Restrictions on risk classification can lead to adverse selection, and actuaries usually regard this as a bad thing. However, restrictions do exist in many countries, suggesting that policymakers often perceive some merit in such restrictions. Careful re-examination of the usual actuarial arguments can help to reconcile these observations.

Models of insurance purchasing behaviour under different risk classification regimes can quantify the effects of specific regulatory frameworks such as banning the use of genetic test results or EU restrictions on gender classification.

Areas of research

Adverse selection and loss coverage

Actuaries tend to take a negative view of adverse selection because…

If insurers cannot charge risk-differentiated premiums, more insurance is bought by higher risks and less insurance is bought by lower risks. This raises the equilibrium pooled price of insurance above a population-weighted average of true risk premiums. Also, since the number of higher risks is usually smaller than the number of lower risks, the total number of risks insured usually falls. This combination of a rise in price and fall in demand is usually portrayed as a bad outcome, both for insurers and for society.

Dr Pradip Tapadar

This argument overlooks one point: with adverse selection, expected losses compensated by insurance can be higher than with no adverse selection. The rise in equilibrium price with adverse selection reflects a shift in coverage towards higher risks.

From a public policymaker’s viewpoint, this means that more of the “right” risks, i.e. those more likely to suffer loss, buy insurance. If the shift in coverage is large enough, it can more than outweigh the fall in numbers insured. This result of higher expected losses compensated by insurance – higher “loss coverage” – might be regarded by a public policy-maker as a better outcome for society than that obtained with no adverse selection.

Ongoing work by Dr Pradip Tapadar and Guy Thomas building on this insight includes investigations of adverse selection and loss coverage under various insurance demand functions and risk classification regimes; links from utility-based models of insurance purchasing to insurance demand and loss coverage; and reconciliation of the concept of loss coverage with the economists’ concept of social welfare.

Genetics and insurance

Guy Thomas

In the past 20 years, insurers’ use of genetic test results has been banned or restricted in many countries. However, there is a perception that if genetic information continues to be treated as private, and insurance companies are not allowed access to it, adverse selection becomes possible.

This debate on the implications of using an individual’s genetic information for insurance underwriting purposes has become all the more critical with the advent of large-scale investigations, such as the UK Biobank project, which studies the combined effects of genotype and environmental exposures on the risk of common diseases.

Dr Pradip Tapadar and Guy Thomas have various publications on genetics, insurance and underwriting spanning nearly 20 years. Their work in this area quantifies the implications of such restrictions on the use of predictive genetic test results on society as a whole.

Price optimisation

In consumer insurance, many insurers apply individual variations in prices which are not related to individual risk. For example, in motor or household insurance, the price for a renewing customer is often higher than the price for a risk-equivalent new customer. Practitioners usually call this “price optimisation”, but from a public policy perspective, it is not obvious that insurance prices with non-risk individual variations are optimal (although in some circumstances they may be).

Guy Thomas investigates the effects of insurance price optimisation on society as a whole.