Artificial Intelligence in Insurance & 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

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.