Artificial Intelligence in Insurance & Actuarial Studies
Teacher
ECTS:
3
Course Hours:
12
Tutorials Hours:
6
Language:
English
Objective
To understand the main issues (methodological, commercial, regulatory) related to the use of data science in actuarial science.
Planning
I - The contexts of application of data-science in actuarial science
- Underwriting and pricing
- Reserving and risk management
- Associated risks
II - Statistical Learning Concepts
- Aggregation
- Bootstrap
- Classical statistical learning methods
III - Example of insurance applications
References
nHastie, T., Tibshirani, R., Friedman, J. (2001) The Elements of Statistical Learning, Springer.
Chancel, Antoine and Bradier, Laura and Ly, Antoine and Ionescu, Razvan and Martin, Laurene and Sauce, Marguerite, (2022) Applying Machine Learning to Life Insurance: some knowledge sharing to master it
Dimitri Delcaillau, Antoine Ly, Alize Papp, Franck Vermet, (2022) Applying Machine Learning to Life Insurance: some knowledge sharing to master it