It seems straightforward to base insurance costs on the degree of risk assumed.
If insurers had to determine a fixed price for coverage without taking into account specific risk considerations, such as the probability of needing to submit a claim, insurance would be prohibitively expensive for everyone, with the lowest-risk policyholders subsidizing the riskiest.
Risk-based pricing enables insurers to offer the lowest premiums to policyholders with the best risk factors by allowing them to underwrite a wider range of coverages, improving both the accessibility and affordability of protection.
There are issues when other criteria are combined with actuarially sound rating elements in ways that could be interpreted as unduly discriminatory.
For instance, questions have been made regarding the use of geography, home ownership status, credit-based insurance ratings, and driving histories when determining the cost of home and auto insurance premiums.
According to critics, this might result in “proxy discrimination,” with individuals of color in urban areas frequently paying more for the same coverage than their suburban counterparts.
The use of gender as a rating component has also drawn criticism.
I have released a new Issues Brief that succinctly discusses risk-based pricing, the predictive power of rating criteria, and their significance in keeping insurance costs down while enabling insurers to keep the cash on hand needed to fulfill their obligations to policyholders.
The teams of actuaries and data scientists that insurers employ to measure and differentiate among a variety of risk characteristics while avoiding unfair discrimination are essential to fair pricing and reserving.
In today’s insurance market, unfair discrimination has no place, the brief declares.
In today’s diverse culture, discrimination based on any factor that doesn’t directly affect the insured risk would not only be illegal but also bad for business.