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Mathematical models and numerical methods for Actuarial Sciences


  1. Introduction and vocabulary for Actuarial risk management.
  2. Definition and analysis of the Cramér-Lundberg model: compound Poisson processes, ruin, premium and risk reserve.
  3. Some stochastic and machine learning algorithm applied to actuarial data.
  4. Introduction to risk measures.


At the end of this module, the student should be able to :


  • Understand the main notions and issues of risk modeling in Actuarial sciences.


  • Know the definition and the notions of ruins, pricing and risk reserving in the framework of the Cramér-Lundberg model.



  • Know the main machine learning algorithms for risk management in the context of life and non-life insurance contracts data.


  • Know the main notions of risk measures in light of risk management issues. 

Needed prerequisite

-       Probability and Statistics (I2MIMT31)

-       Poisson processes and application to reliability theory and actuarial sciences (I5MAOPPDP11)

Form of assessment

The evaluation of outcome prior learning is made as a continuous training during the semester. According ot the teaching, the assessment will be different: as a written exam, an oral exam, a record, a written report, peers review...