial Property Introduction Agenda 25 September, 2014 John Buchanan Some New Insights into Large Commercial Risks Enrico Biffis 15 minutes Property Insurance in China and the Far East Region Xiaoxuan (Sherwin) Li 15 minutes Application to Netherlands Q&A John Buchanan 15 minutes To the extent there is time, will pause for questions after each of the Three main sections. Otherwise, will have questions at the end. Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 2

3 Extracts from full CARe Presentation 4

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White Paper Large Commercial Property Risk Loss Estimation: A Practitioner s Application to the Netherlands John Buchanan (Verisk/ISO) Enrico Biffis (Imperial College Business School) 25 Sept 2014 Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 27 Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 28

Large Commercial Property Risk Loss Estimation: A Practitioner s Application to the Netherlands Overview o Netherlands vs. US and UK o Attempting to solve the Puzzle Non-cat Excess vs. Ground-up A. Non-cat Excess Loss Estimates o Important link between exposures and losses o US vs. International loss scales COPE-ARM adjustments o Cross-country validations macro and micro view B. Non-cat Ground-upup Loss Estimates o Breakdown by perils Fire, Wind, other causes of loss o Scaling adjustments C. Cat Estimates o Hazards by country D. Bringing It All Together o Case Study 1000 NL Offices and Light Manufacturing Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 29 Why is NL so much worse for large claims than US or UK? Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 30

Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 31 Non-Cat and Cat Perils Non-Catastrophe Risks Fire Vandalism and theft Lightning Explosion Water leakage Catastrophe Risks Tropical cyclone (hurricanes, typhoons) Severe thunderstorm (tornado, hail, straight-line wind) Extratropical cyclone (includes U.S. winter storm) Earthquake Flood Terrorism US data sources split non cat and cat losses into three components. Relative size varies significantly by territory / occupancy, etc. Basic Group I (Fire, lightning, i explosion, vandalism, sprinkler leakage) Basic Group II (Windstorm, civil commotion, smoke, hail, aircraft, volcano, riot, sinkhole collapse, ) Special Causes of Loss (all other perils such as weight of ice/snow, additional causes of collapse, water damage, theft, Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 32

International Property A. Non-Cat Excess Loss Estimates Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 33 Sample FPA Data Collection Netherlands Original Data 34

Large Netherlands Claims Validation by Type Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 35 Additional Validation: Imperial-IICI Dataset Imperial College IICI Large Commercial Risks (LCR) Insurance Intellectual Capital Initiative (IICI) New dataset from Syndicate submissions shows similar major Occupancy group distributions as PSOLD Occupancy split by North America vs. Rest of the World also similar Source: International Congress of Actuaries (Wash DC April 2014 Enrico Biffis Imperial) Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 36

Cross-Country Comparison of Large Claims # of Large Claims per $B of Total Industry Premium Using US as the base, compare # of large claims per $B of total commercial property premium in excess of various thresholds. Shown are thresholds ranging from $30M to $150M Although varies significantly by country, the number of large claims on average is 40 50% higher than the US for these largest claims Protection/ sprinkler differences may account for a significant portion of the US vs. non US experience Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 37 US to International Property Risk Excess Loss Factors PSOLD International: COPE Assessment Matrix (for illustration only) 1. With US as base, compare each COPE+ attribute 2. Tally up expected impacts and qualitatively weigh them by COPE+ attribute 3. See how compares to actual large loss experience 4. Use same procedure for Ground up Loss Costs, but include Frequency component COPE+FARM Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 38

NFPA US Large Loss Data Collection Detection / Suppression Trends 39 International Property B. Non-Cat Ground-up up Losses Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 40

Calculating Ground-Up Non-Cat Loss Costs (Illustrative) Non-Cat Loss = Base LC x Territorial Multiplier x Deductible Factor x Limit of Insurance Factor x (Limit of Insurance / 100) x Protection Factor x Sprinklered Relativity Parameter Building Value Contents Value Base loss cost 0.175 0.220 (for specific occupancy/ construction combination) Territorial Multiplier 1.150 1.150 Deductible Factor 0.870 0.730 Limit of Insurance Factor 0.600 0.750 Limit of Insurance $42.5M $9M Subtotal $44,647 $12,467 Protection Factor 1.00 1.00 Sprinklered Relativity it 085 0.85 085 0.85 Loss Estimate $37,950 $10,597 Basic Group 1: Fire et al (building & contents) t $48,547 Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 41 Portability to Australia (Illustrative) - NonCat Ground-Up Loss Costs and Layering Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 42

