Insights: The Race Between Education and Catastrophe

Technology can now track natural and man-made catastrophes as they unfold, link to insurers’ policy portfolios and notify clients about the risks in advance. Forbes McKenzie, Founder of McKenzie Intelligence Services, scans the horizon for the next developments when it comes to the integration of exposure data and the automation of claims information.

Forbes McKenzie

It was H G Wells who said “Human history becomes more and more a race between education and catastrophe” – a timeless phrase that aptly sums up the efforts of society to build resilience to the natural and man-made catastrophes that afflict us, and learn from them to be proactive about mitigating catastrophe risks in the future.

In recent years advances in geospatial technology have meant it’s become possible to be proactive when it comes to managing catastrophes, understanding exposure and predicting economic outcomes.

This is as true of natural catastrophes such as hurricanes, which can be tracked in real-time and whose future courses can be accurately forecast, as it is of man-made ‘black swan’ events such as the August 2020 Beirut explosion – where highly accurate imagery and exposure analysis were available within a matter of hours.

Climate change and natural catastrophes

Over the past 50 years, recorded natural disasters have increased five-fold, thanks in part to climate change, with one in three people on Earth not adequately covered by early warning systems according to the UN, which itself recently highlighted the urgent need to increase these systems for extreme weather events. What’s more, the State of Climate Services 2020 report points to the prediction that the number of people in need after natural disasters will increase by 50% over the next decade.

The 2020 Atlantic hurricane season has been a case in point – featuring tropical cyclone formation at a record-breaking rate, a dynamic that is indisputably linked to our warming climate. At the time of writing, hurricane Delta had made landfall in Louisiana the previous weekend, exposing over 172,000 properties to the full force of the storm with 227,000 impacted by the wider storm.

Our analysis of Hurricane Delta’s impact was available less than 24 hours after it made landfall, with a flood layer update within 48 hours and a full claims report following within 72 hours, and it compared damage caused by Hurricane Laura in the same area weeks before with more recent damage to ensure clarity and insight into timelines never before possible using traditional loss adjusting methods.

In the build up to, during and following catastrophic events, the re/insurance industry needs actionable intelligence from the ground so that mitigating action can be taken and policyholders can receive proactive service.

Right now, the automatic aggregation and analysis of space, air ground and internet of things (IoT) sensors can provide a highly accurate and holistic view of a catastrophic event, at hyper local, individual property level. Insurers can link this information to their policy portfolios via seamless API integration, delivering the power of drone and aerial imagery and straight to the desks of claims and exposure management teams, confirming levels of damage in near real-time.

Standing still is not an option

But this is no time to stand still and pat ourselves on the back – the need to quantify and understand the impacts of catastrophes has never been more urgent. In the future, insurance and disaster response workflows should be automated and seamless. Analytics is critical to this – using what we know so far to capture the footprint / life cycle of an event, to help predict the outcome of future events.

The process of evolution is speeding up, and we are now spearheading further growth in a number of fields, not least supporting our clients with in-house automation and risk mitigation, and underpinning a cultural shift towards trust and reliance on technology to replace costly and time consuming manual processes.

A Global Event Observer

From a market-wide perspective, our recent award of EUR 685,00 in co-funding from the European Space Agency will enable us to deliver a Global Event Observer for the insurance industry.

This represents a major evolution of MIS’ technology capability, and will enable the further collection and use of highly accurate, geotagged external data from a range of sources – including augmenting data from IoT devices and satellite and aerial imagery – to provide early warnings of loss events thereby increasing opportunities to mitigate the risks and support the transformation of claims workflows.

The features of a global event observer are far reaching, we can automatically ingest risk data, store and monitor it against insured perils, using a huge number of data sources from around the world.

Once a trigger event happens, delivery of the intelligence via API allows clients to act upon it in either their exposure management, claims or other workflows, greatly speeding these up workflows and providing very accurate data from the ground.

There will always be a gap between education and catastrophe, due to the inherent unpredictability of man-made catastrophes and the complexity of natural catastrophes events, but the race to narrow the gap is speeding up.

As an intelligence company, our priority is that our clients are able to take action and make decisions based on the carefully curated data and expert analysis we provide. The integration of highly accurate exposure data into re/insurers risk management strategies and the automation of claims information is critical to this, and we intend to stay at the forefront of research and development in this field to foster greater resilience in our industry and beyond.


About alastair walker 6830 Articles
20 years experience as a journalist and magazine editor. I'm your contact for press releases, events, news and commercial opportunities at Insurance-Edge.Net

Be the first to comment

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.