Bayesian hierarchical modelling of exposure to accident benefit claims

The project will assess the financial risks to DGAG (Desjardins Groupe d’assurances
generales) associated with payments of accident insurance claims. A large database is
available on the losses incurred due to different aspects of insurance claims (medical costs,
rehabilitation and attendant care, etc.), and this project will assist DGAG in developing
exposure assessments for future accident benefit claims. By adopting a Bayesian statistical
approach, the uncertainties associated with various data sources and modelling assumptions
can be integrated into a single, coherent framework. The complexity and magnitude of the
database render Bayesian modelling a challenging task, so a major part of the project will
address efficient computational strategies. The intern will develop code in the free statistical
software R that will allow DGAG to develop and implement coherent financial management
strategies.

Faculty Supervisor:

Christian Genest

Student:

Partner:

Desjardins Assurances Générales

Discipline:

Mathematics

Sector:

Finance and Insurance

University:

McGill University

Program: