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Effect of General Insurance Product Mix on Aggregate Loss Estimates

Abstract

General insurance product mix refers to the combination and relative composition of different general insurance products within an insurer’s portfolio. These products may include motor, property, liability, marine, fire, and other forms of non-life insurance, each with different claim frequencies, claim severities, and loss characteristics. Variations in the composition of an insurer’s product mix may therefore influence the overall level and distribution of aggregate insurance losses. This study will examine the effect of general insurance product mix on aggregate loss estimates. It will assess how differences in the composition of general insurance portfolios influence the estimation of total expected losses. The study will also compare aggregate loss estimates under different product mix structures to determine how changes in the relative contribution of individual insurance products affect overall loss projections. The study will focus on general insurance product mix, aggregate loss estimates, insurance portfolios, claim frequency, claim severity, loss distributions, expected losses, product composition, insurance exposure, aggregate claims, and actuarial loss modelling. Different product combinations and portfolio compositions will be examined to identify variations in aggregate loss experience. Statistical and actuarial techniques will be applied to evaluate the relationship between product mix and aggregate loss estimates. A quantitative research approach will be adopted for the study. Historical claims, exposure, premium, and loss data from selected general insurance products will be analysed using descriptive statistics, claim frequency and severity analysis, loss ratio analysis, probability distributions, aggregate claims modelling, comparative analysis, and sensitivity analysis. Aggregate loss estimates generated from alternative product mix structures will be compared to determine the effect of portfolio composition on expected losses. The study is expected to reveal that general insurance product mix may have a significant effect on aggregate loss estimates. Portfolios with a greater concentration in products characterised by higher claim frequency or severity may produce higher aggregate loss estimates, while portfolios with different product compositions may generate different loss patterns. The magnitude of the effect may depend on product-specific claims experience, exposure levels, portfolio size, claim distributions, and the degree of concentration across insurance products. The study will be useful to actuaries, insurance companies, pricing analysts, underwriters, claims analysts, risk managers, portfolio managers, and insurance researchers. It may provide useful information for assessing portfolio composition, improving aggregate loss estimation, supporting premium pricing and reserving decisions, and strengthening insurance risk management. The findings may also assist insurers in understanding the actuarial implications of changes in their general insurance product mix. The study concludes that general insurance product mix is an important consideration in aggregate loss estimation because differences in product composition can influence the frequency, severity, and overall distribution of insurance losses. It is therefore recommended that insurers regularly evaluate the loss characteristics of individual products, monitor changes in portfolio composition, and apply appropriate actuarial modelling and sensitivity analysis when estimating aggregate insurance losses.

Keywords: General insurance product mix, aggregate loss estimates, insurance portfolio, claim frequency, claim severity, aggregate claims, loss distributions, expected losses, insurance exposure, actuarial loss modelling, loss ratios, portfolio composition, insurance risk, aggregate loss modelling, sensitivity analysis.