1Understand and apply methods for modeling severity and aggregate loss distributions, including creating new distributions and comparing tail behaviors.

2Analyze the impact of coverage modifications and inflation on loss modeling in insurance.

3Estimate parameters using the maximum likelihood method and assess the asymptotic normality of the maximum likelihood estimator for a function of parameters.

4Select models based on graphical and score-based approaches and perform goodness-of-fit tests.

5Evaluate credibility concepts, including limited fluctuation credibility, Bayesian credibility with conjugate priors, and Buhlmann and Buhlmann-Straub models.

6Apply techniques for estimating unpaid losses, incurred but not reported (IBNR) losses, and project losses using trend analysis, as well as calculate overall average rates, rate changes, and risk classification differential changes.