Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-10T16:10:29.699Z Has data issue: false hasContentIssue false

Adverse Selection Spirals

Published online by Cambridge University Press:  17 April 2015

Piet De Jong
Affiliation:
Department of Actuarial Studies, Macquarie University, NSW 2109, Australia. Email: piet.dejong@mq.edu.au
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

This article discusses risk classification and develops and discusses a framework for estimating the effects of restrictions on risk classification. It is shown that expected losses due to adverse selection depend only on means, variances and covariances of insurance factors and rates of uptake of insurance. Percentage loadings required to avoid losses are displayed. Correlated information, such as family history, is also incorporated and it is seen how such information limits losses and decreases required loadings. Although the evidence suggests that adverse selection is not, at present, a severe problem for insurers, this might change if the authorities impose restrictions on risk classification and/or customers gain an informational advantage (such as better knowledge of their own risk levels). Application is made to unisex annuity pricing in the UK insurance market.

Type
Articles
Copyright
Copyright © ASTIN Bulletin 2006

References

Ainslie, R. (2000) Annuity and insurance products for impaired lives. Presentation to the Staple Inn Actuarial Society.Google Scholar
American Academy of Actuaries Committee on Risk Classification (1980) Risk classification. Statement of Principles.Google Scholar
Armstrong, K., Weber, B., Fitzgerald, J., Hershey, G., Pauly, M., Lemaire, J., Subramanian, K. and Asch, D. (2003) Life insurance and breast cancer risk assessment: Adverse selection, genetic testing decisions, and discrimination. American Journal of Medical Genetics 120A(3), 35964.CrossRefGoogle ScholarPubMed
Australian Bureau of Statistics (2001) Deaths. Catalogue number 3302.0.Google Scholar
Babbage, C. (1826) A Comparative View of the Various Institutions for the Assurance of Lives. New York: AM Kelley. Reprinted in 1967.Google Scholar
Banks, G., Owen, H., and Kearney, B. (1997) Private health insurance. Industry Commission Inquiry 57, Australian Government Publishing Service, Canberra.Google Scholar
Barn, G., Berry, P., Brien, A., Bui, H., Burgess, F., Chan, P., Clarke, S., Hui, C., Knight, R., Longden, D., Mak, A., Service, D., Turner, S., and Whittaker, G. (2004) Report on the Lump Sum Experience Investigation 1998-1999. Institute of Actuaries of Australia Life Risk Insurance Committee.Google Scholar
Bowers, N., Gerber, H., Hickman, J., Jones, D., and Nesbitt, C. (1986) Actuarial Mathematics. Itasca, Illinois: Society of Actuaries.Google Scholar
Brown, R.L. and McDaid, J. (2003) Factors affecting retirement mortality. North American Actuarial Journal 7(2), 2443.CrossRefGoogle Scholar
Bühlmann, H. (1970) Mathematical methods in risk theory. Berlin: Springer-Verlag.Google Scholar
Chuffart, A. (1995) Genetic underwriting. Paper presented to the Actuarial Life Convention, Glasgow, December 1995.Google Scholar
Curry, C. and O’Connell, A. (2004) An analysis of unisex annuity rates. Working Paper Series Report 16, Equal Opportunity Commission.Google Scholar
De Ravin, J. and Rump, D. (1996) The right to underwrite. The Institute of Actuaries of Australia Quarterly Journal (September).Google Scholar
Dickson, P. (1960) Sun Insurance Office Ltd, 1710-1960: the history of two and a half centuries of British insurance. Oxford: Oxford University Press.Google Scholar
Doeer, T.S. (1984) Sex-based actuarial assumptions, Title VII, and the Equal Pay Act: employee benefit planning following Manhart and Norris. Rutgers Law Review 36(4), 839860.Google Scholar
Doyle, S., Mitchell, O., and Piggott, J. (2002) Annuity values in defined contribution retirement systems: Australia and Singapore compared. Research Discussion Papers 2-02, University of New South Wales Centre for Pensions and Superannuation Research.Google Scholar
