Fairness of predictive models: an application to insurance markets

This project addresses biases within the automatic artificial intelligence algorithms utilized to determine optimal pricing in individual policies. Its aim is to mitigate or eliminate such biases, which could lead to inequities or discriminatory practices based on factors such as gender, race, religion, or origin in the coverage provided by insurers or reinsurers to policyholders.  

The research topic has both theoretical significance, as it involves enhancing control over the "black box" nature of AI-based models, and practical importance, as it aims to reduce risks associated with discrimination and inequality. Given the increasing influence of social networks and the consequential reputational challenges faced by insurers and reinsurers, this issue is particularly relevant and timely.

Fields of research / technical cooperation 
Actuarial science

Arthur Charpentier, PhD, Fellow of the French Institute of Actuaries*, is full professor at UQAM, Montreal, Canada, and Université de Rennes, in France. He is member of the editorial board of the Journal of Risk and Insurance, the ASTIN Bulletin, and Risks. He edited, a few years ago, Computational Actuarial Science with R (CRC), and more recently wrote Insurance, Biases, Discrimination and Fairness (Springer). He is also the former director of the Data Science for Actuaries program of the French Institute of Actuaries. He is a Louis Bachelier Fellow, and his recent work is about climate change and predictive modeling insurance, more specifically in the context of fairness and discrimination.

Alma mater: MSc in actuarial science ENSAE (1999, Paristech, France), MSc in mathematical economics Paris Dauphine (1999, PSL, France), PhD in applied mathematics KU Leuven (2006, Belgium), HDR* in applied mathematics Université de Rennes (2016, France).    Arthur Charpentier - Curriculum Vitae     Arthur Charpentier - Blog

Insurance, Biases, Discrimination and Fairness (Springer)

Overview of the book
Author: Arthur Charpentier

  • An account of fairness in predictive models
  • Discusses fairness issues arising from big data and algorithms
  • Addresses a topic of high interest to actuaries and regulators

Project activities & events

• Annual conference of the Canadian Econometrics Study Group
  Abstract - Presentation - "Calibration of Probabilistic Scores of Classifiers" - December 2024
  Based on two papers:
  • Paper #1 - "From Uncertainty  to Precision: Enhancing Binary Classifier Performance through Calibration" - February 2024
  • Paper #2 - "Probabilistic Scores of Classifiers, Calibration is not Enough" - August 2024
   

• "Actuarial ethics and the future of the profession"
  Arthur Charpentier gave an interview to Jennifer Baker, for The European Actuary, volume 40
  Interview - December 2024
   
• "Selection bias in insurance: why portfolio-specific fairness fails to extend market-wide"
  by Olivier Côté, Marie-Pier Côté and Arthur Charpentier
  Abstract - Paper - December 2024
   
• "Insurance analytics: prediction, explainability and fairness"
  Arthur Charpentier wrote, with Kjersti Aas (Norwegian Computing Center & Norwegian University of Science and Technology), Fei Huang (University of New South Wales) and Ronald Richman (Old Mutual Insure and University of the Witwatersrand) the editorial of the new volume of Annals of Actuarial Science.
  Paper - December 2024
   
• "Post-Calibration Techniques: Balancing Calibration and Score Distribution Alignment"
  Agathe Fernandes Machada presented recent work at a workshop at the Thirty-Eighth Annual Conference on Neural Information Processing Systems (also known as NeurIPS 2024),
  Poster - December 2024 / Paper - December 2024
   
• "Demystify fairness and discrimination in insurance, and avoid some pitfalls"
  Arthur Charpentier was invited to give a talk at the Financial Conduct Authority (FCA)
  Presentation - Seminar, London, UK - November 2024
   

• "Optimal transport and fairness of predictive models"
  Keynote presentation - Workshop - SCAI (Sorbonne Center for Artificial Intelligence) - September 2024

• SCOR-UQAM Fairness and Insurance Project Newsletter
  Newsletter #2 - September 2024

• "Certitudes collective et incertitudes individuelles, les données massives changent-elles la donne ?" [French]
  Abstract - Colloque au Centre Culturel International de Cerisy - Cerisy-la-Salle, France - September 2024

• "From contemplative to predictive modeling in actuarial science and risk management"
  ACP Conference - KU Leuven - July 2024

• "Collaborative insurance, unfairness, and discrimination"
  Workshop on decentralized insurance and risk sharing - Chicago - July 2024

• "Scope and limits of artificial intelligence"
  SCOR Foundation Online Webinar - May 15, 2024

• SCOR-UQAM Fairness and Insurance Project Newsletter
  Newsletter #1 - March 2024

Project research results: reports & articles

• Annual Research Report
  | [EN] | 2024 | Authors: Arthur Charpentier (Principal investigator), Professeur UQAM |