Managing risk in an age of extreme weather… towards calibrating and predicting volatility
Every year on 5 June, World Environment Day is celebrated around the globe. This year’s theme is about living in harmony with nature. And yet, with the increasing unpredictability of changing weather patterns wreaking havoc on communities worldwide, it is unlikely that countries will become immune to climate risk any time soon. Ronald Richman, chief actuary at Old Mutual Insure, weighs in on what this means and how the insurance industry is thinking about these events.
In the coming seasons South Africa is expected to emerge from the La Niña phenomenon – topping off a decade characterised by frequently alternating La Niña and El Nino events. The increased severity of flood and fire associated with this scenario, while extreme, is not unprecedented.
Already we have seen the devastating impact of singular events characterised by extreme weather: The recent devastating KwaZulu-Natal floods was among the deadliest and costliest South African storms on record, causing wide scale catastrophe in the province. While the area focuses on rebuilding, it is important to acknowledge what the data is telling us: As our climate changes, and global warming in particular increases, the levels of damage and loss incurred over the last decade point to a future where volatile and more intense weather becomes the norm.
And the insurance implications of this new normal stretch way beyond South Africa.
Insurance is a globalised industry. To date, the local insurance industry has generally not resorted to passing weather-related losses on to policyholders in the form of premium increases. Beyond normal inflation and standard operational increases, the costs of a decade of volatile weather have, on the whole, been absorbed and managed by South Africa’s well-capitalised risk sector. Going forward, however, if historically large floods in Germany, wildfires in California and Australia and droughts in Japan become the norm, increased global reinsurance costs will inevitably drive up the cost of cover in South Africa.
In a globally interconnected climate system no one, or no one country, is immune from climate risk.
While long-term global warming scenarios have been clearly mapped, right now there are no shorter-term predictive models that can confidently say when we will see another weather phenomena like the La Niña event; whether next year this time or in six months’ time.
According to Willem Landman, professor in meteorology at the University of Pretoria and specialist in seasonal to decadal forecasts, oscillations in weather patterns are difficult to predict, and it was impossible to predict that La Niña would last for a second consecutive summer, the impact of which we have already felt in places like Gauteng and Kwa-Zulu Natal this year.
And yet, predictability and the planning that it enables are key to managing risk and the cost of insurance.
The more predictable a risk, the easier it is to manage – and the cheaper it is to price. The short-term weather volatility emerging in response to long term climate change is, however, currently not possible to predict.
In an age of climate change driven by global warming, unpredictable short-term weather phenomena are challenging the insurance industry’s predictive pricing models.
As such, the risk sector in South Africa and around the world is struggling not only to find a way to calibrate the impact of long-term climate change, but also to predict and calculate the immediate costs of short-term weather volatility.
Bringing predictability to the long and short-term impacts of climate change demands a response able to blend client data and global and regional climate trends supported by accurate local weather tracking and measurement.
Asset managers, for example, are increasingly calibrating ESG risk as a measurable component of asset value. If insurers are to begin developing similar models, the industry needs to work much more closely with the climate scientists to develop integrated predictive, climate, damage and loss models.
The implications of building more data around changing weather patterns are, however, far broader than their impact on individual policyholders.
In South Africa, for example, only a very small percentage of citizens have insurance. Yet the vast majority of South Africans, without any form of cover at all, experience the same volatile weather damage and loss as the insured minority. Much of the flood and storm damage occurring on South Africa’s East coast over this and the last year, for example, was sustained by communities and individuals largely without insurance. How does insurance or, in its absence, compensation work in such scenarios? What is the role of the state? Should South Africa have national flood insurance, like the United States or the newer arrangements in the United Kingdom? What about fire loss in informal settlements?
In developing societies in particular, climate change – and volatile weather – is impacting the edges of urban centers disproportionately. Flood and fire, for example, affect urban fringes the most, where infrastructure is not fully developed, or human infrastructure is surrounded by bush or forest. Any predictive climate change model would, therefore, also need to factor in where people live or where property is located.
And where you are in the world will also make a difference.
Looking at the long-term and going beyond individual or personal loss, Landman also argues that if average temperatures in South Africa increase by even a few degrees over the next few decades, the kinds of crops being planted now will no longer grow in South Africa in 30 years’ time. As rainfall patterns and crop varieties change, will South Africa be able to continue to feed itself? Extrapolated globally, what will this mean for migration, immigration and food and national security around the world? What are the implications for borders, nations, states or the current world order?
None of these questions nor any of the risks can be answered or managed without a calibrated, integrated, and predictive global climate and local weather risk model.
The big challenge in both the risk and the climate science communities is to build the quantitative linkages between long-term global warming and climate change, short-term weather volatility and individual, business and industry risks.
Key in this will be a model needed to leverage the skills, disciplines and data required to understand and predict the impact of global changing weather patterns on the short and medium-term weather phenomena, currently causing so much damage. DM
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