1. Mortality and Longevity Research Mortality Working Group IAA Meeting, St Petersburg, Russia Friday May 27 2016 Michael Sherris CEPAR, AIPAR UNSW Business School School of Risk and Actuarial Studies UNSW

2. What is CEPAR? ARC Centre of Excellence in Population Ageing Research (CEPAR) http://www.cepar.edu.au/http://www.cepar.edu.au/ Multi-disciplinary, multi-university research centre focussing on population ageing research UNSW focus is actuarial science and economics Established in 2011 Actuarial research includes: mortality and health models, annuity pricing and insurer solvency, long term care insurance, reverse mortgages, risk management and hedging, housing and aged care financing Supported actuarial researchers: 10 PhD’s (6 completed, 4 current), 10 honours, and 10 Postdocs (2 current, 4 entered academia, 4 entered industry) 2

3. Actuarial Research in Longevity at UNSW Overview Longevity risk and mortality models Consistent modelling framework Smooth (parametric) mortality curve Closed form survival probabilities Risk adjustment in financial framework Challenges – model estimation, market price of risk Health and functional disability Multiple state models and heterogeneity Cause of death models Aggregate mortality improvement Challenges – individual health data over long periods Longevity risk and mortality models Consistent modelling framework Smooth (parametric) mortality curve Closed form survival probabilities Risk adjustment in financial framework Challenges – model estimation, market price of risk Health and functional disability Multiple state models and heterogeneity Cause of death models Aggregate mortality improvement Challenges – individual health data over long periods Funding Health and Care Risks Modelling functional disability LTC and housing, reverse mortgages and equity release, care annuities Challenges – government provision, public-private risk and cost sharing Individual decision making Pre-retirement and post retirement Annuities, housing, health, LTC, pension and health costs Challenges – data at individual level, calibration of realistic models Funding Health and Care Risks Modelling functional disability LTC and housing, reverse mortgages and equity release, care annuities Challenges – government provision, public-private risk and cost sharing Individual decision making Pre-retirement and post retirement Annuities, housing, health, LTC, pension and health costs Challenges – data at individual level, calibration of realistic models Retirement Income and Annuities Innovative product design, risk sharing, care annuities Costly capital, demand and supply Portfolio decisions including equity investments, long term care insurance, housing Variable annuities and guarantees Challenges – lack of product market, government provision Retirement Income and Annuities Innovative product design, risk sharing, care annuities Costly capital, demand and supply Portfolio decisions including equity investments, long term care insurance, housing Variable annuities and guarantees Challenges – lack of product market, government provision Life insurer, reinsurer risk management Capital costs, reinsurance, long term solvency Natural hedging Role of financial markets Hedging equity, interest rate and mortality/longevity risk Challenges – limited life annuity markets, lack of wholesale financial markets (basis risk) Life insurer, reinsurer risk management Capital costs, reinsurance, long term solvency Natural hedging Role of financial markets Hedging equity, interest rate and mortality/longevity risk Challenges – limited life annuity markets, lack of wholesale financial markets (basis risk)

4. Mortality and Health Models Systematic mortality risk - Consistent dynamic mortality model (Blackburn and Sherris, 2013) and Cohort models (Yajing Xu, PhD student; Yang and Sherris, 2015) Heterogeneity - Health status and Markov Ageing model (Su and Sherris 2012; Sherris and Zhou 2014 ) Frailty models (Su and Sherris 2012; Fong, Sherris, and Yap 2015) Systematic mortality and heterogeneity (Xu, Meyricke, Sherris 2015; Shao, Chen, Sherris 2016) Functional disability and multiple state models (Fong, Shao, Sherris 2015; Li, Shao, Sherris 2016) 4

5. Consistent Dynamic Mortality Model Factor model for mortality (age x, current time t survival to time T Risk factors Mortality rate dynamics 5 Source: Blackburn and Sherris (2013)

6. Consistent Dynamic Mortality Model Survivor curve Multiple factors Swedish mortality 1910 to 2007 ages 50 to 100 6 Source: Blackburn and Sherris (2013)

7. Heterogeneity in Australian Population Mortality Markov Physiological Age Model Frailty Model Source: Shu and Sherris (2010)

8. Age – Period – Cohort Models Trend models - birth year or cohort effect a significant trend factor Period effects less significant (Spanish flu) Links to Lee-Carter 8 Source: Alai and Sherris (2014)

