With insurers largely focused on major catastrophic events and the two ‘primary’ perils – tropical cyclones and earthquakes – ‘secondary’ perils can get overlooked.
The accumulation of small-to-mid-sized loss events or losses from follow-on perils as a secondary effect of a primary peril – such as flooding, wildfires, tornadoes, hailstorms and tsunamis – is increasing.
According to a Gallagher Re report, during 2022, “secondary perils were again the most expensive on an economic basis and exceeded those on the insured loss side”.
More frequent than primary perils, often more unpredictable and localised, and vulnerable to both climate change and economic factors, attritional secondary peril events can exacerbate earnings risk which is inherently tied to loss volatility.
And as secondary peril losses chew away at earnings, C-suite executives will ask why performance lags their peers. So, should ‘secondary’ perils be called ‘earnings’ perils, and reflect their potential earnings impact?
To better understand the frequency and severity of secondary perils requires highly granular risk models, able to aggregate and measure correlation across multiple perils within the same event, and financially model complex policy terms and outwards reinsurance policies.
Growing computing power together with technological advances over recent years is helping deliver the required level of granularity to more accurately model high-gradient perils such as floods, wildfires and severe convective storms, to bring secondary perils into clearer focus.
The latest models can enhance a firm’s understanding of their 1-in-10 annual exceedance probability, as the cloud’s computing power enables higher-res modelling, complemented by a much higher number of event simulations. This facilitates improved financial modelling across multi-peril events.
Introducing the term ‘earnings perils’ helps to underscore the significance of these risks and their potential impact on the profitability of a (re)insurer.
