Abstract
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).
Issue
3
Series
II
Year
2024
Keywords
Bias Model, Governance, Algorithmic Bias
Description
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).
Categories
Credit Scoring
Generalized Linear Modeling
Homeowners
Personal
Rate Regulation
Ratemaking
Ratemaking Considerations
Publications
Research Paper Series on Race and Insurance Pricing
Formerly on syllabus
Off
