International Reinsurance Pricing and Challenges Casualty Actuarial Society Seminar on Ratemaking March , 2000

Agenda EQECAT Overview Catastrophe Modeling Overview Pricing and Challenges — Exposure Data Cresta level information Limited, if any, structural information — Modeling Data Varies from Country to Country Soil Information Terrain Information Building Vulnerabilities Frequency & Severity of events

EQECAT Leading provider of Consulting Services and Catastrophe Modeling Software to the Insurance Industry and Financial Community EQECAT was founded in 1994 and is a wholly owned subsidiary of EQE International. Headquartered in Oakland Other offices in Irvine, Philadelphia, Boston, London, Paris, Sydney and Tokyo Note: EQE has been providing Software and Consulting Services to the Insurance Industry since 1986.

Top U.S. Risk Management Consultants 1.PricewaterhouseCoopers$60,840,0002, Arthur Andersen$54,647, Deloitte & Touche L.L.P.$54,300,0001, EQE INTERNATIONAL$42,300,0001, Ernst & Young L.L.P.$31,038, Tillinghast-Towers Perrin$28,356, TotalRisk Mgmt. CompanyRevenuesClients Professionals Reference: Business Insurance, February 1999 (Ranked by risk management consulting services)

EQECAT Over 45 companies license EQECAT’s software — Primary Insurance Companies — Reinsurance Companies — Global Insurers (Non-US) — Brokers and Financial Institutions EQECAT has worked with over 100 insurance companies on a consulting basis — Portfolio Analysis — Pricing and Product Analysis — Education & Training — Claims & Loss Control Support — Securitization

Securitization Experience California Earthquake Authority (1996) SR Earthquake Fund, Ltd. (1997) Parametric Re (1997) Mitsui Marine (1998) Hedge Financial Products (CNA Insurance) (1998) Concentric Ltd./Circle Maihama Ltd. (Oriental Land)(1999). Namazu Re (Gerling Global Reinsurance) (1999)

EQECAT Geographic Areas: — United States Earthquake - All 50 States + Puerto Rico Hurricane - Gulf Coast & Eastern Seaboard, Hawaii & Puerto Rico — International - (Earthquake, Windstorms, Flood) Over 70 countries including: Canada, UK, Western Europe, Eastern Europe, Japan, Caribbean, Israel, Italy, Philippines, Chile, Australia, New Zealand, Mexico, Taiwan, Indonesia and Turkey

Catastrophe Modeling Overview

Catastrophe Modeling Methodology First Step - Define the Hazard HURRICANE Central Pressure Radius to Max Wind Translational Speed Wind Field Terrain HURRICANE Central Pressure Radius to Max Wind Translational Speed Wind Field Terrain FAULT Strike-slip Thrust Max. Magnitude Rupture Length Duration FAULT Strike-slip Thrust Max. Magnitude Rupture Length Duration

Catastrophe Modeling Methodology Second Step - Overlay Portfolio Individual Risk Information Location Construction type Age Insured value Individual Risk Information Location Construction type Age Insured value Individual Locations

WIND SPEED Calculated for each Location V w = f(P c, d, regional topography) WIND SPEED Calculated for each Location V w = f(P c, d, regional topography) GROUND MOTION Calculated for each Location PGA=f(M 1,d,regional geology) MMI = f(PGA, soil) GROUND MOTION Calculated for each Location PGA=f(M 1,d,regional geology) MMI = f(PGA, soil) Local Site Factors (Terrain/Soil) Distance (d) Catastrophe Modeling Methodology Third Step - Determine Site Hazard Severity

Catastrophe Modeling Methodology Fourth Step - Estimate Ground up Damage Hazard Severity Vulnerability Functions Calculated damage for each Location

PDF Probability density function of damage Distribution of damage based on hazard severity Distribution of hazard severity at the site Intensity Damage Calculation Uncertainty Reflected in Damage Estimate Damage

