Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/168065
Title: Incorporating fuzzy information in pricing substandard annuities
Author: Andrés Sánchez, Jorge de
González-Vila Puchades, Laura
Zhang, Aihua
Keywords: Conjunts borrosos
Lògica borrosa
Assegurances
Fuzzy sets
Fuzzy logic
Insurance
Issue Date: Jul-2020
Publisher: Elsevier
Abstract: There is a growing interest in the insurance industry in offering substandard annuities. These annuities, based on medical underwriting, provide a greater pay out than the standard ones to those individuals who are expected to have a lower than average life expectancy. Medically underwritten annuities often involve imprecise or vague information about the individuals such as health status and lifestyle. To address this issue, this paper proposes two approaches based on Fuzzy Sets Theory tools. Firstly, in order to determine substandard annuity payments, fuzzy mortality factors (also known as mortality multipliers) are introduced. These fuzzy mortality factors, modelled by means of triangular fuzzy numbers, can be estimated using conventional statistical confidence intervals. Secondly, by designing a fuzzy inference system, we demonstrate how to obtain the substandard annuity payment based on imprecise or vague personal information about annuitants. Numerical applications based on Spanish mortality data are provided for illustration. Previous article in issue
Note: Versió postprint del document publicat a: https://doi.org/10.1016/j.cie.2020.106475
It is part of: Computers and Industrial Engineering, 2020, vol. 145, num. 106475
URI: http://hdl.handle.net/2445/168065
Related resource: https://doi.org/10.1016/j.cie.2020.106475
ISSN: 0360-8352
Appears in Collections:Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)

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