no code implementations • 20 Jul 2023 • Ronald Richman, Mario V. Wüthrich
A very popular model-agnostic technique for explaining predictive models is the SHapley Additive exPlanation (SHAP).
no code implementations • 6 Jan 2023 • Mario V. Wüthrich, Johanna Ziegel
Insurance pricing systems should fulfill the auto-calibration property to ensure that there is no systematic cross-financing between different price cohorts.
no code implementations • 2 Sep 2022 • Mathias Lindholm, Ronald Richman, Andreas Tsanakas, Mario V. Wüthrich
This is particularly the case in insurance pricing where protected policyholder characteristics are not allowed to be used for insurance pricing.
no code implementations • 28 Jul 2022 • Mario V. Wüthrich
The Gini index does not give a strictly consistent scoring rule in general.
no code implementations • 6 Jul 2022 • Mathias Lindholm, Ronald Richman, Andreas Tsanakas, Mario V. Wüthrich
Here, we address this issue by using a multi-task neural network architecture for claim predictions, which can be trained using only partial information on protected characteristics, and it produces prices that are free from proxy discrimination.
no code implementations • 23 Jul 2021 • Ronald Richman, Mario V. Wüthrich
Deep learning models have gained great popularity in statistical modeling because they lead to very competitive regression models, often outperforming classical statistical models such as generalized linear models.
no code implementations • 26 May 2021 • Patrick Cheridito, John Ery, Mario V. Wüthrich
We introduce a neural network approach for assessing the risk of a portfolio of assets and liabilities over a given time period.