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References. Lemaire et al : Pricing Term Insurance in the Presence of a Family History of Breast or Ovarian Cancer. North American Act. J., 2000, 75-87

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  1. References • Lemaire et al: Pricing Term Insurance in the Presence of a Family History of Breast or Ovarian Cancer. North American Act. J., 2000, 75-87 • Subramanian et al: Estimating Adverse Selection Costs From Genetic Testing for Breast and Ovarian Cancer: The Case of Life Insurance. J. of Risk and Insurance, 1999, 66, 531-550

  2. Adverse Selection from Genetic Testing for BRCA in a Term Life Insurance Market. Inelastic and Elastic Demands Jean Lemaire The Wharton School Krupa Subramanian Temple University

  3. Genetic Tests and their Implications in Insurance Jean Lemaire Wharton School Krupa Subramanian Temple University

  4. Genetic Testing in the News • Humane Genome Project • Clinton Executive Order • DNA testing on death row • UAE require testing prior to marriage • Greek Orthodox Church requires testing • Pre-marital counseling in Sardinia • Alzheimer-free embryos • Fear of job and insurance discrimination in public

  5. Genetic Diseases (% of carriers) • Huntington’s Disease • Cystic Fibrosis • 1/2,500 US whites • 1/17,000 US African-Americans • Tay-Sachs Disease • 1/27 US Ashkenazi Jews • 1/250 US Sephardic Jews • High Accadians, Cajuns

  6. Sickle-Cell Anemia • 1/4 Central Africa • BRCA • 1/43 US Ashkenazi Jews • 1/833 US whites • High Iceland, Thailand • Six-fingered Drawfism • High Amish, Pennsylvania

  7. Genes impact other diseases • Alzheimer’s Disease • Diabetes • Manic Depression • Schizophrenia • Multiple Sclerosis • Rheumatoid Arthritis • Thalassemia • Haemophilia and over 1,100 others • Over 800 tests offered

  8. Genetic Testing Issues • Privacy concerns • Voluntary testing • Job and insurance discrimination • Regulation addressing genetic testing • Adverse selection in insurance markets

  9. Existing Legislation • 1. Laissez-faire (Australia, Canada, Japan, Ireland, Portugal, Spain) • 2. Disclosure Duty (Germany, New Zealand) • 3. Consent Law (Netherlands, Switzerland) • Strict Prohibition (Austria, Belgium, Denmark, France, Italy, Norway)

  10. In the absence, or in addition to, legislation • Voluntary agreement with state (Sweden) • Moratorium (Germany, Finland, Greece, Netherlands, Switzerland, UK) • Code or conduct or guidelines (Australia, South Africa) • United States: Laws in 44 states • UK: Moratorium, approval of specific tests

  11. Breast Cancer Ovarian Cancer One woman in nine will develop breast cancer (BC) in her lifetime - one in forty will die from the disease 1.8% of women will develop ovarian cancer (OC) - over 60% will die from it. Family history multiplies the risk by 5.4 A very small percentage of women have either BRCA1 or BRCA2 mutations.

  12. 95% of BC are not inherited • They result from diet, lifestyles, environment, social exposures, and many other factors, known and unknown • Early menarchy • Late menopause • First pregnancy past 30 years of age • Hormone replacement therapy • Birth control pills

  13. Tests for the BRCA mutation • About 5% of BC and OC are the results of a gene mutation (BRCA 1 or BRCA 2) • Since late 1997, commercial tests are available to detect the gene mutation • Full-length screening of BRCA: $2,400 • Test of four mutations in BRCA1: $295 (“Ashkenazi test”)

  14. Breast Cancer Ovarian Cancer Lifetime Cancer Risks for BRCA1/2: - breast (female): 56-85% - breast (male): 6% - ovarian: 10-60% - prostate, colon, pancreas cancers Without the mutation, the age at onset is Normal(68, 225). With the mutation, the age at onset is Normal(55, 225).

