30 citations · 74 across the 20 of their papers we have counts for
23 papers
Optimal Transport for Actuarial Science
Arthur Charpentier
These lecture notes introduce optimal transport as a mathematical language for actuarial science. They treat losses, premiums, scores, reserves, capital scenarios, climate losses a…
From Risk Prediction to Risk Mechanisms: A Multi-Resolution Causal Representation for Road Safety and Motor Insurance
Arthur Charpentier
Operational risk models can estimate event frequencies precisely while leaving the underlying mechanisms weakly resolved. We study this resolution mismatch using motor insurance an…
Beyond Zipf's Law: Equifinality and Mechanistic Inference from Scaling Laws
Arthur Charpentier
Scaling laws summarize complex systems through low-dimensional regularities, but the same marginal law can arise from different stochastic dynamics. We examine this ambiguity for Z…
Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory
Samuel Stocksieker, Denys Pommeret, Arthur Charpentier
In supervised learning, it is quite frequent to be confronted with real imbalanced datasets. This situation leads to a learning difficulty for standard algorithms. Research and sol…
Fairness Explainability using Optimal Transport with Applications in Image Classification
Philipp Ratz, François Hu, Arthur Charpentier
Ensuring trust and accountability in Artificial Intelligence systems demands explainability of its outcomes. Despite significant progress in Explainable AI, human biases still tain…
Fairness in Multi-Task Learning via Wasserstein Barycenters
François Hu, Philipp Ratz, Arthur Charpentier
Algorithmic Fairness is an established field in machine learning that aims to reduce biases in data. Recent advances have proposed various methods to ensure fairness in a univariat…
Mitigating Discrimination in Insurance with Wasserstein Barycenters
Arthur Charpentier, François Hu, Philipp Ratz
The insurance industry is heavily reliant on predictions of risks based on characteristics of potential customers. Although the use of said models is common, researchers have long…
Optimal Vaccination Policy to Prevent Endemicity: A Stochastic Model
Félix Foutel-Rodier, Arthur Charpentier, Hélène Guérin
We examine here the effects of recurrent vaccination and waning immunity on the establishment of an endemic equilibrium in a population. An individual-based model that incorporates…
Data Augmentation for Imbalanced Regression
Samuel Stocksieker, Denys Pommeret, Arthur Charpentier
In this work, we consider the problem of imbalanced data in a regression framework when the imbalanced phenomenon concerns continuous or discrete covariates. Such a situation can l…
Optimal Transport for Counterfactual Estimation: A Method for Causal Inference
Arthur Charpentier, Emmanuel Flachaire, Ewen Gallic
Many problems ask a question that can be formulated as a causal question: "what would have happened if...?" For example, "would the person have had surgery if he or she had been Bl…
Quantifying fairness and discrimination in predictive models
Arthur Charpentier
The analysis of discrimination has long interested economists and lawyers. In recent years, the literature in computer science and machine learning has become interested in the sub…
Government Intervention in Catastrophe Insurance Markets: A Reinforcement Learning Approach
Menna Hassan, Nourhan Sakr, Arthur Charpentier
This paper designs a sequential repeated game of a micro-founded society with three types of agents: individuals, insurers, and a government. Nascent to economics literature, we us…
The Fairness of Machine Learning in Insurance: New Rags for an Old Man?
Laurence Barry, Arthur Charpentier
Since the beginning of their history, insurers have been known to use data to classify and price risks. As such, they were confronted early on with the problem of fairness and disc…
A Fair Pricing Model via Adversarial Learning
Vincent Grari, Arthur Charpentier, Marcin Detyniecki
At the core of insurance business lies classification between risky and non-risky insureds, actuarial fairness meaning that risky insureds should contribute more and pay a higher p…
Weighted asymmetric least squares regression with fixed-effects
Amadou Barry, Karim Oualkacha, Arthur Charpentier
The fixed-effects model estimates the regressor effects on the mean of the response, which is inadequate to summarize the variable relationships in the presence of heteroscedastici…
Predicting Drought and Subsidence Risks in France
Arthur Charpentier, Molly James, Hani Ali
The economic consequences of drought episodes are increasingly important, although they are often difficult to apprehend in part because of the complexity of the underlying mechani…
Collaborative Insurance Sustainability and Network Structure
Arthur Charpentier, Lariosse Kouakou, Matthias Löwe +2
The peer-to-peer (P2P) economy has been growing with the advent of the Internet, with well known brands such as Uber or Airbnb being examples thereof. In the insurance sector the a…
Autocalibration and Tweedie-dominance for Insurance Pricing with Machine Learning
Michel Denuit, Arthur Charpentier, Julien Trufin
Boosting techniques and neural networks are particularly effective machine learning methods for insurance pricing. Often in practice, there are nevertheless endless debates about t…
Modeling Joint Lives within Families
Olivier Cabrignac, Arthur Charpentier, Ewen Gallic
Family history is usually seen as a significant factor insurance companies look at when applying for a life insurance policy. Where it is used, family history of cardiovascular dis…
COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability
Arthur Charpentier, Romuald Elie, Mathieu Laurière +1
We consider here an extended SIR model, including several features of the recent COVID-19 outbreak: in particular the infected and recovered individuals can either be detected (+)…
Reinforcement Learning in Economics and Finance
Arthur Charpentier, Romuald Elie, Carl Remlinger
Reinforcement learning algorithms describe how an agent can learn an optimal action policy in a sequential decision process, through repeated experience. In a given environment, th…
Pareto models for risk management
Arthur Charpentier, Emmanuel Flachaire
The Pareto model is very popular in risk management, since simple analytical formulas can be derived for financial downside risk measures (Value-at-Risk, Expected Shortfall) or rei…
Optimal transport on large networks, a practitioner's guide
Arthur Charpentier, Alfred Galichon, Lucas Vernet
This article presents a set of tools for the modeling of a spatial allocation problem in a large geographic market and gives examples of applications. In our settings, the market i…