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Effect of Actuarial Model Selection on Claims Reserve Projections

Abstract

Actuarial models are important tools used by insurance companies to estimate future claims payments and determine the reserves required to meet outstanding insurance liabilities. Different actuarial models may produce varying estimates because they rely on different assumptions, development patterns, statistical structures, and approaches to projecting future claims. The selection of an appropriate actuarial model is therefore an important consideration in claims reserving and insurance financial planning. This study will examine the effect of actuarial model selection on claims reserve projections. It will assess how the selection of different actuarial reserving models influences projected outstanding claims liabilities and determine the extent to which alternative models produce differences in estimated reserve amounts. The study will also compare reserve projections generated from selected actuarial models using the same claims experience data. The study will focus on actuarial model selection, claims reserve projections, outstanding claims liabilities, claims development patterns, loss development factors, reserve estimation, actuarial assumptions, claims experience, and insurance reserving. Selected reserving models will be applied to historical claims development data to examine differences in projected ultimate claims and outstanding reserves. Measures of reserve variation and projection stability will also be considered in assessing the effects of model selection. A quantitative research approach will be adopted for the study. Historical insurance claims and loss development data will be analysed using descriptive statistics, claims development analysis, selected actuarial reserving models, comparative analysis, projection error analysis, and sensitivity analysis. Reserve estimates obtained from different actuarial models will be compared to determine how model selection influences projected claims liabilities and the consistency of reserve estimates. The study is expected to reveal that actuarial model selection may have a significant effect on claims reserve projections. Different models may produce varying estimates of outstanding claims and ultimate liabilities because of differences in their treatment of claims development patterns and underlying assumptions. The magnitude of the differences may depend on the volume and quality of claims data, development period, claims volatility, portfolio characteristics, and the suitability of the selected model. The study will be useful to actuaries, insurance companies, claims managers, financial analysts, underwriters, regulators, and researchers. It may provide useful information for evaluating alternative reserving approaches, improving claims liability estimation, strengthening insurance financial planning, and supporting more reliable actuarial decision-making. The findings may also assist insurers in identifying appropriate models for projecting outstanding claims under different claims experience conditions. The study concludes that actuarial model selection is an important factor in claims reserve projections because alternative models can produce different estimates of outstanding insurance liabilities. It is therefore recommended that insurers and actuaries carefully evaluate the suitability of reserving models, compare alternative reserve estimates, and conduct sensitivity analysis to support appropriate and reliable claims reserve projections.

Keywords: Actuarial model selection, claims reserve projections, insurance reserving, outstanding claims liabilities, claims development, loss development factors, reserve estimation, actuarial models, claims experience, ultimate claims, reserve adequacy, claims liabilities, actuarial assumptions, insurance risk, actuarial analysis.