What if…? How reimagining history could help insurers better analyse risk
What if a solar storm had struck during the London Olympics in 2012?
What if the wind had blown radioactive contamination onshore when the Fukushima nuclear plant was struck by a tsunami in 2011? What if West Africa had been embroiled in civil war during 2014’s Ebola crisis?
Major global events like these could have had even more serious impacts if things had happened just a bit differently.
The worst disaster in aviation history was narrowly avoided in July, for example, when a passenger plane pilot descending into San Francisco airport pulled up at the last second.
Lloyd’s, together with modelling company RMS, have published a new report – entitled Counterfactual Disaster Risk Analysis: Reimagining history – setting out how a type of lateral thinking, called counterfactual, can be applied to complement how insurers analyse risk.
The report discusses how downward counterfactual analysis – in other words considering how historical near misses might have become major disasters – can be carried out in practice. It acts as a starting point for future research into counterfactual events and their characteristics.
According to Lloyd’s, downward counterfactual thinking brings a range of benefits to insurers.
The fact that downward counterfactual events are anchored to actual historical experience helps facilitate complex explanation, deeper understanding and more coherent communication of future risks and modelling uncertainty to board members, policyholders, policymakers, risk managers and others.Trevor Maynard, Head of Innovation at Lloyd’s
Insurers will benefit from looking at the past as just one realisation of what might have happened. Whatever the past, risk insight is gained from exploring how things might have turned for the worse – the downward counterfactuals. By adopting a counterfactual perspective and exploring how historical events could have unfolded differently, additional insight can be gained into rare extreme losses that might otherwise come as a surprise.Gordon Woo, Catastrophist at RMS
Downward counterfactual risk analysis helps address the bias that can be inherent in some models that are based on the same historical data sets. By expanding the data available based on what could have happened, these models can be built with less reliance on single-source data, which might improve their accuracy. It also provides a useful tool for regulators to stress-test catastrophe risk models.
The report offers a way of systematically applying counterfactual thinking. At Lloyd’s we recognise that thoughtful risk management is already in place and this suggested methodology is a useful addition to the suite of tools that insurers and risk managers already use. After a disaster risk analysts tend to carefully study what happened, but comparatively little attention is paid to what might have happened. This is a demanding technical undertaking, but we think insurers will benefit from a systematic assessment of downward counterfactuals.Trevor Maynard, Head of Innovation at Lloyd’s
- The Lloyd’s research – Counterfactual Disaster Risk Analysis: Reimagining history – listed a number of counterfactual disaster scenarios.
- The largest historical solar storm occurred in 1859, and it is known as the Carrington event. On 23-24 July 2012, a Carrington like event occurred, but fortunately the Earth was not in the line of impact of the solar storm. But nine days earlier, the ignition spot of the coronal mass ejection from the Sun had been pointed directly at the Earth. The counterfactual chance of a Carrington like event in July 2012 during the London Olympic Games was about 4%, this could have seriously disrupted satellite communications and the commercial success of the Games.
- On 11 March 2011 a magnitude nine earthquake off the coast of Japan caused a massive tsunami that struck the Fukushima nuclear plant leading to the release of radioactivity. Counterfactually, the disaster might have been worse. From RMS examination of wind rose data around Fukushima, there was a significant chance of the wind direction blowing inland, causing more widespread radiation contamination. Fortunately, the wind blew most of the radioactivity released from the stricken nuclear plant out to sea.
- Infectious diseases can spread exponentially, if no effective containment controls are in place. The Ebola epidemic in West Africa in 2014 was eventually brought under control after intervention from the international medical and public authorities. But their intervention would have been harder if a civil war had been raging in West Africa at the time. Both Sierra Leone and Liberia have been prone to sustained political violence. For half of the past 25 years, there has been a civil war in one of these countries. Counterfactually, had there been a civil war in either country in 2014, for which there was a 50% chance, the ability to enforce the quarantines and safe burial practices would have been greatly diminished and the Ebola epidemic would have been very hard to bring under control.
- On the evening of 7th July 2017 Air Canada flight AC759 from Toronto was preparing to land at San Francisco airport. As the weather was clear, the pilot was on a visual approach but failed to see he was guiding his plane towards a taxiway where four fully loaded planes were waiting for take-off. The pilot pulled up when the aircraft was just 30 m off the ground. This could have been the greatest aviation disaster in history involving multiple planes and more than 500 passengers.
- Downward counterfactual thinking can be applied to two distinct categories of risk assessment. In traditional probabilistic natural catastrophe modelling downward counterfactual analysis can help test model sensitivity and insurers’ understanding of systemic uncertainty. It is also a useful way of expanding stochastic datasets by analysing additional plausible versions of actual events.
- As well as enhancing scenario-based modelling in areas where the data is poor (especially for emerging risks), downward counterfactual analysis could help by creating structured, transparent, scientific and evidence-led scenarios. These could augment existing limited historical loss event datasets and could improve insurer’s assessment of probable maximum loss scenarios.
- For catastrophe risk quantification, counterfactual risk analysis can be applied in all three core catastrophe modelling activities of a P&C (re)insurer, namely pricing, capacity management and capital calibration.
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