  15. Estimates from Claus et al Cumulative Probability of developing BC for a woman who has one First-Degree relative affected with BC, by age of onset of the affected relative Age of woman age of onset in affected relative 20-29 30-39 40-49 50-59 60-69 70-79 29 .007 .005 .003 .002 .002 .001 39 .025 .017 .012 .008 .006 .005 49 .062 .044 .032 .023 .018 .015 59 .116 .086 .064 .049 .040 .035 69 .171 .130 .101 .082 .070 .062 79 .211 .165 .132 .110 .096 .088

  16. Double Decrement Model for BC Alive, without BC Alive, with BC Death, from causes other than BC Death, affected with BC

  17. Double Decrement Model for BC

  18. Double Decrement Model for OC

  19. BC Survival Probabilities • Exponential Decay, with 3.6% annual death probability

  20. OC Survival Probabilities

  21. The Separation Method • Cij = pi Ii+j-1

  22. OC Survival Probabilities

  23. Mortality Ratios for 30 year old woman, according to family history

  24. Mortality Ratios for Common Conditions and Diseases

  25. Relative cost of term insurance(No Family History: Cost = 100)

  26. Adverse Selection Markov Model • First model: Inelastic Demand • Discrete-state, continuous-time Markov Model

  27. Implicit Cost of Adverse Selection = E.V. of Claim costs (Full information) E.V. of Claim costs (Allowable information) Each state for which there is an outward transition translates to a differential equation (Thieles’s differential equation for reserves).

  28. Behavioural Assumptions Inelastic demand for insurance Rate of genetic testing: 0.05 Force of Interest: 0.05 Rate of insurance purchase: 0.05 Rate of lapsing before testing: 0.05 Rate of re-entry into State 1 from lapse state: 0.25

  29. Behavioural Assumptions • If insured and test positive: • P(more insurance) = 0.27 • P(same insurance) = 0.70 • P(less insurance) = 0.02 • P(lapse policy) = 0.01 • If insured and test negative: • P(more insurance) = 0.01 • P(same insurance) = 0.75 • P(less insurance) = 0.17 • P(lapse policy) = 0.07

  30. Mortality improvements • Assumption: no mortality improvements • Conservative since: • Overall improvement: 0.65% per year • Oophorectomy (-50%) • Mastectomy (-90%) • Tamoxifen (-40%)

  31. Adverse selection costs for a woman with no family history of BC or OC, insured at onset; basic benefit $1

  32. Adverse selection costs for a woman with One FDR with OC. Age at onset: unknown

  33. Adverse selection costs for a woman with one FDR with BC, age at Onset: 20-29.

  34. Adverse selection costs for a woman with two FDR with BC, Age at Onset: 20-29

  35. Sensitivity Analysis: 40-year old Woman, 2 FDR with BC

  36. Adverse selection costs for a woman with two FDR with BC, age at Onset 20-29, who claims no family history of BC or OC;

  37. Sensitivity Analysis: 40-year old Woman, 2 FDR with BC, but reports No family history of BC or OC

  38. Second Model: Elastic Demand • Discrete-state, discrete time Markov model • A cohort of 1,000 women is tracked down for 20 years. Initially they are all insured for $100,000 under an annually renewable term policy, and untested for BRCA • Three decrements from initial cohort: death, lapse, testing for BRCA mutation • All may change their benefit each year

  39. Adverse selection results from • Differentiated lapsing rates: women testing positive will exhibit a lower lapsing rate • Differentiated benefits: women testing positive are more likely to increase their benefits • Different reactions to price increases: women testing positive are more likely to accept a price increase

  40. The insurance company • Will increase premiums as a result of adverse selection • Myopic reaction of insurer is assumed: each year, it calculates past losses, and attempts to recoup them by increasing premiums • The same % premium increase is applied to each rating cell • Twelve rating cells: Ages 30, 40, 50. 1 FDR-BC, 2 FDR-BC, 1 FDR OC, No family history

  41. The insurer never fully recovers losses, as it is always one step behind: it does not anticipate the fact that customers constantly change insurance purchasing behaviour as a result of pricing decisions • Other pricing strategies are possible: the insurer could anticipate future mortality trends in portfolio

  42. Elastic Demand • Marshall’s Law of Demand: • PλQ = Cst • λ is the constant elasticity of demand with respect to price: • λ = - (dQ/Q) / (dP/P) • We expect “price elasticity” parameters such that λpositives < λuntested < λnegatives

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