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Modelling Life Insurance Premiums Under Alternative Expense Assumptions

Abstract

The study examines the modelling of life insurance premiums under alternative expense assumptions. Expense assumptions are important components of life insurance pricing because insurers incur various costs in acquiring, administering, maintaining, and servicing insurance policies. These expenses can influence the amount of premium required to cover expected benefits and operational obligations. Accurate modelling of expenses is therefore essential for determining adequate and sustainable life insurance premiums. The study will develop a model for estimating life insurance premiums under different expense assumptions. It will examine how variations in acquisition expenses, administrative expenses, renewal expenses, claims-related expenses, and other applicable policy expenses affect the calculated premium. The study will compare premium values obtained under alternative expense scenarios to determine the extent to which changes in expense assumptions influence life insurance pricing. The modelling process will incorporate mortality probabilities, survival probabilities, benefit amounts, policy duration, premium payment patterns, interest rate assumptions, and expense levels. Actuarial present value techniques will be used to determine the expected value of future benefits and expenses, while alternative expense assumptions will be introduced into the premium calculations. The model will also consider differences between fixed expenses, recurring expenses, and expenses expressed as proportions of premiums or benefits. A quantitative research approach will be adopted for the study. Hypothetical or secondary life insurance data will be used to construct representative policy scenarios under different expense assumptions. Actuarial valuation techniques, life tables, probability calculations, discounting methods, and mathematical modelling will be applied to estimate premiums under the selected scenarios. Comparative and sensitivity analyses will then be conducted to assess the effect of changes in expense assumptions on the resulting premium values. The study is expected to reveal that variations in expense assumptions can produce noticeable differences in life insurance premium estimates. Higher acquisition, administrative, or recurring policy expenses are expected to increase the premium required to support the insurance contract, while lower expense assumptions may result in comparatively lower premium estimates. The magnitude of the effect is expected to depend on the type, timing, frequency, and duration of the expenses incorporated into the actuarial model. The study will provide useful information for actuaries, life insurance companies, regulators, and researchers by demonstrating the importance of expense assumptions in life insurance premium modelling. The findings may assist insurers in developing more accurate pricing models, evaluating premium adequacy, managing policy expenses, and assessing the financial implications of alternative expense structures. The study may also support improved understanding of the relationship between operating expenses and actuarial premium determination. The study concludes that expense assumptions are important determinants of life insurance premium values because changes in the level and timing of expenses can alter the actuarial cost of maintaining insurance contracts. It is therefore recommended that insurers use realistic and regularly reviewed expense assumptions when modelling life insurance premiums. Appropriate actuarial techniques and sensitivity analysis should also be applied to ensure that premium estimates adequately reflect expected expenses and future insurance obligations.

Keywords: Life insurance premiums, expense assumptions, actuarial modelling, premium valuation, actuarial pricing, policy expenses, acquisition expenses, administrative expenses, renewal expenses, claims expenses, mortality probabilities, actuarial present value, premium adequacy, life insurance valuation, actuarial calculations.