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Effect of Insurance Contract Cohort Size on Liability Projection Accuracy

Abstract

Insurance contract cohort size refers to the number of insurance contracts grouped together for the purpose of analysing and projecting their expected future cash flows and liabilities. The size of a cohort can influence the stability and representativeness of observed insurance experience used in actuarial projections. Proper assessment of cohort size is therefore important for producing reliable estimates of future insurance liabilities and improving the accuracy of actuarial projections. This study will examine the effect of insurance contract cohort size on liability projection accuracy. It will assess how variations in the number of contracts included within insurance cohorts influence the accuracy and stability of projected insurance liabilities. The study will also examine the relationship between cohort size, claims experience, policy characteristics, expected cash flows, and projected liability values. The study will focus on insurance contract cohort size, liability projection accuracy, policy grouping, claims experience, expected cash flows, policy duration, premium payments, benefit payments, mortality assumptions, and actuarial liability estimation. Actuarial and statistical techniques will be used to compare liability projections generated from different cohort sizes. Comparative and sensitivity analyses will also be applied to evaluate changes in projection accuracy under alternative cohort structures. A quantitative research approach will be adopted for the study. Relevant insurance contract, claims, premium, benefit, duration, mortality, and liability data will be analysed using descriptive statistics, cohort analysis, actuarial liability projections, forecast error analysis, comparative analysis, scenario analysis, and sensitivity analysis. Different contract cohort sizes will be evaluated and their projected liabilities compared with observed claims and cash flow experience to assess the accuracy of the resulting estimates. The study is expected to reveal that insurance contract cohort size may have a significant effect on liability projection accuracy. Smaller cohorts may produce more variable projections because they contain fewer contracts and may be more sensitive to individual claims experience, while larger cohorts may provide more stable estimates by incorporating a broader range of insurance experience. However, the effect may depend on the similarity of contracts within each cohort, claims variability, policy duration, mortality experience, and the quality of available data. The study will be useful to actuaries, insurance companies, valuation specialists, financial managers, underwriters, claims analysts, and insurance regulators. It may provide useful information for selecting appropriate cohort sizes, improving liability estimation, analysing insurance experience, strengthening actuarial projection models, and supporting financial reporting and reserve management. The findings may also assist insurers in determining suitable approaches for grouping insurance contracts for liability projection purposes. The study concludes that insurance contract cohort size is an important consideration in liability projection because the number of contracts included in a cohort can influence the stability and accuracy of projected insurance obligations. It is therefore recommended that insurers carefully determine appropriate cohort sizes based on the characteristics and experience of the underlying contracts, validate projected liabilities against observed experience, and conduct sensitivity analysis to assess the effect of alternative cohort sizes on projection accuracy.

Keywords: Insurance contract cohort size, liability projection accuracy, insurance cohorts, actuarial liability estimation, contract grouping, claims experience, expected cash flows, policy duration, premium payments, benefit payments, mortality assumptions, liability projections, forecast accuracy, actuarial analysis, sensitivity analysis.