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Ratemaking and Claims Reserving

  • Teacher(s):  
  • Course given in: English
  • ECTS Credits:
  • Schedule: Spring Semester 2018-2019, 2.0h. course (weekly average)
  •  sessions
  • Related programme: Master of Science (MSc) in Actuarial Science

 

Objectives

  • To introduce students to actuarial methods used for non-life insurance pricing.
  • To introduce students to actuarial methods used for claim reserving in non-life insurance.
  • To apply these methods on examples of practical relevance.
  • To understand the advantages and drawbacks/limitations of each method as well as their complementarity.

Contents

  • Non-life insurance pricing with :
    • Generalized linear models (GLM)
    • Generalized additive models (GAM)
    • Machine learning techniques (regression trees, random forests, gradient boosting methods)
  • Methods used for claim reserving in non-life insurance:
    • Deterministic methods : chain ladder, Bornhuetter-Ferguson
    • Stochastic methods : Mack model and GLM models
    • Collective loss reserving approaches

References

  • Charpentier A., Computational Actuarial Science with R, 2014, CRC Press.
  • Denuit M. and Charpentier A., Mathématiques de l'assurance non-vie, Tome 1, 2004, Economica.
  • Denuit M. and Charpentier A., Mathématiques de l'assurance non-vie, Tome 2, 2005, Economica.
  • Denuit M and Trufin J., Beyond the Tweedie reserving model: the collective approach to loss development, 2017, North American Actuarial Journal 21(4), 611-619.
  • Denuit M. and Trufin J., Collective loss reserving with two types of claims in motor third party liability insurance, 2018, Journal of Computational and Applied Mathematics 335, 168-184.
  • Hastie T., Tibshirani R. and Friedman J., The elements of statistical learning, 2009, Springer, New York.
  • Kuhn M. and Johnson K., Applied Predictive Modeling, 2013, Springer, New York.
  • Ohlsson E. and Johansson B., Non-life pricing with Generalized Linear Models, 2010, Springer.
  • Wüthrich M.V. and Merz M., Stochastic claims reserving methods in insurance, 2008, Wiley.

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