Adjusting Ground-up Loss Costs by Region and Peril Component NL (Illustrative) Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 43 International Property C. Cat Loss Estimates Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 44

Modeled Tropical Cyclone Locations Caribbean Anguilla Antigua & Barbuda Aruba Bahamas Barbados Bermuda British Virgin Islands Cayman Islands Cuba Dominica Dominican Republic Grenada Guadeloupe Haiti Jamaica Martinique Montserrat Netherlands Antilles Puerto Rico Saint Barts, Saint Kitts & Nevis St. Lucia St. Maarten St. Martin St. Vincent & the Grenadines Trinidad & Tobago Turks & Caicos Island U.S. Virgin Islands Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. North America Hawaii Gulf of Mexico (Offshore Assets) Mexico United States Central America Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama Source: AIR Touchstone Asia Pacific Australia China Hong Kong India Japan Philippines Taiwan South thkorea 45 Modeled Extratropical Cyclones Locations North thamerica United States Europe Austria Belgium Czech Republic Denmark Estonia Finland France Germany Ireland Latvia Lithuania Luxembourg Netherlands Norway Poland Sweden Switzerland United Kingdom* * Includes coastal storm surge flooding Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. Source: AIR Touchstone 46

International Property D. Bringing it All Together Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 47 Netherlands Case Study White Paper Include Ground-up, up, Excess and Cat Components Case Study 1000 Netherlands exposures split between Commercial and Industrial (banded profile) Ground-up Loss Costs Use NL ground-up loss cost factors that have been adjusted for Fire, Wind, and other cause of loss factors from US or other source Include construction, occupancy, protection (location or region) and other exposure selections either identified or judgmental Excess Pricing Use selected size of loss curves, adapted to country specific circumstances using COPE+ methodology Cat Pricing Incorporate cat model results, generated using the same individual exposure information as with the Ground-up Loss Costs Combined Results Total ground-up and excess layer cat and noncat results in aggregate and by exposure Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 48

Case Study Netherlands Banded Profile (Illustrative) Source: compiled from AIR Cede file Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 49 Netherlands Geospatial Exposure Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 50

Ground-Up Non-cat Loss Costs NL (Illustrative) Individual exposures assigned to LMH region based on postal code; construction/ sprinkler usage was selected based upon building size; occupancies selected: offices and light manufacturing for commercial and industrial sensitivity testing Includes Peril scalars to adjust for expected Fire, Wind, other causes of loss differentials for US vs. Netherlands Include additional country/region scalars as needed to balance back to credible actual expected loss ratio (vs. 60.1% indicated LR) Source: ISO Rapid Valuator International with ISO-Portal Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 51 Ground-Up Non-cat Loss Costs NL (Illustrative) Results by Peril Source: ISO Rapid Valuator International with ISO-Portal Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 52

Ground-up and Excess Layer Distribution Non-cat Source: ISO PSOLD-International capping losses at 150% of AOI Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 53 Case Study 2: 50 European Locations Total cat/non cat GULC=$3.9M; $5x5M =305k (about 90% non cat) for these 50 risks Source: Verisk Cat/Non cat Integrated Solution (Tripod) cat: AIR Touchstone non cat: ISO Rapid Valuator with Portal and PSOLD International Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 54

Appendix Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 55 Netherlands - Sample FPA Data Collection Sample Fire Cause Comments Source: NIVRE and Verisk/ISO 56

US Sample FPA Data Collection Sample Fire Cause Comments Source: US National Fire Protection Association and Verisk/ISO 57 UK - Sample FPA Data Collection Sample Fire Cause Comments Source: UK Fire Protection Association and Verisk/ISO 58

Another look at cross country comparison statistics Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 59 John W. Buchanan Verisk / ISO - Principal, Excess and Reinsurance John.Buchanan@iso.com John Buchanan, FCAS, MAAA, is a principal in charge of ISO's Excess and Reinsurance Division. He has over 30 years of experience as a front-line pricing actuary and consultant in the US, London, and other international reinsurance marketplaces. In John's career, he has conceptualized, developed and implemented extensive benchmarking and modeling services for various reinsurers, excess carriers, and industry groups. He has pioneered extensive work to extend information gathered in mature benchmarking markets, and extending that information to other International markets making use of local and customized knowledge. He was a frontline sign-off actuary for many domestic and international lines of business. While a consultant, he was also the main contact for many years for the Reinsurance Association of America and the Reinsurance Research Council of Canada as well as having worked extensively with the London and European reinsurance market through the Casualty Actuaries in Reinsurance in London. John's professional accomplishments in the property p area also include being heavily involved with many international meteorological groups including NOAA, UK-Met, GLOBE, ACRE, and as chairperson of the CAS Climate Change Student Outreach subcommittee. He is in charge of the reinsurance educational tracks at the annual CARe conference, and previously at the CAS Ratemaking Seminar. He has also been a moderator and panelist at dozens of industry seminars on the topic of domestic and international reinsurance pricing, the underwriting cycle, international benchmarking, etc. Prior to joining Verisk, John was a Senior Vice President at Platinum Underwriters (previously St. Paul Reinsurance), a Principal at Tillinghast (now Towers Watson), and a Senior Consultant at KPMG, Peat Marwick. He also has competed as an amateur in the Global Salsa Championships, and is determined to write the book "The Mathematician's Guide to Salsa Dancing". Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 60

