Insurance rating factors and other practices have come under intense scrutiny by consumer advocates and regulators, as part of a broader focus in the United States on the potential impacts of societal systemic bias. What lessons can we learn from other financial services industries and their approaches to addressing racial bias? How can we quantify and measure discriminatory effects in insurance models? Join the CPCU Society in partnership with the Casualty Actuarial Society for part two of our webinar series on race and insurance pricing.
This session will provide an overview of two research papers commissioned as part of the Casualty Actuarial Society's Approach to Race and Insurance Pricing - Approaches to Address Racial Bias in Financial Services: “Lessons for the Insurance Industry and Methods for Quantifying Discriminatory Effects on Protected Classes in Insurance,” presented by Radost Wenman, FCAS, MAAA, CSPA, and “Solutions in Financial Services,” presented by Robin Harbage, FCAS, MAAA.
Attendees are encouraged to consider how solutions to bias in other industries, and statistical methods to identify bias could be applied to their area of focus in Insurance.
Presenters:
Robin Harbage, FCAS, MAAA
Principal
Robin Austin, LLC.
Robin Harbage is a former insurance executive now advising and investing in start-up organizations in insurance, technology, and beer. Robin worked in a wide variety of roles including the global telematics practice at Willis Towers Watson. For Progressive Insurance, Robin served as general manager, managing marketing, product development, sales, and claims, and as vice president actuarial.
Robin has a BA in mathematics from The College of Wooster and an MBA in finance from Ohio State University. He is a fellow of the Casualty Actuarial Society and a member of the American Academy of Actuaries.
Radost Wenman, FCAS, MAAA, CSPA
Senior Consulting Actuary
Pinnacle Actuarial Resources, Inc.
Radost Wenman has been in the property/casualty industry since 2006, focusing on pricing and product development. In this role, she has developed homeowners, private passenger auto and commercial lines pricing solutions through the design and implementation of advanced predictive models.
Radost performs traditional actuarial analyses, including assessment of company financial experience, overall rate level indications, rate and rule filings, and regulatory support. She develops risk classification plans through assessment of underwriting profitability, competitive analysis and research of insurance laws. She also performs rate filing reviews for departments of insurance.
Radost also designs, builds and evaluates statistical models, incorporating supervised and unsupervised techniques for a variety of applications in the insurance domain, including a) pricing and risk classification, b) underwriting tiers, c) territory definitions, d) claims triage and e) customer conversion and retention. She also manages, assesses and transforms data to enhance the utility of statistical models.
Radost researches the topics of Bayesian statistics, methods for missing data imputation, and unsupervised algorithms for outlier and anomaly detection.