Insurance, Biases, Discrimination and Fairness, 1st Edition by Arthur Charpentier | 2025/2026 Study Guide to Pass Exams and Avoid Resits

Unlock a comprehensive understanding of the ethical and statistical challenges in the modern insurance industry with this essential guide for the 2025/2026 academic year. This resource delves into the intricacies of statistical modeling, exploring the risks of bias, data errors, and the impact of asymmetric modeling power. Gain critical insights into discrimination and fairness, reframing them as issues of both social justice and economic efficiency. This expertly curated content is designed to...