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Updating Bonus Malus indexing mechanism to adjust long-term health insurance premiums

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1001 ‎$0‎MAPA20230008720‎$a‎Kanani Dizaji, Atefeh
24510‎$a‎Updating Bonus Malus indexing mechanism to adjust long-term health insurance premiums‎$c‎Atefeh Kanani Dizaji, Amir T. Payandeh Najafabadi
520  ‎$a‎Economic shocks, high inflation, longevity, and new emerging technologies make the long-term health care insurance challenging for insurers. To overcome this problem, an indexing mechanism has been employed to update predicted premiums based on the new information in hand. Such indexing mechanisms have thus far failed to consider the available policyholder's risk experience at its updating time. This article employs the well-known bonusmalus system to introduce a bonusmalus indexing mechanism that takes into account the policyholder's risk experience in its updating mechanism. More precisely, it uses the bonusmalus system's idea to update the premium of each policyholder based upon her or his risk experience as well as updated inflation. The theoretical foundation of this approach has been developed and its practical implementation is shown through a simulation study
650 4‎$0‎MAPA20080590567‎$a‎Empresas de seguros
650 4‎$0‎MAPA20080594794‎$a‎Asistencia sanitaria
650 4‎$0‎MAPA20080602871‎$a‎Percepción del riesgo
650 4‎$0‎MAPA20080581886‎$a‎Primas de seguros
650 4‎$0‎MAPA20210010392‎$a‎Simulación
650 4‎$0‎MAPA20080591960‎$a‎Métodos de análisis
7001 ‎$0‎MAPA20230008737‎$a‎Payandeh Najafabadi, Amir T.
7730 ‎$w‎MAP20077000239‎$g‎06/09/2023 Tomo 27 Número 3 - 2023 , 15 p.‎$x‎1092-0277‎$t‎North American actuarial journal‎$d‎Schaumburg : Society of Actuaries, 1997-
85600‎$y‎MÁS INFORMACIÓN‎$u‎ mailto:centrodocumentacion@fundacionmapfre.org?subject=Consulta%20de%20una%20publicaci%C3%B3n%20&body=Necesito%20m%C3%A1s%20informaci%C3%B3n%20sobre%20este%20documento%3A%20%0A%0A%5Banote%20aqu%C3%AD%20el%20titulo%20completo%20del%20documento%20del%20que%20desea%20informaci%C3%B3n%20y%20nos%20pondremos%20en%20contacto%20con%20usted%5D%20%0A%0AGracias%20%0A