Christian Lorentzen
Hi, I’m Christian, a former theoretical particle physicist who transformed into a non-life actuary working at la Mobilière (die Mobiliar). I’m also a core developer of scikit-learn and a member of the data science working group of the Swiss Association of Actuaries (SAV).
Michael Mayer
Hi, I am Michael. Doing statistics and ML is my hobby and – as non-life actuary at la Mobilière (die Mobiliar) – fortunately also my job. I do some teaching, develop R packages and am a member of the data science working group of the Swiss Association of Actuaries (SAV).
For a shared interview article at la Mobilière in German, see https://www.mobiliar.ch/news/sie-wissen-wie-die-maschine-rechnet.
Selected Publications
- Lorentzen, Christian and Mayer, Michael and Wuthrich, Mario V. (2022). Gini Index and Friends. Available at SSRN: doi:10.2139/ssrn.4248143
- Mayer, Michael (2022). SHAP for additively modeled features in a boosted trees model. doi:10.48550/arXiv.2207.14490
- Fissler, Tobias, Lorentzen, Christian and Mayer, Michael (2022). Model Comparison and Calibration Assessment: User Guide for Consistent Scoring Functions in Machine Learning and Actuarial Practice. doi:10.48550/arXiv.2202.12780
- Mayer, Michael, Bourassa, Steven C., Hoesli, Martin and Scognamiglio, Donato (2022). Machine Learning Applications to Land and Structure Valuation. Journal of Risk and Financial Management. 2022; 15(5):193. https://doi.org/10.3390/jrfm15050193
- Lorentzen, Christian and Mayer, Michael (2020). Peeking into the Black Box: An Actuarial Case Study for Interpretable Machine Learning. Available at SSRN: doi:10.2139/ssrn.3595944