Actuarial Studies Tackle Bias, AI, and Modeling in Insurance Pricing

The Casualty Actuarial Society (CAS) has released four reports aimed at addressing bias in property/casualty insurance pricing models. These studies focus on the role of AI and advanced modeling techniques in potentially contributing to unfair discrimination and offer strategies for actuaries to mitigate this risk. The first report, "A Practical Guide to Navigating Fairness in Insurance Pricing," helps actuaries understand regulatory concerns regarding AI and machine learning, offering tools to ensure fairness in pricing.

The second paper surveys U.S. state insurance commissioners, revealing that most regulators are concerned about algorithmic bias but believe that insurers should bear the responsibility for testing their models. The third report uses telematics to suggest how insurers can reduce reliance on demographic factors like age and gender, offering a case study from auto insurance to demonstrate how usage-based data can support fairer pricing. The final report compares international regulatory frameworks, emphasizing the need for transparency and accountability in AI use. Actuaries are urged to stay informed on these trends to remain compliant and ensure non-discriminatory practices.