Artificial Intelligence in Insurance and Actuarial Studies

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