Loss Coverage
Why Insurance Works Better with Some Adverse Selection

This book argues that, contrary to received wisdom, some adverse selection in insurance markets is beneficial to society as a whole.

Guy Thomas (Author)

9781107100336, Cambridge University Press

Hardback, published 11 May 2017

282 pages, 25 b/w illus. 9 tables
23.5 x 15.7 x 2 cm, 0.52 kg

'In summary, Loss Coverage offers policymakers, academics, professionals, students, and other interested parties useful insight into the 'problem' of adverse selection. Thomas employs simple and timely real-world examples to make the concepts of adverse selection, loss coverage, and risk classification more understandable and relevant for policy decisions, offering a path toward mitigating concerns over unfair discrimination while increasing insurance market efficiency.' William L. Ferguson, Journal of Risk and Insurance

Most academic and policy commentary represents adverse selection as a severe problem in insurance, which should always be deprecated, avoided or minimised. This book gives a contrary view. It details the exaggeration of adverse selection in insurers' rhetoric and insurance economics, and presents evidence that in many insurance markets, adverse selection is weaker than most commentators suggest. A novel arithmetical argument shows that from a public policy perspective, 'weak' adverse selection can be a good thing. This is because a degree of adverse selection is needed to maximise 'loss coverage', the expected fraction of the population's losses which is compensated by insurance. This book will be valuable for those interested in public policy arguments about insurance and discrimination: academics (in economics, law and social policy), policymakers, actuaries, underwriters, disability activists, geneticists and other medical professionals.

Part I. Introduction: 1. The central ideas of this book
2. Adverse selection: a history of exaggeration
Part II. Loss Coverage: 3. Introduction to loss coverage
4. Basic mathematics of loss coverage
5. Further mathematics of loss coverage
6. Partial risk classification, separation and inclusivity
Part III. Further Aspects of Risk Classification: 7. A taxonomy of objections to risk classification
8. Empirical evidence on adverse selection
9. Myths of insurance rhetoric
10. Myths of insurance economics
11. Contexts where adverse selection may be stronger
12. Risk classification and moral hazard
13. Risk classification and big data
Part IV. Conclusion: 14. Summary and suggestions
Appendix A. Alternative demand functions
Appendix B. Multiple equilibria: a technical curiosity
References
Index.

Subject Areas: Insurance & actuarial studies [KFFN], Finance [KFF], Economic statistics [KCHS], Economics [KC]