| A Neural Network Extension of the Lee-Carter Model to Multiple Populations R Richman, MV Wuthrich Annals of Actuarial Science 15 (2), 346-366, 2018 | 132 | 2018 |
| Time-Series Forecasting of Mortality Rates using Deep Learning F Perla, R Richman, S Scognamiglio, M Wuthrich SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3595426, 2020 | 93 | 2020 |
| Neural network embedding of the over-dispersed Poisson reserving model A Gabrielli, R Richman, MV Wüthrich Scandinavian Actuarial Journal 2020 (1), 1-29, 2020 | 77 | 2020 |
| Nagging Predictors R Richman, M Wuthrich Risks 8 (3), 83, 2020 | 54 | 2020 |
| Discrimination-free insurance pricing M Lindholm, R Richman, A Tsanakas, MV Wüthrich ASTIN Bulletin: The Journal of the IAA 52 (1), 55-89, 2022 | 51 | 2022 |
| AI in actuarial science–a review of recent advances–part 1 R Richman Annals of Actuarial Science 15 (2), 207-229, 2021 | 51 | 2021 |
| AI in actuarial science R Richman Available at SSRN 3218082, 2018 | 49 | 2018 |
| AI in actuarial science–a review of recent advances–part 2 R Richman Annals of Actuarial Science, 1-29, 2020 | 34 | 2020 |
| Lee and Carter go Machine Learning: Recurrent Neural Networks R Richman, MV Wuthrich Available at SSRN 3441030, 2019 | 33 | 2019 |
| LocalGLMnet: interpretable deep learning for tabular data R Richman, MV Wüthrich Scandinavian Actuarial Journal 2023 (1), 71-95, 2023 | 29 | 2023 |
| Mind the Gap-Safely Incorporating Deep Learning Models into the Actuarial Toolkit R Richman Available at SSRN 3857693, 2021 | 19 | 2021 |
| Believing the Bot-Model Risk in the Era of Deep Learning R Richman, N von Rummell, MV Wuthrich Available at SSRN 3444833, 2019 | 17 | 2019 |
| Interpreting deep learning models with marginal attribution by conditioning on quantiles M Merz, R Richman, A Tsanakas, MV Wüthrich Data Mining and Knowledge Discovery, 1-36, 2022 | 13 | 2022 |
| A multi-task network approach for calculating discrimination-free insurance prices M Lindholm, R Richman, A Tsanakas, MV Wüthrich European Actuarial Journal, 1-41, 2023 | 12 | 2023 |
| The Actuary and IBNR Techniques: A Machine Learning Approach C Balona, R Richman Available at SSRN 3697256, 2020 | 12 | 2020 |
| Embeddings and Attention in Predictive Modeling K Kuo, R Richman arXiv preprint arXiv:2104.03545, 2021 | 10 | 2021 |
| What is Fair? Proxy Discrimination vs. Demographic Disparities in Insurance Pricing M Lindholm, R Richman, A Tsanakas, MV Wuthrich SSRN, 2023 | 7 | 2023 |
| A Discussion of Discrimination and Fairness in Insurance Pricing M Lindholm, R Richman, A Tsanakas, MV Wüthrich arXiv preprint arXiv:2209.00858, 2022 | 6 | 2022 |
| Using machine learning to model claims experience and reporting delays for pricing and reserving L Rossouw, R Richman Available at SSRN 3465424, 2019 | 6 | 2019 |
| Old age mortality in South Africa, 1985-2011 RD Richman University of Cape Town, 2017 | 6 | 2017 |
Andreas TsanakasProfessor of Risk Management, Bayes Business School, City, University of LondonVerified email at city.ac.uk
