Generates synthetic South African health insurance data with a known data-generating process, for teaching and testing pricing models. One function simulates a cross-sectional portfolio of principal members with negative binomial claim counts and a lognormal-Pareto severity mixture. Another simulates a multi-year open-cohort panel with ageing, smoking cessation, wearable activity and sleep data joined by a Clayton copula, claims inflation, annual benefit limits, lapses and deaths. Every parameter can be changed, and the true expected frequency and severity are available for checking fitted models.