Sources of adverse selection in insurance markets with genetic information

Abstract

In this thesis we quantify costs of adverse selection in insurance markets where there are multiple sources of adverse selection. We aim to find the relative impact of genetic information as one of these sources. Using new data on the effects of components of a polygenic model of breast cancer, we model adverse selection in a critical illness insurance market. We confirm the results of a previous study, which used a simpler polygene model without details of particular genes, that polygenes pose a greater source of adverse selection risk than the major genes (BRCA1 and BRCA2). In a start-up market for long-term insurance, we model the progression of adverse selection costs over time, where premiums are repriced to adapt to the information the insurer gains about its business mix from its claims experience. In a U.K. setting we find the greatest costs of adverse selection come from a hypothetical intermediate stage of dementia progression which is not visible to an insurer, while testing of the APOE gene poses very little risk. We find the U.K. government's proposed cap on care liability has very little impact on adverse selection costs, as it benefits a very small proportion of people.