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Effect of Actuarial Model Sensitivity Analysis on Insurance Valuation Estimates

Abstract

Actuarial models are important tools used by insurance companies to estimate premiums, reserves, liabilities, benefits, and other financial values associated with insurance contracts. These models depend on assumptions and parameters such as mortality rates, interest rates, claim frequencies, claim severities, expenses, and policy durations. Changes in these assumptions can produce different valuation estimates, making sensitivity analysis an important technique for assessing the stability and reliability of actuarial valuation results. This study will examine the effect of actuarial model sensitivity analysis on insurance valuation estimates. It will assess how changes in selected actuarial assumptions and model parameters influence estimated insurance values. The study will also evaluate the extent to which sensitivity analysis can reveal the responsiveness of valuation estimates to changes in key assumptions used in insurance models. The study will focus on selected actuarial parameters, including mortality assumptions, interest rate assumptions, claim frequency, claim severity, expense assumptions, and policy duration. Sensitivity analysis will be applied by varying individual assumptions and observing corresponding changes in insurance valuation estimates. Measures such as actuarial liabilities, premium values, reserve estimates, and expected benefits may be examined to determine the magnitude of changes resulting from alternative assumptions. A quantitative research approach will be adopted for the study. Relevant insurance valuation data and actuarial assumptions will be obtained and analysed using descriptive statistics, scenario analysis, sensitivity analysis, and appropriate actuarial valuation techniques. Alternative assumption scenarios will be developed to examine changes in estimated insurance values. The resulting estimates will be compared to determine the sensitivity of insurance valuations to variations in key model parameters. The study is expected to reveal that changes in important actuarial assumptions may produce significant variations in insurance valuation estimates. The magnitude of the effect is expected to differ according to the parameter being changed and the type of insurance contract being valued. The findings may also demonstrate that sensitivity analysis provides useful information about assumptions that have a substantial influence on valuation outcomes. The study will be useful to actuaries, insurance companies, underwriters, regulators, financial analysts, and researchers. It may assist in identifying assumptions that require careful monitoring and improving the interpretation of actuarial valuation results. The findings may also support better risk assessment, financial planning, reserve management, and decision-making under uncertain economic and demographic conditions. The study concludes that actuarial model sensitivity analysis is an important technique for understanding variations in insurance valuation estimates and assessing the effects of changes in key model assumptions. It is therefore recommended that insurers and actuaries incorporate systematic sensitivity analysis into actuarial valuation processes to improve the reliability, transparency, and robustness of insurance valuation estimates.

Keywords: Actuarial model sensitivity analysis, insurance valuation estimates, actuarial valuation, model assumptions, mortality assumptions, interest rate assumptions, claim frequency, claim severity, insurance liabilities, premium valuation, reserve estimation, sensitivity analysis, actuarial modelling, insurance risk assessment, valuation uncertainty.