Research

Published papers

  1. Blier-Wong, C., Cossette, H., Marceau, E. (2025). Efficient evaluation of risk allocations. Insurance: Mathematics and Economics. https://doi.org/10.1016/j.insmatheco.2025.02.006
  2. Blier-Wong, C., Cossette, H., & Marceau, E. (2024). Collective risk models with FGM dependence. Scandinavian Actuarial Journal. https://doi.org/10.1080/03461238.2024.2401390
  3. Blier-Wong, C., Lamontagne, L. & Marceau, E. (2024). A representation-learning approach for insurance pricing with images. ASTIN Bulletin. https://doi.org/10.1017/asb.2024.9
  4. Blier-Wong, C., Cossette, H., & Marceau, E. (2024). Exchangeable FGM copulas. Advances in Applied Probability.  https://doi.org/10.1017/apr.2023.19
  5. Blier-Wong, C., Cossette, H., Legros, S. & Marceau, E. (2023). A new method to construct high-dimensional copulas with Bernoulli and Coxian-2 distributions. Journal of Multivariate Analysis. https://doi.org/10.1016/j.jmva.2023.105261
  6. Blier-Wong, C., Cossette, H., & Marceau, E. (2023). Risk aggregation with FGM copulas. Insurance: Mathematics and Economics. https://doi.org/10.1016/j.insmatheco.2023.03.002
  7. Blier-Wong, C., Cossette, H., & Marceau, E. (2022). Stochastic representation of FGM copulas using multivariate Bernoulli random variables. Computational Statistics & Data Analysis, 107506. https://doi.org/10.1016/j.csda.2022.107506
  8. Blier-Wong, C., Cossette, H., Lamontagne, L. & Marceau, E. (2021). Geographic ratemaking with spatial embeddings. ASTIN Bulletin. https://doi.org/10.1017/asb.2021.25
  9. Blier-Wong, C., Cossette, H., Lamontagne, L. & Marceau, E. (2021). Machine learning in P&C insurance: A review for pricing and reserving. Risks. https://doi.org/10.3390/risks9010004
  10. Blier-Wong, C., Baillargeon, J. T., Cossette, H., Lamontagne, L., & Marceau, E. (2020). Encoding neighbor information into geographical embeddings using convolutional neural networks. In The Thirty-Third International Flairs Conference.

Submitted manuscripts

  1. Improved thresholds for e-values (submitted) with Ruodu Wang. https://arxiv.org/abs/2408.11307
  2. A multi-view contrastive learning framework for spatial embeddings in risk modelling (submitted) with Freek Holvoet and Katrien Antonio. https://arxiv.org/abs/2511.17954

Preprints and technical papers

  1. Blier-Wong, C., Baillargeon, J. T., Cossette, H., Lamontagne, L., & Marceau, E. (2021). Rethinking Representations in P&C Actuarial Science with Deep Neural Networks. https://arxiv.org/abs/2102.05784