Research interests: Actuarial Science and Data Analytics applied to Insurance Problems.

Selected Manuscripts (non peer-reviewed)

• Calibration bands for mean estimates within the exponential dispersion family
  (with S. Gatti and L. Delong). arXiv:2503.18896, 2025.




• An observation-driven state-space model for claims size modeling
  (with J.Y. Ahn and H. Jeong). SSRN Manuscript, ID 5075185, 2025.




• Claims processing and costs under capacity constraints
  (with F. Lindskog). arXiv:2409.09091, 2024.




• The balance property in insurance pricing
  (with M. Lindholm). SSRN Manuscript, ID 4925165, 2024.




• Sensitivity-based measures of discrimination in insurance pricing
  (with M. Lindholm, R. Richman, A. Tsanakas). SSRN Manuscript, ID 4897265, 2024.




• Reflections on deep learning and the actuarial profession(al)
  (with R. Harris, R. Richman). SSRN Manuscript, ID 4672447, 2024.




• A classification of observation-driven state-space count models for panel data
  (with J.Y. Ahn, H. Jeong, Y. Lu). arXiv:2308.16058, 2023.




• Conditional expectation network for SHAP
  (with R. Richman). SSRN Manuscript, ID 4514891, 2023.




• Claims run-off uncertainty: the full picture
  (with M. Merz). SSRN Manuscript, ID 2524352, 2014.
  Code available through ChainLadder 0.2.0 on CRAN:
  http://cran.r-project.org/web/packages/ChainLadder/






• Modelling the claims development result for solvency purposes
  (with M. Merz). CAS E-Forum, Fall 2008, 542--568.

Selected Recent Publications

(full list of publications: ▸ see)

• The credibility transformer
  (with R. Richman, S. Scognamiglio). European Actuarial Journal , in press, 2025.


• Presentation Slides; Code on GitHub




• Model selection with Gini indices under auto-calibration
  European Actuarial Journal 13/1 (2023), 469--477.




• LocalGLMnet: interpretable deep learning for tabular data
  (with R. Richman). Scandinavian Actuarial Journal 2023/1 (2023), 71--95.




• Discrimination-free insurance pricing
  (with M. Lindholm, R. Richman, A. Tsanakas). ASTIN Bulletin 52/1 (2022), 55--89.




• Collective reserving using individual claims data
  (with L. Delong, M. Lindholm). Scandinavian Actuarial Journal 2022/1 (2022), 1--28.




• Boosting Poisson regression models with telematics car driving data
  (with G. Gao, H. Wang). Machine Learning 111/1 (2022), 243--272.




• Time-series forecasting of mortality rates using deep learning
  (with F. Perla, R. Richman, S. Scognamiglio). Scandinavian Actuarial Journal 2021/7 (2021), 572--598.




• On the lifetime and one-year views of reserve risk, with application to IFRS 17 and Solvency II risk margins
  (with P.D. England, R.J. Verrall). Insurance: Mathematics and Economics 85 (2019), 74--88.
  R Shiny app