Abstract

In this thesis, a stochastic approach to insurance risk modeling and measurement that is compliant with the new International Financial Reporting Standards (IFRS 17) is proposed. The compliance is achieved through the use of a semiparametric hierarchical copula which accounts for the dependence between the lines of business of the Canadian auto insurance industry. A model for the marginal unpaid claim liabilities of each line of business based on double generalized linear models is also developed. Development year and accident year effect factors along with an autoregressive feature for residuals enable modeling the dependence between the various entries of the loss triangles in a given line of business. Capital requirements calculations are then performed through simulation; numbers obtained with univariate and multivariate risk measures are compared. Moreover, a risk adjustment for non-financial risk required by IFRS 17 is also computed through a cost of capital approach.