Dependence modelling for heavy-tailed multi-peril insurance losses

Assessing and managing risks is essential for insurance companies. We recognize the heavy-tailed behaviour and dependency among different coverages in insurance claim datasets. To capture claim dependency, we proposed a hierarchical model and several Copula-Based models. Composite models are applied to address the heavy-tailed behaviour of individual losses. To evaluate the performance of the proposed model from the insurance aspect, we approximate the risk measures using the Monte Carlo methodology. Finally, we demonstrate that the model considering dependency enhances model goodness-of-fit while providing more accurate risk measures of the aggregate losses for all types of coverage in total.