A Fair Price to Pay: Exploiting Causal Graphs for Fairness in Insurance
A causal graph tailored for insurance gives formal definitions of direct and indirect discrimination, and sorts fair pricing methodologies into five families by the fairness properties they can deliver.
Talks (13)
CAS (webinar), 2026AAA (webinar), 2026Department of Mathematics, Stockholm University, 2026ARC (AAA invited panel), 2025ARC (CAS invited session), 2025Chaire ACTIONS, 2025Institut intelligence et données, 2024IMEC, 2024Workshop on fairness and discrimination in insurance, 2024Autorité des marchés financiers, 2024 Industry: Milliman Paris, Intact Financial Corporation, Desjardins Groupe d'assurances générales
BibTeX
@article{Cote/etal:2024,
author = {Côté, Olivier and Côté, Marie-Pier and Charpentier, Arthur},
title = {A fair price to pay: Exploiting causal graphs for fairness in insurance},
journal = {Journal of Risk and Insurance},
volume = {92},
pages = {33-75},
year = {2025},
keywords = {bias, causal inference, directed acyclic graph, discrimination, disparate impact, fairness criteria, score},
doi = {https://doi.org/10.1111/jori.12503},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jori.12503},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/jori.12503}
}