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Risks 2016, 4(1), 3; doi:10.3390/risks4010003

Premiums for Long-Term Care Insurance Packages: Sensitivity with Respect to Biometric Assumptions

Department DEAMS “Bruno de Finetti”, University of Trieste, Piazzale Europa 1, Trieste 34127, Italy
Academic Editor: Nadine Gatzert
Received: 19 November 2015 / Accepted: 2 February 2016 / Published: 22 February 2016
(This article belongs to the Special Issue Life Insurance and Pensions)
View Full-Text   |   Download PDF [344 KB, uploaded 22 February 2016]   |  

Abstract

Long-term care insurance (LTCI) covers are rather recent products, in the framework of health insurance. It follows that specific biometric data are scanty; pricing and reserving problems then arise because of difficulties in the choice of appropriate technical bases. Different benefit structures imply different sensitivity degrees with respect to changes in biometric assumptions. Hence, an accurate sensitivity analysis can help in designing LTCI products and, in particular, in comparing stand-alone products to combined products, i.e., packages including LTCI benefits and other lifetime-related benefits. Numerical examples show, in particular, that the stand-alone cover is much riskier than all of the LTCI combined products that we have considered. As a consequence, the LTCI stand-alone cover is a highly “absorbing” product as regards capital requirements for solvency purposes. View Full-Text
Keywords: long-term care insurance; LTCI; biometric functions; multi-state models; Markov models; mortality laws; mortality of disabled people long-term care insurance; LTCI; biometric functions; multi-state models; Markov models; mortality laws; mortality of disabled people
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Pitacco, E. Premiums for Long-Term Care Insurance Packages: Sensitivity with Respect to Biometric Assumptions. Risks 2016, 4, 3.

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