Extremal Application of Underwriting Instruments in South African Medical Schemes, 2015–2024: A Peaks-Over-Threshold Analysis with Policy Implications
DOI:
https://doi.org/10.31290/ijhimr.v3i2.6672Keywords:
Extreme value theory, generalised Pareto distribution, medical schemes, South Africa, underwritingAbstract
Medical schemes in South Africa may apply three statutory underwriting instruments—general waiting periods, pre-existing-condition exclusions, and late-joiner penalties—to protect risk pools against anti-selection. However, their application varies, and extreme cases affecting large numbers of beneficiaries have not been formally modelled. This study applies extreme value theory (EVT) to underwriting cases across benefit options in South African medical schemes from 2015 to 2024, using national regulatory data, and interprets the findings in the context of policy debates on anti-selection and risk equalisation. The distribution of cases per option-year exhibited a heavy tail. A generalised Pareto distribution fitted to high-threshold exceedances yielded a positive shape parameter (ξ ≈ 0.18 using maximum likelihood and ≈ 0.85 using the Hill estimator), placing the data in the Fréchet domain, with a tail index of approximately 1.2–3. Concentration was substantial: the most affected 10% of benefit options accounted for approximately three-quarters of all cases, while estimated return levels reached tens of thousands of cases for rare option-years. Trends varied by instrument: pre-existing-condition exclusions declined, general waiting periods peaked in 2024, and late-joiner penalties remained relatively stable but were concentrated in open schemes and older age groups. Extreme case counts were consistently higher in open schemes. These findings support policy discussions on risk equalisation and reducing reliance on underwriting. EVT offers regulators a systematic approach to identifying extreme underwriting case loads, although the results must be interpreted cautiously because counts depend on benefit-option size and do not measure application rates.
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