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Effect of Model Parameter Uncertainty on Insurance Premium Estimates

Abstract

The study examines the effect of model parameter uncertainty on insurance premium estimates, focusing on how uncertainty in the parameters used in actuarial models influences the estimation of insurance premiums. Actuarial premium models depend on parameters such as claim frequency, claim severity, mortality rates, interest rates, and other risk measures. Uncertainty surrounding these parameters can affect the reliability of estimated premiums and create challenges for insurers in accurately pricing insurance risks. The study will investigate how variations and uncertainty in model parameters affect insurance premium estimates. It will assess the extent to which parameter uncertainty produces changes in estimated premium values under different assumptions. The study will also examine the sensitivity of premium estimates to changes in selected actuarial parameters and identify the parameters that produce substantial variations in premium estimates. The analysis will focus on model parameter uncertainty, insurance premium estimates, claim frequency, claim severity, risk assumptions, parameter estimation, and premium variability. Actuarial modelling and sensitivity analysis will be applied to examine how changes in parameter values influence calculated premiums. Statistical estimation techniques may also be used to quantify the effect of uncertainty surrounding the selected model parameters. A quantitative research approach will be adopted for the study. Relevant insurance claims and policy data will be analysed using descriptive statistics, parameter estimation techniques, actuarial pricing models, and sensitivity analysis. Simulation techniques may be employed to generate alternative parameter scenarios and evaluate their effects on estimated insurance premiums. Comparative analysis will then be used to assess the differences between premiums estimated under alternative parameter assumptions. The study is expected to reveal that model parameter uncertainty has a measurable effect on insurance premium estimates. Changes in estimated claim frequency, claim severity, or other model parameters may produce corresponding changes in calculated premiums. The extent of premium variation is expected to depend on the sensitivity of the pricing model to individual parameters and the degree of uncertainty associated with their estimation. The findings are expected to provide useful information for actuaries and insurance companies in evaluating the reliability of premium estimates. The study may support the use of sensitivity analysis, simulation, and appropriate parameter estimation techniques to identify and manage uncertainty in actuarial pricing models. It may also contribute to more consistent premium determination and improved assessment of insurance pricing risk. The study concludes that model parameter uncertainty is an important consideration in actuarial premium estimation. It is therefore recommended that insurers and actuaries regularly assess parameter uncertainty and apply appropriate statistical and actuarial techniques to evaluate its potential effect on premium estimates and support sound pricing decisions.

Keywords: Model parameter uncertainty, insurance premiums, premium estimates, actuarial modelling, parameter estimation, insurance pricing, claim frequency, claim severity, actuarial assumptions, sensitivity analysis, premium variability, statistical modelling, risk assessment, simulation techniques, actuarial pricing.