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Incorporating fuzzy information in pricing substandard annuities

  • Datos identificativos

    Identificador: imarina:6390342
    Autores:
    de Andrés-Sánchez JGonzález-Vila Puchades LZhang A
    Resumen:
    © 2020 Elsevier Ltd 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.
  • Otros:

    Autor según el artículo: de Andrés-Sánchez J; González-Vila Puchades L; Zhang A
    Departamento: Gestió d'Empreses
    Autor/es de la URV: De Andrés Sànchez, Jorge
    Palabras clave: Underwriting Systems Substandard annuity payment Risk classification Regression Mortality Model Liability Insurance Heterogeneity Fuzzy number Fuzzy mortality factor (or multiplier) Fuzzy inference system Frailty Enhanced annuities Determinants
    Resumen: © 2020 Elsevier Ltd 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.
    Áreas temáticas: Matemática / probabilidade e estatística Interdisciplinar General engineering General computer science Engineering, industrial Engineering (miscellaneous) Engineering (all) Engenharias iv Engenharias iii Engenharias ii Engenharias i Economia Computer science, interdisciplinary applications Computer science (miscellaneous) Computer science (all) Ciências agrárias i Ciência da computação Administração pública e de empresas, ciências contábeis e turismo
    ISSN: 03608352
    Direcció de correo del autor: jorge.deandres@urv.cat
    Identificador del autor: 0000-0002-7715-779X
    Fecha de alta del registro: 2023-02-19
    Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
    Enlace a la fuente original: https://www.sciencedirect.com/science/article/abs/pii/S0360835220302096
    Referencia al articulo segun fuente origial: Computers & Industrial Engineering. 145 (UNSP 106475):
    Referencia de l'ítem segons les normes APA: de Andrés-Sánchez J; González-Vila Puchades L; Zhang A (2020). Incorporating fuzzy information in pricing substandard annuities. Computers & Industrial Engineering, 145(UNSP 106475), -. DOI: 10.1016/j.cie.2020.106475
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    DOI del artículo: 10.1016/j.cie.2020.106475
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2020
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Computer Science (Miscellaneous),Computer Science, Interdisciplinary Applications,Engineering (Miscellaneous),Engineering, Industrial
    Underwriting
    Systems
    Substandard annuity payment
    Risk classification
    Regression
    Mortality
    Model
    Liability
    Insurance
    Heterogeneity
    Fuzzy number
    Fuzzy mortality factor (or multiplier)
    Fuzzy inference system
    Frailty
    Enhanced annuities
    Determinants
    Matemática / probabilidade e estatística
    Interdisciplinar
    General engineering
    General computer science
    Engineering, industrial
    Engineering (miscellaneous)
    Engineering (all)
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Economia
    Computer science, interdisciplinary applications
    Computer science (miscellaneous)
    Computer science (all)
    Ciências agrárias i
    Ciência da computação
    Administração pública e de empresas, ciências contábeis e turismo
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