European Commission (2004) Implementing the principle of equal treatment between women and men in the access to and supply of goods and services. Council Directive 2004113EC, European Commission.Google Scholar
Finkelstein, A. and Poterba, J. (2002) Selection effects in the United Kingdom individual annuities market. The Economic Journal 112, 2850.CrossRefGoogle Scholar
Gerber, H. (1990) Life Insurance Mathematics. Berlin: Springer-Verlag.CrossRefGoogle Scholar
Government Actuary’s Department (2005) UK Government Actuary: Interim Tables for 1990-1992.Google Scholar
Hall, C. (1991) Insurance firms retain bias over HIV tests, according to AIDS working party report. The Independent. March 6, 1991.Google Scholar
Hall, M. (1999) Restricting insurers use of genetic information: A guide to public policy. North American Actuarial Journal 3(1).CrossRefGoogle Scholar
Harper, P. (1992) Huntington disease and the abuse of genetics. American Journal of Human Genetics 50, 460464.Google ScholarPubMed
Harris, P. (1994) New AIDS question for UK life insurance. Reuters News. 26 July 1994.Google Scholar
Hellman, D. (1997) Is actuarially fair insurance pricing actually fair?: A case study in insuring battered women. Harvard Civil Rights – Civil Liberties Law Review 32, 355.Google Scholar
Hoem, J. (1969) Markov chain models in life insurance. Blatter der Deutschen Gessellschaft fur Versicherungsmathematik 9(2), 91107.Google Scholar
Hoem, J. (1988) The versatility of the Markov chain as a tool in the mathematics of life insurance. Transactions of the 23rd International Congress of Actuaries R, 171202.Google Scholar
Hoffman, F. (1900) History of the Prudential Insurance Company of America (Industrial Insurance) 1875-1900. Newark New Jersey: Prudential Press.Google Scholar
Hopegood, J. (1990) Department of health survey to examine AIDS test fears. Money Marketing. 20 December 1990.Google Scholar
Hurd, M. and McGarry, K. (2002). The predictive value of subjective probabilities of survival. Economic Journal 112, 966985.CrossRefGoogle Scholar
Jones, J. (1991) Insurance companies’ life cover questions stop thousands having AIDS test. The Independent. 25 July 1991.Google Scholar
Knox, D. and Tomlin, A. (1997) An analysis of pensioner mortality by pre-retirement income. Centre for Actuarial Studies Research Paper Series 44, University of Melbourne.Google Scholar
Lapham, E., Chahira, K. and Weiss, J. (1996) Genetic discrimination: Perspective of consumers. Science 274(5287), 621625.CrossRefGoogle ScholarPubMed
Le Grys, D. (1998) Life underwriting and reassurance. In Renn, D. (Ed.), Life, Death, and Money: Actuaries and the creation of financial security, Chapter 9, pp. 165177. Blackwell Publishers.Google Scholar
Leigh, T. (1990) Underwriting – a dying art? Journal of the Institute of Actuaries 117, 443532.CrossRefGoogle Scholar
Leigh, T. (1996) The freedom to underwrite. Presentation to the Staple Inn Actuarial Society.Google Scholar
Macdonald, A. (2000) Human genetics and insurance issues. In Torrance, I. (Ed.), Bio-ethics for the new millenium. St Andrew Press.Google Scholar
Macdonald, A.S. (1997) How will improved forecasts of individual lifetimes affect underwriting? British Actuarial Journal 3(15), 10091025.Google Scholar
Macdonald, A.S. (1999) Modeling the impact of genetics on insurance. North American Actuarial Journal 3(1), 83101.CrossRefGoogle Scholar
McGarry, K. and Finkelstein, A. (2003) Private information and its effect on long term equilibrium: New evidence from long term care insurance. Working Paper Series 9957, National Bureau for Economic Research.Google Scholar
Meikle, J. (1886) On the official publications of the mortality of assured lives. Transactions of the Actuarial Society of Edinburgh I.CrossRefGoogle Scholar
