Navigating Fairness in Insurance Pricing: The Role of AI and Actuarial Studies

The Growing Concern Over Bias in Insurance Pricing

The Casualty Actuarial Society (CAS) has recently published four new reports aimed at helping actuaries detect and address potential bias in property/casualty insurance pricing. These reports delve into various aspects of unintentional bias and propose forward-looking solutions. The first report, 'A Practical Guide to Navigating Fairness in Insurance Pricing,' addresses regulatory concerns about how the industry's increased use of models, machine learning, and artificial intelligence (AI) may contribute to or amplify unfair discrimination. It equips actuaries with the necessary tools to proactively consider fairness in their modeling process.

Regulatory Perspectives on Algorithmic Bias

The second report, 'Regulatory Perspectives on Algorithmic Bias and Unfair Discrimination,' presents the findings of a survey of state insurance commissioners. The survey reveals that while most commissioners are concerned about discrimination, few are actively investigating it. The majority believe that the onus should be on insurers to detect and test their models for potential algorithmic bias. This aligns with recent trends where regulators are increasingly scrutinizing the use of AI and machine learning in insurance pricing.

Balancing Risk Assessment and Social Fairness

The third report, 'Balancing Risk Assessment and Social Fairness: An Auto Telematics Case Study,' explores the use of telematics and usage-based insurance technologies to reduce reliance on sensitive information when pricing insurance. Traditional actuarial models often rely on demographic factors like age and gender, which some consider unfair. The CAS analysis found that telematics variables significantly reduce the need to include sensitive demographic data in claim frequency and severity models. This approach not only enhances fairness but also aligns with consumer preferences for personalized and transparent insurance products.

In conclusion, the integration of AI and advanced modeling techniques in insurance pricing presents both opportunities and challenges. To navigate this landscape effectively, actuaries and insurers must stay informed about regulatory trends and continuously evaluate their models for fairness. By doing so, they can ensure that their practices not only comply with regulations but also contribute to a more equitable and transparent insurance marketplace.