Enrico Biffis Associate Professor of Actuarial Finance Imperial College Business School e.biffis@imperial.ac.uk Enrico Biffis is an Associate Professor of Actuarial Finance at Imperial College Business School, a fellow of the Pensions Institute London, a member of the Munich Risk and Insurance Center at LMU Munich, and an editor of ASTIN Bulletin The Journal of the International Actuarial Association. His area of expertise is asset-liability management, with emphasis on risk analysis and market consistent valuation for the insurance and pensions industry, as well as optimal risk transfers for catastrophe t and long term risks. His research has attracted funding from leading insurers and governmental organizations, and has been published in the Journal of Risk and Insurance, Insurance: Mathematics and Economics, North American Actuarial Journal, Scandinavian Actuarial Journal, among others. Enrico has also worked with industry bodies on the benchmarking of stochastic asset models, and the impact of Dodd- Frank/EMIR regulation on OTC derivative markets. Enrico is a regular speaker at academic and industry events, including Risk Theory Society (American Risk and Insurance Association), Risk Minds Insurance, and Global Derivatives. Enrico holds a BSc and MSc in Statistics, a MSc in Actuarial Management, and a PhD in Mathematics for Economic Decisions. Prior to joining Imperial College London in 2007, Enrico held positions at Bocconi Milan, Association of British Insurers, and Cass Business School. Verisk Analytics, Inc., 2014. Not for copying or distributing without permission. 61

Property Insurance in China and the Far East Region Xiaoxuan(Sherwin) Li, FIA,FCAA,FCAS 2014 GIRO Conference

CONTENTS Overview of the Far East Ins Market Property Line in the Far East Ins Market Exposure Curves in China 2014 China Re P&C. All rights reserved. 2

P&C Insurance Market in China China s P&C insurance market was growing rapidly during the past decade, with an average annual growth rate of 22%. It becomes the third largest non-life insurance market in the world by 2013. GPW of P&C Insurance in China (in USD, billions) 120 104 100 89 80 65 77 60 40 20 11 13 14 18 20 25 33 39 48-2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 3 2014 China Re P&C. All rights reserved.

P&C Insurance Market in S.Korea Korean P&C insurance market grew rapidly before 2012 with growth rate of over 20%, but slowed down after 2012. 70 60 GWP of P&C Insurance in S.Korea (in USD, billions) 55 61 63 50 45 40 36 30 20 10 0 2009 2010 2011 2012 2013 4 2014 China Re P&C. All rights reserved.

P&C Insurance Market in Japan The premium volume of Japan s P&C insurance market was decreasing until 2010 and then goes on the rise. It is the fourth largest non-life insurance market in the world. 86 GWP of P&C Insurance in Japan (in USD, billions) 84 84 82 80 78 76 81 78 76 76 78 80 74 72 FY2006 FY2007 FY2008 FY2009 FY2010 FY2011 FY2012 2014 China Re P&C. All rights reserved. 5

P&C Insurance Market in China The commercial property line is the second largest line in China s market, only after motor insurance. Homeowners insurance is not a large market in China. Mix of LOBs in China Market 16.1% 4.7% 0.6% 5.8% 53.4% Voluntary Motor(MOD&MTPL) Statutory MTPL Commercial Property 19.4% Agricultural Homeowners Others 6 2014 China Re P&C. All rights reserved.

