This course provides an introduction to actuarial practices in non-life insurance. It encompasses a general overview of the industry, including the history of general insurance and risk-sharing arrangements. Topics covered include loss distributions for modelling individual and aggregate losses, statistical inference, moment generating functions for various distributions (gamma, exponential, Pareto, generalized Pareto, normal, log-normal, Weibull, etc.), and the collective model for risk involving frequency and severity distributions.

The course delves into moments and moment generating functions of compound distributions, stochastic risk models such as compound Poisson processes, and reinsurance treaties (proportional, excess of loss, stop-loss). It covers the derivation of distributions, moment generating functions, and other properties of losses for both the insurer and reinsurer across all the aforementioned models. Additionally, the course explores ruin theory, Lundberg theorem, and an integral approach to ruin probability.

Fundamental concepts of Bayesian statistics are introduced, covering prior distributions, posterior distributions, loss functions, Bayesian estimators, credibility theory, Bayesian models, experience rating models and applications, claims reserving (run-off triangles), and programming applications using R.