New research led by Dr Pradip Tapadar, Senior Lecturer in Actuarial Science at the School of Mathematics, Statistics and Actuarial Science (SMSAS), has found that as well as advancing social objectives such as non-discrimination, banning full risk classifications can make insurance markets more economically efficient.
Restrictions on insurance risks classifications are common in personal insurance markets such as life insurance, preventing insurance companies from using socially objectionable factors such as gender or genetic tests to set their prices. Yet, it has been argued by many economists and insurance commentators that this has negative effects on economic efficiency.
The new research published by Insurance: Mathematics and Economics calls into question this alleged trade-off. The team of researchers led by, Dr Tapadar, found that under plausible conditions, bans on risk classifications can simultaneously advance social objectives and increase economic efficiency. The optimal policy depends critically on detailed information about demand elasticities for higher and lower risks.
Dr Tapadar said: ‘Claims that governments need to make a trade-off between social objectives and well-functioning insurance markets when implementing regulations around insurance risk classifications may no longer be valid. Our research suggests that the required elasticity conditions for social welfare to be increased by a ban may indeed be realistic for some insurance markets.’
The research paper titled ‘When is utilitarian welfare higher under insurance risk pooling?’ is published by Insurance: Mathematics and Economics. (Indradeb Chatterjee, Kent; Pradip Tapadar, Kent; R. Guy Thomas, Kent; Angus S. Macdonald, Heriot-Watt University). doi: 10.1016/j.insmatheco.2021.08.006