Titlebook: Insurance, Biases, Discrimination and Fairness; Arthur Charpentier Book 2024 The Editor(s) (if applicable) and The Author(s), under exclus

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Models: Overview on Predictive Modelsf classes, and then to modern insurance, with the concept of “premium personalization.” Modern modeling techniques are presented, starting with econometric approaches, before presenting machine-learning techniques.

Peristalsis

Observations or Experiments: Data in Insuranceand causality, we describe the “causation ladder,” and the three rungs: association or correlation (“.”), intervention (“.”), and counterfactuals (“.”). Counterfactuals are important for quantifying discrimination.

Lymphocyte

Encephalitis

In-processinghe model is required to satisfy constraints, a natural idea is to add a penalty term in the objective function. The idea of “in-processing” is to get a trade-off between accuracy and fairness. As previously, we present that approach to some datasets.

Modicum

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978-3-031-49785-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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