probabilistic view and that using longer time periods (50 to 100 years) leads to more robustly calibrated stochastic models. However, it is possible that the risk of extreme events may be underestimated if most of the data comes from a period when climate change had less of an effect on the underlying weather risk.
The “new normal” scenario
Our scenario assumes that the past decade is typical, and it considers catastrophe loss experience on a gross basis (that is, excluding the effect of retrocession protection). It projects that the highest catastrophe loss events seen in this period (adjusted for inflation and exposure changes) would recur every 10 years on average, that is, would be considered a one-in-10-year event. Our annual catastrophe surveys include each reinsurer’s calculation of its one-in-10- year loss event. To calculate losses under the “new normal” scenario, we took the highest catastrophe loss each reinsurer suffered during the past decade, adjusted for inflation and changes in exposure. We calculated how its catastrophe risk exposures would look if that was its one-in-10-year loss.
On average, our scenario’s one-in-10- year loss is around 50% higher than the one-in-10-year loss reinsurers are modeling. (Most reinsurers are in the range 0% to 80%.) We then extrapolated from the one- in-10-year loss to find the one-in-250-year loss under the scenario, because we input this level into our capital model to assess a reinsurer’s capital needs for catastrophe risk. We estimate that on a gross basis, reinsurers may be understating both the one-in-10 and the one-in-250-year loss by the same magnitude (around 50%). Even though we did not explicitly quantify it, the impact after retrocession recoveries may be somewhat higher. This is because the average benefit of retro protection reduces at this increased level of estimated losses. The benefit of retrocession protection may be further reduced if extreme losses are accompanied by an increase in frequency because most reinsurers have very limited protection after a second catastrophe event occurring within a contract year. Purchasing new retrocession protection may be prohibitively expensive after a second major catastrophe event.
Impact on the rating metrics Under this scenario, key ratings metrics which we use to assess reinsurers’ capital adequacy
Global Reinsurance Highlights 2014
Chart 1: Earnings Versus Capital At Risk Exposure: The "New Normal" Scenario Impact
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4
010 © Standard & Poor's 2014. Midsize global obal Bermuda
Midsize global uda
Global Gl al Prop-cat Prop cat Sector average
rop-cat Gl
Globall London Lo Bermuda Sector average Prop cat Prop-cat Lond London
20
30
40
50
60 One -in-250 year net catastrophe loss versus shareholders' equity (%)
PBT = Profit before tax. Prop-cat = Property-catastrophe/Short-tail. Blue area = Reinsurers’ modeled results Red area = “New normal” scenario
70
80
and catastrophe exposure are materially affected. The reinsurers that have the highest catastrophe exposure would be most affected. The average capital adequacy of the reinsurers we rate could fall from extremely strong to the high end of very strong. In addition, in the event of a one-in-250-year loss, capital at risk would be 54% as a percentage of total adjusted capital, up from 36% (see “Global Reinsurers’ Appetite For Catastrophe Risk Remains Largely In Check”).
Reinsurers’ exposure to earnings volatility would be also higher if a one-in-10-year loss were as high as we have projected in this scenario. We use the earnings-at-risk exposure metric (defined as the one-in-10- year loss impact on two-year average of profit before tax excluding catastrophe losses) to measure earnings volatility for rated insurers, which our scenario indicates would increase to 112% from 75% (see “Global Reinsurers’ Appetite For Catastrophe Risk Remains Largely In Check”). Investors may be less willing to support reinsurers with high catastrophe exposure if the probability of increased annual losses is higher.
What Can We Learn From This Scenario? We recognize that the approach described above is too simplistic to give us a reliable insight of what might be the “new normal”. We anticipate that the real impact of climate change on catastrophe experience will likely fall between the view shown in our scenario and reinsurers’ currently modeled losses. However, the scenario’s pessimistic estimate of potential exposure to catastrophe risk indicates the scale of
“Most reinsurers have very limited protection after a second catastrophe event occurring within a contract year.”
the impact climate change could have on catastrophe risk and ratings.
Although we recognize the difficulties in accurately capturing the potential impact of climate change on extreme events, we take a favorable view of reinsurers whose capital modeling and exposure management takes into consideration how climate change may affect extreme weather events. We consider that disregarding the possible impact may lead reinsurers to accept higher catastrophic risk than their risk appetite would usually allow.
Miroslav Petkov London, (44) 20-7176-7043
miroslav.petkov@
standardandpoors.com Mark Coleman
London, (44) 20-7176-7006
mark.coleman@
standardandpoors.com
Dennis Sugrue
London, (44) 20-7176-7056
dennis.sugrue@
standardandpoors.com
23
One-in-10-year catastrophe loss versus PBT two-year average excl. catastrophe losses (x)
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