Geospatial tech is transforming insurance

Insurance is at a hinge moment in its history. For four years in a row, the industry has absorbed over $100 billion in losses linked to natural catastrophes every year. Even in 2023, a ‘quiet’ year, 28 meteorological events and climatic disasters generating losses of over $1 billion were recorded. Climate change is rewriting the rules, bringing more frequent and severe disasters to our towns and cities. This poses a serious question: how can insurers keep providing protection when the risks grow so large that even the most robust, time-honoured models start to break down?

For decades, what insurers feared most were ‘peak perils’ – events like hurricanes and earthquakes, which can wreak widespread devastation in an instant. But this approach, while logical, has its blind spots. The real threat today comes from ‘secondary perils’ like wildfires, floods, and severe storms. (Given the destruction these events cause – recent events in Florida, northern Portugal and central Europe have made this plain – it seems almost wrong to consider them secondary.) The fact is that these events are smaller in scale. But, crucially, they occur more frequently and are increasingly . As climate change intensifies, they also become more severe. Over time, their cascading effects lead to losses on par with, or exceeding, those of peak perils. The AXA Future Risk Report has considered climate change humanity’s number-one risk for five years running.

That’s why the industry has to evolve. Insurers can recalibrate their approach to accommodate these secondary risks, and so make sure that coverage is affordable and available for literally millions of businesses and homeowners. We at AXA DCP are calling on insurers to face up to this real and very real and daunting reality, and to look to technology – geospatial technology, in particular – to adapt to our ‘new normal’.

But let me be more concrete. Traditional insurance models rely on historical data to assess risk. This approach has served as well. We know from Hume that inductive inferences, or predictions based on past observations, are not rationally justifiable. But practice has shown us that the past is the best predictor of the future. The problem now is not philosophical. It’s a problem rooted in the reality in which we now live, a reality in which the past cannot predict the future with the same level of accuracy as it once did. Climate change, which is getting worse, has made floods more intense, wildfires more frequent, and storms more unpredictable. What’s more, these risks often strike with highly localised impact.

So we need not just to know if or when or where a disaster might happen. We need a level of precision, and an ability to operate at scale but enable local action, that the old methods can’t deliver. And that’s where geospatial technology comes into play.  Because geospatial technology combines imagery for multiple satellites equipped with advanced remote-sensing tech, and AI-powered analytics to provide real-time insights into risk. Geospatial data crunches the raw data satellites gather, stitching together the images and converting what they see into information we can actually use. For insurers, this is revolutionary. With high-resolution images and machine-learning, we can map vulnerabilities with pinpoint accuracy – whether it’s a house in a floodplain, a factory in a fire-prone zone, or a business park at risk of storm damage.

This innovation enables two vital changes. First, it lets us predict and prevent catastrophic natural events before they occur. Second, it helps us tailor coverage to reflect the true level of risk, ensuring that protection remains affordable and fair. For example, in wildfire-prone regions, we can use geospatial data to model how fires might break out and spread based on wind patterns, vegetation density, and dozens of other factors. Businesses can receive early warnings, allowing them to take action – clearing brush, for example, or reinforcing structures, or evacuating if needed. And insurers can adjust premiums dynamically to reflect the reduced risk.

Similarly, for floods, geospatial technology can identify vulnerabilities at the micro level. This allows clients to install defences in advance and helps communities target infrastructure investments where they’re most needed. In both cases, insurance moves from being a reactive safety net to a proactive partner in resilience. That’s a historic shift.

And it isn’t theoretical. This technology is being used more and more worldwide, including by emergency services in France. Nor is it just for businesses. By providing geospatial data, insurers can empower entire communities. Imagine a neighbourhood receiving tailored alerts about an approaching storm, along with actionable advice on how to protect their homes. Or consider a city government using geospatial analytics to prioritise flood mitigation projects. This is the future. The potential to save lives and reduce losses is immense.

The insurance industry has always been about managing uncertainty. But in the face of climate change, our role must expand. We need to move from responding to disasters to helping to prevent them. Geospatial technology – married, as always, to the human expertise of insurers – enables us to do just that. By making use of real-time data and predictive analytics, insurers can provide clients with actionable insights, early warnings, and customised solutions. This isn’t just about keeping homes and businesses insurable. It’s about building a more resilient society.

by Pierre du Rostu, CEO of AXA Digital Commercial Platform