Actuarial Modelling and Data Integrity

Describe the various purposes of models in actuarial work (e.g., pricing, reserving, capital modeling).

Identify the key features of a robust actuarial model, including the importance of documentation.

Justify the choice between deterministic and stochastic modeling for a given actuarial problem.

Describe the process of model validation, including back-testing and sensitivity testing.

Describe the key requirements for data quality (accuracy, completeness, appropriateness).

Explain the processes of data verification, cleaning, and adjustment.

Explain how to effectively communicate model results, including key limitations and uncertainty.