Document Type : Research Article
Authors
1 Insurance research center, Tehran, Iran
2 MSc, Department of Economic, Faculty of Social and Economics, Alzahra University, Tehran, Iran.
Abstract
The aim of this study is to examine the impact of different adjustment multipliers (β) on mortality tables and their effect on premium calculation in the life insurance industry. In this research, standard mortality tables are compared with mortality tables adjusted by modification multipliers to explore the differences in insurance risks for individuals with varying health statuses. The results show that as the value of the adjustment multiplier (β) increases, the mortality rate significantly rises. These changes directly impact the calculation of premiums, with premiums being higher for individuals with more health problems. Furthermore, the study emphasizes the importance of using specific mortality tables at younger ages, as health status changes during these periods can significantly affect risk assessment and premium determination. The use of these tables allows insurers to calculate fairer premiums aligned with the actual health status of policyholders, thereby improving both the accuracy of insurance risk assessments and their financial solvency, as well as strengthening their competitive position in the insurance market.
Keywords
of Insurance Research, 11(1) (2021), pp. 15-30. (In Persian)
[2] M. Aalaei Using fuzzy interest rates for uncertainty modelling in enhanced annuities pricing,
International Journal of Mathematical Modelling & Computations, 12(4) (2022), pp. 265-274.
[3] M. Aalaei Pricing life settlements in the secondary market using fuzzy internal rate of
return, Journal of Mathematics and Modeling in Finance, 2(2) (2022), pp. 53-62.
[4] M. Aalaei The impact of using Iranian life table on standard and modified premium of
various life insurance products, Journal of Population Association of Iran, 17(33) (2022), pp.
159-177. (In Persian)
[5] M. Aalaei Introducing enhanced annuity product and calculating its payouts for the insureds
with different cancers using adjustment approaches of possible mortality, Iranian Journal of
Insurance Research, 12(2) (2023, pp. 143-154. (In Persian)
[6] M. Aalaei and F. Atatalab The impact of using Iran life table on the present value of
future loss of life insurance portfolio, Journal of Population Association of Iran, 19(37) (2024),
217-248. (In Persian)
[7] M. Aalaei and K. Ebrahimnezhad Life settlements pricing based on fuzzy interest rates
arisen from life insurance premiums, Journal of Mathematics and Modeling in Finance, 3(2)
(2023), pp. 177-189.
[8] M. Aalaei, E. Safarzadeh and K. Ebrahimnezhad Life settlements pricing in Iran's secondary market using deterministic, probabilistic, and stochastic approaches, Financial Research Journal, 25(2) (2023), pp. 255-274. (In Persian)
[9] M. Aalaei, E. Safarzadeh and K. Ebrahimnezhad Pricing life settlements in the secondary market for the insured with cancer based on the amount of healthy lifestyle score,
Journal of Investment Knowledge, In Press. (In Persian)
[10] R. L. Brown and J. McDaid Factors affecting retirement mortality, North American Actuarial Journal, 7(2) (2003), pp. 24-43.
[11] M. Danan and Z. Basukordshami Life insurances: Basics, calculations and processes.
Pooshesh Gostar Press, 2015. (In Persian)
[12] D. C. M. Dickson, M. R. Hardy and H. R. Waters Actuarial mathematics for life contingent risks, Cambridge university press, Third edition, 2019.
[13] V. F. Dolan, Advantages of a Life Expectancy Using Life Insurance Underwriting and Life
Settlement Methods in the Legal Setting, Las Vegas: VFD Consulting, Inc. 2013.
[14] H. Hosseini, M. M. Torkashvand and S. A. Azizi Age patterns of mortality in the provinces
of Iran and their adaptation to standard model life tables, 6(2) (2020), pp. 263-291.
[15] J. G. Kilgour The New Mortality Tables, Life Expectancy and Pension Plans, Compensation and Benefits Review, 48(5-6) (2016), pp. 128-140.
[16] M. Kousheshi, M. T. Moradabadi and S. Mohammad, Investigating the adaptation of
age pattern of mortality in Iran with model life tables. Population Studies Quarterly,
3(1) (2017), pp. 39-63.
[17] H. S. Kwon and B. L. Jones The impact of the determinants of mortality on life insurance
and annuities, Insurance: Mathematics and Economics, 38(2) (2006), pp. 271-288.
[18] M. Qi The impact of mortality risk on the asset and liability management of insurance
companies, Asia-Pacific Journal of Risk and Insurance, 7(2) (2013), pp. 81-104.
[19] J.A. Sanchez and L.G. Puchades, Life settlements: descriptive analysis and quantitative
aspects, Management Letters, 21(2) (2021), pp. 19-34. (In Spain)
[20] M. Santos, V. Richman and J. Urbanski Annual changes in mortality rates and related
effects on life insurance company financials. John. Journal of Applied Financial Research; Gulfport, 1 (2017), pp. 61-73.
[21] G. O. Siswono, U. Azmi and W. H. Syaifudin Mortality projection on Indonesia’s abridged
life table to determine the EPV of term annuity, Jurnal Varian, 4(2) (2021), pp. 159-168.
[22] Society of Actuaries 2015 valuation basic table report: Joint Academy of Actuaries Life
Experience Committee and Society of Actuaries Preferred Mortality Oversight Group Valuation Basic Table Team, Society of Actuaries, 2018.
[23] A. Souri, G. H. Mahdavi, M. Kousheshi, M. Sasani and M. Torkashvand Compilation
of the life tables of men and women in the year 2013, divided into urban and rural areas
and its use in calculating insurance premiums for various types of life insurance contracts.
Insurance Research Center, Customized Research Projects of Central Insurance.
I.R. Iran, 2015.
[24] J. Xu Dating death: An empirical comparison of medical underwriters in the US life settlements market, North American Actuarial Journal, 24(1) (2020), pp. 36-56.
[25] B. Y. Kulekci and A. S. S. Kestel Assessment of longevity risk: credibility approach
Journal of Applied Statistics, 48(13-15) (2021), pp. 2695-2713.
)