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Effect of Dependence Between Insurance Lines on Aggregate Loss Estimates

Abstract

Insurance companies commonly operate across multiple lines of business, such as motor, property, liability, and health insurance, each of which can generate different patterns of claims. However, losses across these insurance lines may be dependent because they can be affected by common economic, environmental, social, or catastrophic factors. The presence of dependence can influence the distribution of total portfolio losses and is therefore an important consideration in aggregate loss estimation. This study examines the effect of dependence between insurance lines on aggregate loss estimates. The study will assess how relationships between claims arising from different insurance lines influence the estimation of total losses within an insurance portfolio. It will focus on how alternative dependence assumptions affect expected aggregate losses and the assessment of overall portfolio risk. The study will consider factors such as claim frequency, claim severity, correlation between insurance lines, exposure levels, loss distributions, portfolio composition, and common risk factors. Dependence between selected insurance lines will be modelled to determine how changes in the strength and structure of relationships between lines affect aggregate loss estimates. The study will also compare aggregate loss estimates under dependent and independent assumptions. A quantitative research approach will be adopted for the study. Historical claims and exposure data from selected insurance lines will be analysed using descriptive statistics, correlation analysis, probability distributions, dependence models, compound loss models, and simulation techniques. Alternative dependence structures will be applied to estimate aggregate losses and examine changes in expected losses and other portfolio risk measures. Sensitivity analysis will also be used to assess the effect of varying dependence assumptions. The study is expected to reveal that dependence between insurance lines may significantly affect aggregate loss estimates. Positive dependence between insurance lines may increase the likelihood of simultaneous or closely related losses and consequently produce higher aggregate loss estimates than models based on independence. The findings may also show that ignoring significant dependence can lead to an understatement of total portfolio risk, while the magnitude of the effect depends on the strength of dependence and the characteristics of the individual insurance lines. The study will be useful to actuaries, insurers, risk managers, regulators, and financial institutions involved in insurance portfolio management. It may provide useful information for improving aggregate claims modelling, assessing diversification benefits, determining capital requirements, evaluating portfolio risk, and strengthening risk management practices across multiple lines of insurance business. The study concludes that dependence between insurance lines is an important factor in estimating aggregate insurance losses because interconnected claim outcomes can materially influence the distribution and magnitude of total portfolio losses. It is therefore recommended that insurers incorporate appropriate dependence structures into aggregate loss models, regularly analyse relationships between insurance lines, use reliable claims data, and apply simulation and sensitivity analysis to improve the accuracy of aggregate loss estimates.

Keywords: Insurance lines, dependence between insurance lines, aggregate loss estimates, aggregate claims, insurance portfolio, claim frequency, claim severity, loss distributions, risk correlation, dependence modelling, portfolio risk, aggregate loss modelling, actuarial modelling, simulation techniques, insurance risk.