Mitchell, O. and McCarthy, D. (2001) Estimating international adverse selection in annuities. Working Paper Series 12, Pension Research Council.Google Scholar
Murthi, M., Orszag, J., and Orszag, P. (1999) The value for money of annuities in the UK: Theory, experience and policy. Birbeck Working Papers in Economics and Finance 19/99, University of London.Google Scholar
Nicoll, J. (1904) Life assurance without medical examination. Transactions of the Faculty of Actuaries II, 5789.Google Scholar
Norberg, R. (1995) Differential equations for moments of present values in life insurance. Insurance: Mathematics & Economics 17, 171180.Google Scholar
Nova Scotia Insurance Review Board (2004) A study into the use of gender as a rating factor in automobile insurance in Nova Scotia. Report to the governor in council.Google Scholar
Papworth, J. (1991) Insurance industry acts to ease worries over HIV tests. The Guardian. 6 April 1991.Google Scholar
Pauly, M.V., Withers, K.H., Subramanian, V.K., Lemaire, J., Hershey, J.C., Armstrong, K., and Asch, D.A. (2003) Price elasticity of demand for term life insurance and adverse selection. Working Paper W9925, National Bureau for Economic Research.CrossRefGoogle Scholar
Philipson, and Cawley, (1996) An empirical examination of information barriers to trade in insurance. Working Paper 5669, National Bureau for Economic Research.Google Scholar
Promislow, S. (1987) Measurement of equity. Transactions of Society of Actuaries 39, 215256.Google Scholar
Rothschild, M. and Stiglitz, J. (1976) Equilibrium in competitive insurance markets: The economics of markets with imperfect information. Quarterly Journal of Economics 90, 629649.CrossRefGoogle Scholar
Rothschild, M. and Stiglitz, J. (1997) Competition and insurance twenty years later. The Geneva Papers on Risk and Insurance Theory 22, 7379.Google Scholar
Skipper, H. and Black, K. (2000) Life and Health Insurance (13 ed.). Prentice Hall.Google Scholar
Society of Actuaries Individual Life Experience Committee (2004) Mortality under standard individually underwritten life insurance between 1995 and 2000 policy anniversaries. Mortality experience studies.Google Scholar
Spens, W. (1854) On the inadequacy of existing data for determining the rate of mortality among select lives. The Assurance Journal IV, 19.Google Scholar
Stenhouse, G. (1886) The mortality of assured lives viewed in relation to the sums at risk. Transactions of the Actuarial Society of Edinburgh II.Google Scholar
Subramanian, K.J. and Lemaire, A.S. (1999) Estimating adverse selection costs from genetic testing for breast and ovarian cancer: The case of life insurance. Journal of Risk and Insurance 66(4), 53150.CrossRefGoogle Scholar
Subramanian, K., Lemaire, J., Hershey, J., Pauly, M., Armstrong, K., and Asch, D. (1999) Estimating adverse selection costs from genetic testing for breats and ovarian cancer: The case of life insurance. Journal of Risk and Insurance 66, 531550.CrossRefGoogle Scholar
Sullivan, M. (1991) AIDS issues polarises the insurance industry, pressure groups, and the government. Post Magazine. 31 October 1991.Google Scholar
Thomas, R. (2001) Genetics and insurance. Response to the Human Genetics Commission Public Consultation.Google Scholar
Wilkie, A., McCutcheon, J., Forfar, D. and Leandro, P. (1999) Standard tables of mortality based on the 1991-94 experience. Continuous Mortality Investigation Report 17, Institute of Actuaries and Faculty of Actuaries Continuous Mortality Investigation Bureau.Google Scholar
Worsfold, D. (1991) Viscount Falkland attacks insurance industry lifestyle questions. Post Magazine. 14 February 1991.Google Scholar
Wright, W., Bakel, L., Monaghan, J., Szczepanski, C., Taylor, R., Wickman, A., Woods, P., Dieter, G. and Vass, G. (2002) The use of credit history for personal lines of insurance: report to the national association of insurance commisioners. Report to the NAIC, American Academy of Actuaries Risk Classification Subcommittee.Google Scholar