Earnings perils: Redefining the risks that matter
Moody’s RMS’ Rob Stevenson on why the term ‘secondary perils’ is overdue a rethink.
The insurance industry, with good reason, has historically focused on what it regards as primary perils, namely tropical cyclones and earthquakes. Catastrophic events such as the Tohoku quake and hurricanes Andrew, Katrina and Ian have generated significant market losses and even threatened insurers’ survival.
But the cumulative impact of small to mid-sized loss events, or losses from perils that follow on as a secondary effect of a primary peril – such as flooding, wildfires, tornadoes, hailstorms and tsunamis – can lead to increasing and alarming levels of loss for many (re)insurers.
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”.
The frequency of these so-called secondary peril events typically outpaces that of primary perils and they are often more unpredictable and localised. They are also vulnerable to both climate change and external economic factors such as increases in property exposure, inflation and supply chain issues.
Whereas primary perils typically produce industry-wide losses impacting large swathes of the market, for secondary perils, any uptick in severe weather events and an increased volume and magnitude of claims can chew away at earnings, with C-suite executives asking why earnings performance lags their peers.
Small, frequent secondary peril events can cause a year-over-year erosion of earnings – contributing to earnings risk which is inherently tied to loss volatility. So, is it time to drop this 'secondary' label and reflect the true scope of their potential impact – as earnings perils?
The volatility of (re)insurance earnings can be examined at a portfolio level and is often measured as a 1-in-10-year annual exceedance probability normalised to the premium.
Measuring earnings perils poses a challenge that requires the use of risk models with a high level of detail, the ability to aggregate and measure correlation across multiple perils within the same event, and the capability to financially model complex policy terms and outwards reinsurance policies.
These capabilities provide underwriters with a more informed understanding of the frequency and severity of modelled perils.
Growing computing power through the cloud, together with technological advances over recent years, is helping deliver the required level of granularity to more accurately model high-gradient perils like floods, wildfires and severe convective storms, bringing secondary perils into clearer focus.
It is worth noting that the decision to classify a peril as an earnings peril or a primary peril will depend on a (re)insurer’s portfolio, given that a portfolio might have limited earthquake exposure but significant flood exposure.
Regardless, introducing the term ‘earnings perils’ underscores the significance of these risks and their potential impact on the profitability of a (re)insurer.
Rob Stevenson is senior client director at Moody’s RMS