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Loss Models

  • Teacher(s):  
  • Course given in: English
  • ECTS Credits:
  • Schedule: Spring Semester 2018-2019, 4.0h. course (weekly average)
      WARNING :   this is an old version of the syllabus, old versions contain   OBSOLETE   data.
  •  sessions
  • site web du cours course website
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The principal objective of this course is to provide a solid actuarial understanding of building, selecting and developing statistical models relevant for insurance business and related actuarial applications. This course aims at establishing a useful bridge between statistical and probabilistic models of insurance contracts and the raw, typically incomplete, insurance portfolio data available to actuaries. Accompanying exercises in R will help towards a better understanding of both insurance data and statistical models used by actuaries.


  • Introduction to Models, Data & Insurance Contracts
  • Parametric Models
  • Non-parametric Models
  • Loss Data, Model Validation & Selection
  • Extreme Value Statistics
  • Generalised Linear Models


  • Loss Models. From Data to Decisions. Klugman, S.T., Panjer, H.H., and Willmot, G.E. 3rd Edition, Wiley, 2008.
  • Statistical Theory. Seleznjev, O. Manuscript available in moodle.
  • Generalized Linear Models for Insurance Data. Jong, P., Heller, G.Z. Cambridge University Press, Cambridge, 2008.
  • Nonlife Actuarial Models, Theory, Methods and Evaluation. Tse, Y. Cambridge University Press, Cambridge, 2009.
  • Regression Modeling with Actuarial and Financial Applications. Frees, E.W. Cambridge University Press, Cambridge, 2009.
  • Statistical Analysis of Extreme Values: From Insurance, Finance, Hydrology and Other Fields. Reiss, R-D., Thomas, M. 3rd Edition, Birkhäuser, Basel, 2007.
  • Modeling Extremal Events for Finance and Insurance. Embrechts, P., Klüpelberg, C., and Mikosch, T. Springer, 1997.
  • Laws of Small Numbers: Extremes and Rare Events. Falk M., Hüsler, J., and Reiss R.-D. DMV Seminar 23, 3rd Edition, Birkhàuser, Basel, 2010.
  • Non-Life Insurance Mathematics: An Introduction with Stochastic Processes. Mikosch, T. 2nd Edition, Springer, 2006.


Basic in statistics & probability


First attempt

Written 3h00 hours
Not allowed
Not allowed

Final Grade= Grade of Final Exam


Written 3h00 hours
Not allowed
Not allowed

Final Grade= Grade of Final Exam

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