9. Cohort mortality models 9 Mortality improvement approximately linear in age Volatility is exponential in age Risk factors (changes in mortality) not perfectly correlated across cohorts Source: Yang and Sherris (2015)

10. Multi-State Actuarial Models of Functional Disability 10 Disability & recovery transition intensities estimates In U.S.: -Rates of becoming LTC disabled significantly higher for women than men. -Force of disability > mortality hazard for females of all ages. -Distinct age patterns of recovery. Source: Fong, Shao, and Sherris (2015)

11. LTC Insurance 11 -Use of HRS individual panel data -Estimation methodology using individual data Source: Shao, Sherris and Fong (2015)

12. Selected Publications and Research Working Papers Alai, D.H. and Sherris, M. (2014), Rethinking Age-Period-Cohort Mortality Trend Models, Article published on line 16 Apr 2012, Scandinavian Actuarial Journal, DOI: 10.1080/03461238.2012.676563, Volume 2014, Issue 3, April 2014, Pages 208-227. Alai, D., Chen, H., Cho, D., Hanewald, K. and Sherris, M., (2014), Developing Equity Release Markets: Risk Analysis for Reverse Mortgages and Home Reversions, North American Actuarial Journal, Volume 18, Issue 1, January 2014, Pages 217-241. Blackburn, C. and Sherris, M., (2013), Consistent Dynamic Affine Mortality Models for Longevity Risk Applications. Insurance: Mathematics and Economics. Vol 53, Issue 1, 2013, Pages 64-73. http://dx.doi.org/10.1016/j.insmatheco.2013.04.007http://dx.doi.org/10.1016/j.insmatheco.2013.04.007 Fong, H. Y., Shao A.W., and Sherris, M. (2015), Multi-State Actuarial Models of Functional Disability, North American Actuarial Journal, Volume 19, Issue 1, January 2015, Pages 41-59. Fung, M. C., Ignatieva, K. and Sherris, M., (2014), Systematic Mortality Risk: An Analysis of Guaranteed Lifetime Withdrawal Benefits in Variable Annuities, Insurance: Mathematics and Economics, Volume 58, September 2014, Pages 103-115. Meyricke, R., and Sherris, M., (2014), Longevity risk, cost of capital and hedging for life insurers under Solvency II, Insurance: Mathematics and Economics, Volume 55, March 2014, 147-155. Nirmalendran, M., M. Sherris and K. Hanewald, (2014), Pricing and Solvency of Value-Maximizing Life Annuity Providers, ASTIN Bulletin, Vol 44, Issue 1, Pages 39-62.

13. Selected Publications and Research Working Papers Shao, A.W., Hanewald, K., and Sherris, M., (2015), Reverse Mortgage Pricing and Risk Analysis Allowing for Idiosyncratic House Price Risk and Longevity Risk, accepted 2 March 2015, Insurance: Mathematics and Economics. Wong, A., Sherris, M. and Stevens, R., (2015), Natural Hedging Strategies for Life Insurers: Impact of Product Design and Risk Measure, accepted 5 January 2015, Journal of Risk and Insurance. Blackburn, C., Hanewald, K. Olivieri, A. and Sherris, M., (2013), Life Insurer Longevity Risk Management, Solvency and Shareholder Value. Chang, Yang and Sherris, M., (2015), A Value-Based Cohort Index for Longevity Risk Management. Fong, J.H., Sherris, M. and Yap, J., (2015), Forecasting Disability: Application of a Frailty Model. Shao, A.W., Sherris, M., and Hanewald, K., (2013), Measuring House Price Growth and the Impact of Property Characteristics. Shao, A.W., Sherris, M., and Fong, J.H., (2015), Product Pricing and Solvency Capital Requirements for Long-Term Care Insurance. Xu, M., Sherris, M. and Meyricke, R., (2015), Mortality Heterogeneity and Systematic Mortality Improvement.

14. m.sherris@unsw.edu.au http://www.cepar.edu.au/ Michael Sherris CEPAR, Risk and Actuarial Studies UNSW Business School UNSW Michael Sherris CEPAR, Risk and Actuarial Studies UNSW Business School UNSW http://papers.ssrn.com/author=410919 http://papers.ssrn.com/author=410919