Plagues of the 21 st Century

1. Plagues of the 21st Century Emile Elefteriadis, FCIA, FSA Swiss Re Life & Health Canada November 17, 2004

2. Agenda • Possible Mortality Catastrophes • Vita Capital’s Principal-At-Risk Variable-Rate Mortality Catastrophe Indexed Note • aka Swiss Re’s Mortality Catastrophe Bond • Modeling Approaches

3. Possible Mortality Catastrophes • Terrorist Attack • Profound difference in ideology • September 11, 2001 • Biological, nuclear threats • War • Middle East • North Korea • India and Pakistan • Intervention and escalation • Wars have been relatively frequent

4. Possible Mortality Catastrophes • Meteorite Crash • 1908 Tunguska River, 55 meter meteorite • 15,000 Kiloton (kT) explosion • Hiroshima 12.5 kT • a 1:1900 year event • 1972 a 10 meter object bounced off earth’s atmosphere. • Energy release could have been over 20kT • a 1:35 year event Source: Target Earth: Present, Past and Future. B. French, Lunar and Planetary Institute

5. Possible Mortality Catastrophes • Influenza Epidemics 20th Century

6. Possible Mortality Catastrophes • More recent outbreaks

7. Other major infectious diseases • Tuberculosis • Smallpox and threat of biological weapons • Newly emerging diseases - SARS • Other diseases - CJD, Plague, West Nile virus and other water borne / vector borne diseases (like Malaria)

8. Mortality Risk Transfer • In December 2003, Swiss Re sponsored a $400 million securitization of mortality risk • The purpose was to get protection against extreme mortality events, without relying upon the credit-worthiness of a retrocessionaire • A catastrophe bond structure was used, with loss measurement based on a parametric index

9. Mortality Risk Transfer - Issuer’s Risk Position Losses [% of expected] The Issuer’s internal risk assessment is based on its aggregate portfolio LIFE INSURANCE PORTFOLIO [100+Y]% Desired Risk Transfer [100+X]% Acceptable Variance 100% Expected Deaths

10. Mortality Risk Transfer - Structure Insurer Financial Contract Premium (1) (2) Up to Original Principal Amount at Redemption (3) Principal At-Risk Variable Rate Notes SPV Total Return Swap Counterparty Investment Income Interest: LIBOR + [ ]% LIBOR - [ ] Collateral Account Original Principal Amount

11. Mortality Risk Transfer - Payout Exhaustion Point: [100 + y ]% Attachment Point: [100+x]% 100% 90% 80% 70% 60% % Reduction in Principal 50% 40% 30% 20% 10% 0% 100 100+Y 100+X Index Results (% of Base Index Value)

12. Mortality Risk Transfer - Trigger Definition • The index value for a given year is defined to be the average death rate per 100,000 for pre-defined coverage area • The average death rate is calculated using a parametric index formula, which applies pre-determined weights to gender, age, and country, and draws on publicly-available mortality data as the inputs: • Attachment Point = x% of Index Value in baseline year • Exhaustion Point = y% of Index Value in baseline year • % Loss = 100 x (Index Value - Attachment Point) / (Exhaust Point - Attachment Point) Index = Where cj is the weight for country j, gm,f is the gender weighting, ai is the weight for age band i, and qi,jis the observed death per 100,000 for males and females, respectively, from country j and age band i

13. Historical Analysis

14. Modeling Approaches • Perspective: • interest is in acute events • near term (1-3 years)

15. Theoretical Epidemiologic Models for Influenza/Infectious Disease

16. Theoretical Epidemiologic Models • Theoretical models are useful for understanding how certain factors can influence the incidence and severity of an influenza epidemic/pandemic • SEIR Model • Susceptible • Incubating • Infected • Recovered

17. Good in theory • Viral Virulence • Incidence of infection • Immunity representation • Public health, Surveillance • Population size, density • Air travel • Response • Useful for constructing various theoretical severity distributions using stochastic modeling

18. Age Standardized Mortality

19. Epidemiologic Transition • Changes in the relative importance of causes of death – Orman’s three-stage theory: • Famine and Pestilence, prior to 19th century • Infectious diseases and pandemics , middle of 20th century • Chronic diseases (cardiovascular, cancer) • Fourth stage? death due to longer-term degenerative diseases (Olshansky & Ault (1983), Rogers & Hackenburg ( 1987)

20. US Age Standardized Mortality

21. Future Value of Index • Approach 1 • Index(t)=Index(t-1)*(1+annual change) • annual change is the RV • RV is not normal 1918 is more than 6 standard deviations • fatter tail distribution more appropriate • however returns are correlated: large increase followed by large decrease (reversion to mean)

22. Annual Change in Mortality

23. Approach 2 • Index(t)=Index(0)(1-Imp)^t*(1+EM) • EM is extreme mortality distribution

24. Age Standardized Pandemic Mortality

25. Excess Mortality • Influenza Epidemics 20th Century

26. Influenza - Excess mortality (US Experience)

27. Infectious diseases mostly affects the young and the elderly

28. Frequency of Pandemics since 1800 source: Gust et al. (2001)

29. Frequency Model • Time between pandemics • Exponential mean of about 30 years • Or is there a cycle?

30. CDC’s FluAid –Severity Model • Based on paper “Economic Impact of Pandemic Influenza in the United States: Priorities for Intervention”, Meltzer, et all, 1999 • Non-epidemiologic model used to estimate excess deaths, hospitalizations and resulting economic impact under various vaccine based interventions for a potential pandemic in the USA. • Applied FluAid model to Canadian individual inforce

31. FluAid • Key Assumptions

32. FluAid • At-risk groups assumed to be lives in ultimate period of mortality table and a fraction of substandard lives in the select period • Excess Mortality (default values)

33. FluAid Results

34. FluAid Model Relative to MCCSR Mortality Recommendation • CIA Capital and Risk Subcommittee • proposed required capital formula includes catastrophe component • 10% of expected claims • Consistent with 25% attack rate most likely estimate from FluAid application.