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
Hastie, T., Tibshirani, R., Friedman, J. (2001) The Elements of Statistical Learning, Springer.
James G., Witten, D., Hastie T. Tibshirani, R. (2013) An Introduction to Statistical Learning with Applications in R.