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A Risk Based approach for the Solvency Capital requirement for Health Plans

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  • Fabio Baione
  • Davide Biancalana
  • Paolo De Angelis

Abstract

The study deals with the assessment of risk measures for Health Plans in order to assess the Solvency Capital Requirement. For the estimation of the individual health care expenditure for several episode types, we suggest an original approach based on a three-part regression model. We propose three Generalized Linear Models (GLM) to assess claim counts, the allocation of each claim to a specific episode and the severity average expenditures respectively. One of the main practical advantages of our proposal is the reduction of the regression models compared to a traditional approach, where several two-part models for each episode types are requested. As most health plans require co-payments or co-insurance, considering at this stage the non-linearity condition of the reimbursement function, we adopt a Montecarlo simulation to assess the health plan costs. The simulation approach provides the probability distribution of the Net Asset Value of the Health Plan and the estimate of several risk measures.

Suggested Citation

  • Fabio Baione & Davide Biancalana & Paolo De Angelis, 2020. "A Risk Based approach for the Solvency Capital requirement for Health Plans," Papers 2011.09254, arXiv.org.
    • Handle: RePEc:arx:papers:2011.09254
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    References listed on IDEAS

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    1. I. Duncan & M. Loginov & M. Ludkovski, 2016. "Testing Alternative Regression Frameworks for Predictive Modeling of Health Care Costs," North American Actuarial Journal, Taylor & Francis Journals, vol. 20(1), pages 65-87, January.
    2. Edward Frees & Jie Gao & Marjorie Rosenberg, 2011. "Predicting the Frequency and Amount of Health Care Expenditures," North American Actuarial Journal, Taylor & Francis Journals, vol. 15(3), pages 377-392.
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