Tag Archives: mortality risk

Mortality and catastrophe risk reinsurance

In July 2020, Milliman published the research report “Reinsurance as a capital management tool for life insurers.” This report was written by our consultants Eamon Comerford, Paul Fulcher, Rik van Beers and myself.

Capital management is an increasingly important topic for insurers as they look to find ways to manage their risks and the related capital requirements and to optimise their solvency balance sheets. Reinsurance is one of the key capital management tools available to insurers. The paper investigates common reinsurance strategies, along with new developments and innovative strategies that could be implemented by companies.

This blog post is the eighth in a series of posts about this research. Each post provides an overview of a certain section of the Milliman report.

Mortality and catastrophe risk reinsurance

Two common interrelated risks that life insurers can face are mortality risk and catastrophe risk. Mortality risk is the risk of both policyholders dying earlier than expected and more policyholders dying than expected. This risk occurs gradually throughout the duration of the portfolio. If best estimate mortality rates are set too low then, as a result, provisions for mortality covers are insufficient to cover liability payments.

Catastrophe risk is the risk of many policyholders dying or falling sick due to a sudden event, such as a pandemic. The effects of a catastrophe shock are felt more immediately than the effects resulting from a mortality shock. A recent example of this is the COVID-19 pandemic.

Determining mortality risk and catastrophe risk

Setting robust best estimate mortality parameters for an insurer’s portfolio can be subject to a substantial amount of expert judgement, especially in the case of smaller portfolios or where the insurer does not have a lot of experience. Mortality risk can be quite material, as a small variance in the portfolio’s mortality can readily lead to insufficient reserves. This especially holds true if this variance occurs on life covers from individuals with above average sums assured. Estimating catastrophe risk can be challenging. Parameters and models used to determine the catastrophe risk are dependent on the event driving it. In the case of a pandemic, variables such as social distancing, contagiousness, population age structure and lethality are important when calibrating a catastrophe risk model.

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