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Effect of Fractional Age Mortality Assumptions on Life Insurance Premium Valuation

Abstract

Fractional age mortality assumptions are actuarial assumptions used to estimate mortality probabilities for ages that fall between whole-number ages in a life table. Since life insurance contracts may commence or provide benefits at ages that do not correspond exactly to whole-number ages, actuaries require appropriate methods for estimating mortality rates between observed ages. The choice of fractional age assumption can therefore influence the calculation of survival probabilities, expected benefits, and life insurance premiums. This study will examine the effect of fractional age mortality assumptions on life insurance premium valuation. It will assess how different methods of estimating mortality probabilities between integer ages influence actuarial premium values and determine the extent to which fractional age assumptions produce differences in premium requirements. The study will also compare premium valuations obtained under alternative fractional age mortality assumptions. The study will focus on fractional age mortality assumptions, life insurance premium valuation, mortality probabilities, survival probabilities, life tables, actuarial present values, premium calculation, mortality interpolation, policy entry age, and insurance benefits. Selected methods for estimating mortality at fractional ages will be applied to life insurance valuation models. The study will examine how differences in mortality assumptions affect expected claims, actuarial present values, and resulting premium estimates. A quantitative research approach will be adopted for the study. Historical mortality and life table data will be analysed using descriptive statistics, actuarial life table functions, mortality interpolation techniques, comparative analysis, actuarial present value calculations, and sensitivity analysis. Life insurance premiums will be calculated under alternative fractional age mortality assumptions and compared to determine the effect of each assumption on premium valuation results. The study is expected to reveal that fractional age mortality assumptions may have a significant effect on life insurance premium valuation, particularly for policies issued at ages between whole-number life table ages. Different interpolation or fractional age methods may produce variations in estimated mortality probabilities, resulting in differences in actuarial present values and premium requirements. The magnitude of the effect may depend on the mortality pattern, policy duration, age at entry, benefit structure, and mortality table used. The study will be useful to actuaries, life insurance companies, underwriters, pricing analysts, valuation professionals, regulators, and researchers. It may provide useful information for selecting appropriate fractional age mortality assumptions, improving premium calculations, strengthening actuarial valuation practices, and assessing the sensitivity of life insurance prices to mortality interpolation methods. The findings may also assist insurers in maintaining consistency between mortality assumptions and premium valuation procedures. The study concludes that fractional age mortality assumptions are important considerations in life insurance premium valuation because the treatment of mortality between whole-number ages can influence expected mortality probabilities and actuarial premium estimates. It is therefore recommended that insurers and actuaries carefully select appropriate fractional age assumptions, assess alternative mortality interpolation methods, and conduct sensitivity analysis to support accurate and consistent life insurance premium valuation.

Keywords: Fractional age mortality assumptions, life insurance premium valuation, mortality probabilities, survival probabilities, life tables, actuarial present value, mortality interpolation, premium calculation, policy entry age, insurance benefits, mortality assumptions, actuarial valuation, life insurance pricing, mortality rates, actuarial analysis.