Resources
This page provides links to relevant resoures.
We recommend to refer to the Upskilling Guide that the working group has devel-oped. It gives an overview of topics and areas that fully qualified actuaries can explore to ex-pand their data science knowledge and skills.
This page is organized by the following categories:
• Foundations of Data Science
• Actuarial Data Science
• Education Programs
Foundations of Data Science
The material below is primarily learning material on basic knowledge in Data Science. It does not discuss actuarial topics.
Below we list several books which we think are well suited for actuaries. We intentionally restrict to a few books, even though there are a lot more available.
Books
Mathematics / Statistics:
- Data Science and Machine Learning, D.P. Kroese, Z.I. Botev, T. Taimre, R. Vaisman, Chapman and Hall/CRC, 2019
- The Elements of Statistical Learning, T. Hastie, R Tibshirani, J. Friedman, Springer, 2009
- An Introduction to Statistical Learning, G. James, D. Witten, T. Hastie, R. Tibshirani, Springer, 2021
- Computer Age Statistical Inference, B. Efron and T. Hastie, Cambridge, 2016
Data Science with R:
- R for Data Science, G. Grolemund, H. Wickham, O’Reilly Media, 2017
- Machine Learning with R, B. Lantz, Packt, 2015
- Interpretable Machine Learning, C. Molnar, Leanpub, 2020
Data Science with Python:
- Data Science from Scratch, J. Grus, O’Reilly Media, 2015
- Python Data Science Workbook, J. VanderPlas, O'Reilly Media, 2017
Neural Networks and Deep Learning:
- Deep Learning, I. Goodfellow, Y. Bengio, A. Courville, MIT Press, 2017
- Neural Networks and Deep Learning, Nielsen, M., 2017
Lecture Material
- Computational Statistics, ETH Zurich, P. Bühlmann, M. Mächler, 2016
- Machine Learning, EPF Lausanne, M. Jaggi, U. Rüder, 2018
- Introduction to Machine Learning, M. Mayer, 2021
Key Articles
- Prediction, Estimation, and Attribution, B. Efron, Journal of the American Statistical Association 115:539 , 636-655, 2020
- To explain or to Predict?, G. Shmueli, Statistical Science 25/3, 289-310, 2010
- Statistical Modeling: The Two Cultures. L. Breimann, Statistical Science 16/3, 199-215, 2001
Actuarial Data Science
Actuarial Data Science is the application of the general concepts of Data Science to topics related to actuarial ques-tions, such as, for example, reserv-ing, pricing or risk modeling.
Books
- Statistical Foundations of Actuarial Learning and its Applications, M.V. Wüthrich and M. Merz, 2023, Springer Actuarial
- Actuarial Data Science, M. Seehafer et. al., De Gruyter, 2021 (in German)
- Computational Actuarial Science with R, CRC Press, A. Charpentier. (traditional actuarial science, but with a “Data Science touch”.
- AI Tools for Actuaries, Mario V. Wuthrich, Ronald Richman, Benjamin Avanzi, Mathias Lindholm, Michael Mayer, Jürg Schelldorfer, Salvatore Scognamiglio, SSRN 2025
Lecture Material
- Data Analytics for Non-Life Insurance Pricing, ETH Zurich, M. V. Wüthrich und C. M. Buser, Spring 2024
- Experience Rating in Insurance Pricing, M.V. Wüthrich (draft lecture notes)
Courses / Tutorials
- Responsible Machine Learning with Insurance Applications, ETH Zurich, M. Mayer, C. Lorentzen, Fall 2024
- Machine Learning for Actuaries in Python, Swiss Assocation of Actuaries, M. Mayer, online
- Machine Learning with R for Actuaries, Swiss Association of Actuaries, M. Mayer, 2022, online
- Deep Learning with Actuarial Application in R, Swiss Association of Actuaries, D. Meier, J. Schelldorfer and M.V. Wüthrich, 2020 & 2021, Zurich
- Insurance Data Science: Use and Value of Unusual Data, University of Lausanne and Swiss Association of Actuaries, J.-P. Boucher, A. Charpentier and Ewen Gallic, 12th - 16th August 2019. The slides and the code are publicly available here.
- Insurance Analytics, A Primer, University of Lausanne and Swiss Association of Actuaries, M. Denuit and J. Trufin, 13th-17th August 2018. (The course slides are not publicly available, please contact the lecturers for providing the slides. The exercises are publicly availabe on GitHub).
Education Programs
The following Universities offer courses in Actu-arial Data Science on Bache-lor/Master Level:
We also recommend the Summer School Lausanne.
For fully qualified actuaries who aim to enhance their (actuarial) data science skills with a non-SAA course, the subsequent recurring block courses may be consid-ered:
- CAS in Machine Learning in Finance and Insurance offered by ETH Zurich
- CAS or MAS Data Science offered by ZHAW (Zurich University of Applied Sci-ences): As a member of the SAA you can benefit from a 5% discount on the course fees of this course. Please mention the following in the commentary field of the regis-tration form: "I am a member of the SAA and hence I get a dis-count of 5%"
- Actuarial Data Science Training Modules offered by DAV( German Association of Actuaries)
- Neural Networks and Random Forest in Insurance Risk Modeling (Video), 26th June 2020, SDS2020, Online
- Erkenntnisse zu Neuronalen Netzen in der Nichtleben-Tarifierung, 2nd De-cember 2019, Daten, Zahlen, Algorithmen - Data Science in der Schadenversi-cherung im Fokus, Cologne
- Recent Achievements and Perspectives in Actuarial Data Science, 13th Sep-tember 2019, ETH Risk Day 2019, Zurich