Catastrophe Modeling Methodology Step Five - Compute Insured Loss Insurance Data - Insured value - Deductible - Occurrence, site & policy limits - Facultative - Treaties Insurance Data - Insured value - Deductible - Occurrence, site & policy limits - Facultative - Treaties site & policy losses

Loss Probability Deductible Damage Distribution Catastrophe Modeling Methodology Compute Insured Loss

Catastrophe Modeling Methodology Portfolio Results Statistically combine individual results taking Correlation into account — Correlation of performance is a real issue It is computationally intense It lengthens the tail of the curve — PML understated without correlation

Catastrophe Modeling Methodology Probabilistic Analysis Requires the development of a extensive Stochastic Event Set Repeat analysis process for Events 1 through N The above analysis enables the development of the Annual Loss and Loss Distribution

International Reinsurance Pricing and Challenges

Exposure Data — Cresta level information — Limited, if any, structural information Modeling Data Varies from Country to Country — Soil Information — Terrain Information — Building Vulnerabilities Building Codes Building Practices Code Enforcement — Frequency & Severity of events (Stochastic event set)

Premium by country, etc. Decreasing Uncertainty Increasing Quality of Data Cresta Zones Occupancy (Residential, Commercial) Premium or TSI Postal Code Standard Structural Classification TSI/ Risk Address, Log/Lat, etc. Material, age, height, engineering report, etc. Value, limits, ded., etc. Specific address Detailed Occupancy Codes TSI, value, limits, etc. LocationStructuralInsurance Exposure Data

Level of Data Impacts Pricing Cresta Prefecture Ku Shi

Aggregate vs. Detail Data Pricing varies significantly within a Cresta Zone

Aggregated vs. Detailed Data Pricing varies significantly within a Prefecture

Aggregate vs. Detailed Data Example of potential impact on results — EQ demo portfolio for California Note: Since the Unicede file was developed from the detailed data, the distribution of exposure is essentially the same. TM

Structural Information

Impact of Structure Type Building performance varies significantly from one building type to another Vulnerability functions are used to develop damage estimates which are structure specific

Impact of Structure Type Rate per $1,000 Structure Type 6 = 0.50 Rate per $1,000 Structure Type 3 = 0.17

Critical Modeling Data Varies from Country to Country 1:24,000 1:500,000 Section of LA Taiwan Critical modeling data includes soil, terrain, frequency & severity of events, etc.

Adapazari - near total damage due to poor soil and liquefaction. Impact of Soil on Pricing August 17, 1999 Izmit, Turkey (M7.4 Earthquake)

Impact of Soil on Pricing Rate per $1,000 Soft Soil - $4.80 Stiff Soil - $2.70 Hard Rock - $0.40

Impact of Terrain (Friction) on Pricing

Building Codes Taiwan — Building with height less than 50 meters No dynamic analysis is required No third party review (by a committee) is required Geotechnical engineers are not required if the excavation is less than 10 meters deep — Architects are in charge of planning, design, and construction inspection Building practice varies from country to country

Building Codes/Practices Most of the damaged high rise buildings in Taiwan were round 12 stories (less than 50 m high) September 21, 1999 ChiChi, Taiwan (M7.6 Earthquake)

New high-end buildings (they “were” built to the California code)! Building Code Enforcement August 17, 1999 Izmit, Turkey (M7.4 Earthquake)

Earthquake Frequency and Severity Since earthquake are felt and measured around the world the historical data is fairly good for most countries. Taiwan U.S. However, information on fault location, type and other characteristics varies. This is an issue since major earthquakes are infrequent events

Typhoon/Hurricane Frequency and Severity Hurricane data is good for major industrialized countries, but largely antidotal for most other countries.

Conclusion International Reinsurers are working with very limited data which can skew or bias results Ability of models to effectively develop loss cost varies from country to country There is a lot of uncertainty in the process which must be accounted for in reinsurance pricing There are also other issues, not touched on in this presentation, that can impact results (e.g., Damage to Loss calculation, handling of uncertainty, etc.) In spite of the above, Catastrophe models are still the best tool available for pricing reinsurance.