P&C Insurance Market in S.Korea In Korean P&C market, long-term insurance is the largest line, which is the unique characteristic of Korean market. One-year term property insurance only accounts for a very small fraction of the market. Mix of LOBs in Korean Market 6% 1% 1% 2% 9% Long-term Motor 62% Casualty Annuity Guarantee 19% Marine Property 2014 China Re P&C. All rights reserved. 7

Long-term Insurance in S.Korea Long-term insurance is not a line of business in fact, but a type of product form. In fact, it includes long-term motor insurance, long-term property insurance, long-term accident insurance, etc. Insurance period is more than 3 years Maturity benefit exists. Premium can be paid by monthly, quarterly, annually or single lump sum and is divided into risk premium and savings premium. Savings premium is operated in separate account, and there is a policy reserve for each policy. 2014 China Re P&C. All rights reserved. 8

P&C Insurance Market in Japan In Japan s P&C market, property insurance is the second largest line. There is also a maturity-refund type of insurance product in Japan market covering property, motor, personal accident and miscellaneous casualty. But its market share is very small. Mix of LOBs in Japan Market 11% 3% 12% 13% 44% Voluntary Automobile Property Personal Accident Miscellaneous Casualty Compulsory Automobile Liability Marine and Inland Transit 17% 9 2014 China Re P&C. All rights reserved.

P&C Insurance Market in China There are totally 65 P&C insurance companies in China by the end of 2013. However, all the foreign insurers account for only 1.3% of the total premium income in the market. Most of their business are commercial property insurance, with very little motor insurance due to the marketing channel. Number of P&C Insurers in China 44 45 40 35 30 21 25 20 15 10 5 0 Domestic JV/Foreign 10 2014 China Re P&C. All rights reserved.

P&C Insurance Market in S.Korea There are totally 31 P&C insurance companies in S.Korea by the end of 2013. Domestic insurers dominate the market and the market share of all the foreign insurers is about 3%. Number of P&C Insurers in S.Korea 17 18 14 16 14 12 10 8 6 4 2 0 Domestic Foreign 11 2014 China Re P&C. All rights reserved.

P&C Insurance Market in Japan There are totally 53 P&C insurance companies in Japan by the end of 2013. Domestic insurers dominate the market and the market share of all the foreign insurers is about 6%. Number of P&C Insurers in Japan 30 30 23 25 20 15 10 5 0 Domestic Foreign 12 2014 China Re P&C. All rights reserved.

CONTENTS Overview of the Far East Ins Market Property Line in the Far East Ins Market Exposure Curves in China 13 2014 China Re P&C. All rights reserved.

Property Insurance in China Before 2012, the growth rate of commercial property insurance in China market was as high as more than 20%. Since 2012, however, the commercial property line grew much slowly. GWP of Property line in China Market (in USD, Billions) 7.0 6.0 5.3 5.8 6.1 5.0 4.0 3.0 2.0 1.0 3.6 4.4-2009 2010 2011 2012 2013 14 2014 China Re P&C. All rights reserved.

Property Insurance in S.Korea Except 2012, the growth rate of one-year term property insurance in Korean market was very low. GWP of Property line in Korean Market (in USD, Millions) 300 250 200 225 229 235 292 300 150 100 50 0 FY2009 FY2010 FY2011 FY2012 FY2013 15 2014 China Re P&C. All rights reserved.

Property Insurance in Japan The premium volume of property line was decreasing until 2010. Then it goes on the rise. GWP of Property line in Japan Market (in USD, Billions) 15 14 14 14 14 14 14 13 14 13 13 13 12 FY2006 FY2007 FY2008 FY2009 FY2010 FY2011 FY2012 16 2014 China Re P&C. All rights reserved.

Property Insurance in China The loss ratio of commercial property is rising during the past few years. In 2008, there was a heavy snowstorm occurring in South China and an earthquake in Sichuan Province. In 2013, a large claim, Hynix Semiconductor, came up. Its estimated loss could reach USD 1 billion and will perhaps become the largest claim in China by now. Loss Ratio of Property line in China Market 90.0% 80.0% 84.0% 82.4% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 47.1% 54.1% 52.9% 61.4% 0.0% 2008 2009 2010 2011 2012 2013 17 2014 China Re P&C. All rights reserved.

Property Insurance in S.Korea The loss ratio of one-year term property insurance line in Korea is normally low. 70.0% 60.0% 62.0% Loss Ratio of Property line in Korean Market 56.2% 58.6% 59.2% 50.0% 40.0% 30.0% 41.4% 39.5% 44.2% 39.7% 32.0% 38.8% 20.0% 10.0% 0.0% FY2003 FY2004 FY2005 FY2006 FY2007 FY2008 FY2009 FY2010 FY2011 FY2012 18 2014 China Re P&C. All rights reserved.

