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The Impact of Genetic Information on the Insurance Industry: Conclusions from the ‘Bottom-Up’ Modelling Programme

Published online by Cambridge University Press:  09 August 2013

Angus Macdonald  and
Fei Yu
Angus Macdonald
Affiliation:
Department of Actuarial Mathematics and Statistics and the Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, U.K.Tel: +44(0)131-451-3209, Fax: +44(0)131-451-3249, E-Mail: A.S.Macdonald@hw.ac.uk
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Abstract

We quantify the overall impact of genetic information on the insurance industry using the ‘bottom-up’ approach, in which detailed models are constructed of representative major genetic disorders. We consider six such disorders, namely adult polycystic kidney disease, early-onset Alzheimer's disease, Huntington's disease, myotonic dystrophy (MD), hereditary non-polyposis colorectal cancer; and breast/ovarian cancer. Actuarial models based on the epidemiological literature exist for all these except MD. We parameterise a suitable model of MD, then synthesize the results from all six models to estimate the adverse selection costs arising from restrictions on insurers' use of genetic information. These are all very small, only in the most extreme cases rising above 1% of premiums. In the worst case — females displaying ‘extreme’ adverse selection in a ‘small’ critical illness insurance market, with the use of family history banned — the cost is about 3% of premiums. Our model includes the most common single-gene disorders relevant to insurance, and includes representatives of most important classes of these disorders. While the ‘bottom-up’ approach could be continued by modelling more and more diseases, we suggest that our model is adequate to draw robust conclusions.

Keywords

Adverse SelectionCritical Illness InsuranceFamily HistoryGenetic TestsLife InsuranceSingle-Gene Disorder
Type
Research Article
Information
ASTIN Bulletin: The Journal of the IAA , Volume 41 , Issue 2 , November 2011 , pp. 343 - 376
Copyright
Copyright © International Actuarial Association 2011

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