Casualty Actuarial Society Releases Final Report in Latest Phase of Race & Insurance Pricing Research Series

The Casualty Actuarial Society (CAS) has concluded the most recent phase of its CAS Research Paper Series on Race & Insurance Pricing with a report examining unintended impacts of bias mitigation. “Potential Unintended Impacts of Bias Mitigation in a Competitive Insurance Market,” investigates the balance between maintaining accurate risk differentiation and ensuring equitable treatment among various classes of interest when the use of certain rating variables is restricted or prohibited by insurance regulatory law. 

Launched in August 2024, the second phase of the CAS Research Paper Series on Race & Insurance Pricing has produced six papers offering insights into detecting and addressing bias in property-casualty insurance pricing. The reports build off the four original papers, launched in 2022, and progress from the series’ historical foundations to forward-looking solutions for quantifying and addressing potential bias. 

The second phase of the series helps insurance practitioners:

• Gain practical knowledge of methods to measure and mitigate bias in insurance pricing models, using case studies and technical tools.
• Recognize how incorporating alternative data, such as telematics, may reduce insurers’ reliance on sensitive or protected policyholder attributes while balancing predictive accuracy and fairness.
• Understand emerging regulations and their implications, including the evolving regulatory landscape for algorithmic bias and fairness in insurance pricing across jurisdictions, including the U.S., EU, Canada, and China.

Papers released in the second phase since August 2024 include:

“Potential Unintended Impacts of Bias Mitigation in a Competitive Insurance Market” by Gary Wang, FCAS, CSPA and Michael K. Chen, FCAS, CSPA

Using a collection of simulated scenarios, the authors review the impacts of a spectrum of regulatory approaches intended to improve fairness for a certain class of interest on both that class and an additional class of interest. 

“Practical Application of Bias Measurement and Mitigation Techniques in Insurance Pricing, Parts 1 & 2” by CAS Race and Insurance Pricing Research Task Force

This two-part report is intended as a practitioners’ guide for actuaries and insurance professionals responsible for building, maintaining, or updating insurance pricing models that satisfy multiple views of fairness. 

• Part 1 - Types of Bias, Imputing Protected Class, and Simple Fairness Tests
• Part 2 - Advanced Fairness Tests, Bias Mitigation, and Non-Modeling Considerations 

“A Practical Guide to Navigating Fairness in Insurance Pricing” by Jessica Leong, FCAS; Richard Moncher, FCAS; and Kate Jordan

This paper aims to create a framework to help insurers develop models that are more likely to comply with evolving regulations on unfair discrimination and bias.

“Regulatory Perspectives on Algorithmic Bias and Unfair Discrimination” by Lauren Cavanaugh, FCAS; Scott Merkord, FCAS; Taylor Davis, FCAS; and David Heppen, FCAS

This paper aims to explore regulatory perspectives on algorithmic bias in the U.S., including  state regulators’ concerns with current insurance pricing practices, perceptions of fairness testing approaches and plans for future activities.

“Balancing Risk Assessment and Social Fairness: An Auto Telematics Case Study” by Jean-Philippe Boucher, Ph.D. and Mathieu Pigeon, Ph.D.

This paper evaluates the potential for telematics or usage-based insurance rating variables to reduce insurers reliance on protected information, (e.g. sex, age), or sensitive information, (e.g. marital status, territory, credit).

“Comparison of Regulatory Framework for Non-Discriminatory AI Usage in Insurance,” By David Schraub, FSA; Jing Lang, FSA; Zhibin Zhang, FSA; and Mark A. Sayre, FSA. Produced with the Society of Actuaries. 

This joint report from the CAS and Society of Actuaries offers a comprehensive overview of the latest and emerging regulatory activities in China, the U.S., Canada, and Europe, focusing on the prevention of discriminatory practices in the use of artificial intelligence (AI) within the insurance industry. It has a particular relevance to international audiences.

Launched in 2022, the CAS Research Paper Series on Race & Insurance Pricing was designed to guide the insurance industry toward proactive, quantitative solutions to identify, measure and address potential racial bias in insurance pricing. The series also reflects the CAS’s commitment to equipping and empowering actuaries and the broader insurance industry with tools to better understand and address potential bias in insurance pricing. 

The CAS invites anyone with an interest in collaborating on future research or educational opportunities on these critical topics to contact Mallika Bender at mbender@casact.org.

To view the entire series, visit the CAS Research Paper Series on Race & Insurance Pricing website.