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Climate change is triggering a generational capital crunch across insurance

Insurers have struggled to model the impact of climate change with potentially devastating implications, writes Highland Europe’s Jacob Bernstein.

a field of dry grass


The insurance industry is in trouble.

Let’s put aside the global economic downturn, and pull back from the wider financial sector. The long-term threat facing the industry is its inability to respond to climate change. 

In 2021, natural catastrophes caused an estimated loss of $270bn, of which $160bn – or 60 per cent – was not covered by insurance. These losses directly hit the bottom line of businesses and governments around the world. More recently, September’s Hurricane Ian led to $50-65bn worth of devastation alone, making it the second most costly catastrophe in history after Hurricane Katrina. Australia’s flooding set new records and carried a $4bn price tag, while France’s record hailstorms cost €5bn.

Instead of leaning into this growing challenge, traditional insurers are tapping out. During the first nine months of 2022, reinsurance capital shrunk by 30 per cent as insurers slammed the brakes on their risk appetite. 

Those insurers who remain in the market are issuing wild price increases. Property reinsurance rates have soared by 37 per cent. In the US, this figure sits closer to 50 per cent, while certain subsegments have seen rises of as much as 200 per cent. This discrepancy widens further as the availability of insurance drops, pricing out some markets, such as developing countries.

The result is a capital crunch that will have huge consequences for the industry itself, as well as the thousands of businesses exposed to more severe, and in some cases more frequent, natural disasters worldwide.

Rather than looking to innovate, the industry is burying its head in the sand.

Cut and run

The problem at the heart of this crisis is the way climate change is priced. For more than a century, the insurance industry has been built on backwards-looking models when pricing cover. They consider what the average losses were over the past 10, 20 or 30 years to determine the risk costs for the years ahead.

This leaves the industry blind to its growing risk exposure. In late 2021, an S&P Global report found that insurers, using this backwards-looking approach, were pricing “once-every-10-year” disasters as if they would only happen every 20 or 30 years. A staggering two to three times underestimation of the risk. 

Again and again, as claims exceed expectations and drive loss ratios above 100 per cent, the renewals season sees prices jump and exclusions rise. This creates a significant price gap on its own, which adds insult to injury when you consider that the industry already covers less than half of the economic losses caused by natural disasters every year.

What’s more, S&P found that many insurers are not even factoring climate change into their decision-making process in the first place, widening the climate rift further. 

It is for this reason that innovation is urgently required across the insurance sector.

Moving from reactive to proactive

One area where this challenge could be remedied is with a switch to forward-looking AI models, that use predictive data science techniques to assess more accurately what the risks are for the coming year.

Real-time data sources, such as satellite imagery, stationary sensors, radar or sonar data, combined with cutting-edge image recognition and machine learning algorithms, allow the probability of a cyclone, hailstorm or wildfire hitting a specific hectare of a forest, solar farm or coastal property to be modelled directly.

In the case of wildfires, for example, trigger events are typically human accidents or lightning strikes. Spread is determined by wind, temperature, and the presence of dry vegetation. Understanding these determining factors dramatically improves model accuracy, allowing insurance to be priced proportionately to the actual risk faced.

A role for parametric insurance?

Compounding the stakes here is the massive uncertainty created by the “indemnity” model of the traditional industry. Essentially, insurance payouts are based on actual losses incurred. This makes modelling these payouts difficult, and the process of calculating and agreeing them slow and expensive. 

When catastrophe strikes, insurance customers are often in dire need of a speedy payout, not years of legal disputes which they have unknowingly paid for as part of the cost of their original insurance.

Parametric insurance refers to cover that pays out a pre-agreed indemnity when an event occurs within set parameters that are objectively determined. Payouts can now be made within days and truly play a role in the customer’s survival, and the insurance policy is more cost-effective because the client is no longer funding its own loss estimation and adjudication.

Technology can make insurance much fairer for those at the forefront of dealing with climate change. Until action is taken, that group will only get bigger. 

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