Property Insurance in Japan The loss ratio of property insurance line in Japan very low in normal years but extremely high when catastrophe occurs. 180.0% 160.0% 140.0% 120.0% 100.0% 80.0% 60.0% 40.0% 20.0% 0.0% Loss Ratio of Fire line in Japan Market 166.8% 65.4% 28.4% 26.8% 27.1% FY2008 FY2009 FY2010 FY2011 FY2012 19 2014 China Re P&C. All rights reserved.

Property Products in China The commercial property insurance products include three form in China market. Basic Form Fire, Explosion, Lightening, Falling of objectives Comprehensive Form Besides those of Basic Form, also covers some natural events such as rain, storm, flood, hail etc. All-risks Form Only specifies what are not covered, such as normal wear and tear, destroyed by gov t, war, SRCC, nuclear etc. 20 2014 China Re P&C. All rights reserved.

Property Ratemaking in China The traditional rating variables for commercial property insurance in China include only a very few factors, such as classification of industry and territory. Since 2006 China Insurance Regulatory Commission and Insurance Association of China started to establish the guidelines of Pure Risk Loss Rate Tables, such as for commercial buildings, power plant, metro(subway) etc. But the work has not covered all the insured objects. After that, more rating factors were introduced to ratemaking, including types of construction, occupancy, fire protection level. 21 2014 China Re P&C. All rights reserved.

Property Ratemaking in China Although there are some actuarial rating guidelines, the underwriters still have more authority to adjust the final rates in the market. The market is very competitive and the premium rate for commercial property line was diving down during the past decades. 0.18% 0.16% 0.14% 0.12% 0.10% 0.08% 0.06% 0.04% 0.02% 0.00% Average Premium Rate for Comm Property 0.17% 0.11% 0.07% 0.05% 2000 2005 2010 2013 22 2014 China Re P&C. All rights reserved.

CONTENTS Overview of the Far East Ins Market Property Line in the Far East Ins Market Exposure Curves in China 23 2014 China Re P&C. All rights reserved.

Exposure Curves in China Market Some exposure curves for property insurance are used in China market. Empirical Curves Lloyds Curves Reinsurer s Curves(Swiss Re, Munich Re, etc) Salzmann Curve (1960 INA Homeowners data) Ludwig Curve (1984-1988 Homeowners and Small Commercial data) ISO s PSOLD & PSOLD+ Parametric Curves Log-log MBBEFD 24 2014 China Re P&C. All rights reserved.

Exposure Curves in China Market But it is in doubt whether these exposure curves are suitable for China market. Risk Classification is different. Data sources are old or unknown. China market has its distinctive risk features. To Develop China s own Exposure Curve 25 2014 China Re P&C. All rights reserved.

China Re Exposure Curves China Re Exposure Curves for commercial property was developed by China Re P&C Insurance Experience Research Center and was released to the market in September 2013. The curves are based on nearly 500,000 policy-level data collected by China Re P&C. Categories General commercial property Warehouse Industrial property of low risk Industrial property of high risk 26 2014 China Re P&C. All rights reserved.

China Re Exposure Curves Mixed exponential curve fitting technique was used. 27 2014 China Re P&C. All rights reserved.

China Re Exposure Curves The graph of China Re Exposure Curves for commercial property suggests that warehouse (storage property) is the most risky class and faces the highest probability of suffering a high-severity loss. 28 2014 China Re P&C. All rights reserved.

China Re Exposure Curves Compared with the typical international exposure curves, China Re Exposure Curves are closer to the top left corner as a whole, which implies that: The probability of total loss reflected by China Re Exposure Curves is lower. More losses on China Re Exposure Curves are medium/small rather than total loss. 29 2014 China Re P&C. All rights reserved.

Thank You for Your Listening! INTRODUCTION OF THE SPEAKER Mr. Xiaoxuan(Sherwin) Li, has nearly ten years of experience in the insurance industry and is currently the Head of Actuarial Department in China Re P&C. Before being transferred to the Actuarial Department, he worked in Treaty Reinsurance Department and Facultative Department for five years within China Re P&C. He holds the Fellow of the Institute and Faculty of Actuaries(FIA), the Fellow of China Association of Actuaries(FCAA), and the Fellow of Casualty Actuarial Society(FCAS). He is also an Associate of Reinsurance Administration(ARA) and a Microsoft Certified Systems Engineer(MCSE). He graduated with a Master's degree of Actuarial Science from Nankai University in China. Email: lixiaoxuan2004@126.com. 30 2014 China Re P&C. All rights reserved.