The Casualty Actuarial Society has created a series of papers that examines the topic of race and insurance pricing. It aims to constructively contribute to the policy debate around it.
According to CAS, determining insurance costs is a challenging and complex undertaking.
Actuaries need to be able to discern between various risk factors while avoiding undue bias.
However, it’s important for us to stay up to date on changes in how discrimination is defined, judged, and judged as a society
Four papers were generated by the CAS research. Two of them have been published this week and two more will be published on March 31. These papers define, quantify, as well as propose methods to address unfair discrimination wherever it is discovered.
It is easy to get confused about insurance ratings. This is due to the complexity of predictive models that are being used today. Machine learning and algorithms are promising tools for ensuring equitable pricing. Research has shown that these tools can also increase biases that are able to sneak into their programming.
The Colorado legislature has recently required that insurers show that they use complex algorithms and external data to ensure that they don’t discriminate against certain classes.
These inequalities can be addressed by policymakers and corporate decision-makers through the actuarial discipline.