What is your role at MIS, and how did you become involved in disaster response?
I’m the Head of Sales & Marketing at MIS and joined the company in 2022. I’ve been working in Insurtech for my entire career and disaster response for nearly five years. I’ve always been drawn to roles that have a strong social benefit and have never felt this stronger than during my time in disaster response – providing the insurance industry with the critical intelligence it needs to make the claim process more efficient and effective for those impacted by disaster is the thing that drives me.
What is ‘disaster response’ and why is it so essential to the insurance industry?
People buy insurance for when the worst happens, and there is very little worse than being impacted by a catastrophic event – the largest of which can cause people to be left with nothing. The insurance industry offers hope in the form of the protection it provides, and the promise made within the policy. It is also an opportunity for the industry to prove their benefit to their policyholders and communities affected by these events.
Dependant on the type of event, we’ll deploy Optical, Synthetic Aperture Rader (SAR), Thermal, or Low-Light satellite imagery, high-resolution aerial imagery, super high-resolution drone imagery, our CAT360 imagery which utilises super high-resolution cameras mounted on vehicles for a unique view of the affected area, ground-based radar, river and tidal sensors, and much more.
Daniel Grimwood-Bird
How does MIS operate/manage a disaster response – what’s the process from reception of intel to finishing with a case?
MIS was built on the intelligence principals from Military Intelligence, and we apply as much rigor into preparing for a disaster to occur as we do in responding to one. We have built a huge available dataset to call upon, including satellite, aerial, drone, and ground-based imagery, IoT sensors, meteorological data, and more, to ensure that whatever the disaster type, and wherever it occurs in the world, we’re able to respond.
We commit to our first report being available within 24 hours of the disaster and, as more data becomes available, will build these into our response to refine the granularity down to individual property damage. We host our client’s exposure/PIF to be able to provide them with bespoke intelligence on the impact to their portfolio, policies, and properties.
What technologies are you using to carry out these processes and gather data?
One of the things that our clients appreciate the most about MIS is that we’re constantly researching and vetting the latest innovations in the world of observation technology. Dependant on the type of event, we’ll deploy Optical, Synthetic Aperture Rader (SAR), Thermal, or Low-Light satellite imagery, high-resolution aerial imagery, super high-resolution drone imagery, our CAT360 imagery which utilises super high-resolution cameras mounted on vehicles for a unique view of the affected area, ground-based radar, river and tidal sensors, and much more. Overall, we have over 100 data sources at our disposal to help provide clients with comprehensive coverage of global events.
when the 7.8 magnitude earthquake struck southern Turkey and Syria, we responded rapidly and provided a detailed damage assessment of the affected areas… by 1pm on that day, our client Zurich was reviewing damage to affected properties and securing local resources much quicker than previously possible.
Daniel Grimwood-Bird
Can you tell us about any recent case studies that demonstrate the work MIS does?
There’s a couple that spring immediately to mind – when the 7.8 magnitude earthquake struck southern Turkey and Syria, we responded rapidly and provided a detailed damage assessment of the affected areas. It was understandably a very challenging time for insurers, given that these affected areas weren’t easily accessible, but by 1pm on that day, our client Zurich was reviewing damage to affected properties and securing local resources much quicker than previously possible. Their claims team were already informed of the situation at specific locations prior to FNOL being received, resulting in a much quicker response for their policyholders and claims payments being sent out on the same day.
MIS operates using fact-based data rather than models – why is this?
We do different jobs – models predict the unknown and future decisions can be made on them, but they’re not designed to be fact. In the aftermath of a disaster, our clients want to know that they can trust the intelligence that we provide, where they can receive actionable insights into how their portfolios are affected and as a result, ensure their decision-making processes are informed by accurate data.
Are you seeing a markedly increased number of climatic events – and what are your predictions for the disaster recovery space?
Whether we’re seeing more disasters purely in terms of numbers is up for debate, for example the 2023 hurricane season saw very little landfalls (albeit still with a high number of formations) but 2024 looks like it’s going to be far more active. What we are seeing is catastrophic events causing more damage which is driven by a couple of factors –they are moving from their traditional risk areas, for example, hail in the US is moving further west and European hail and wildfire are now annual and severe events, and due to population increases and urban sprawl, the bullseye for the events to cause greater damage has increased.
The disaster recovery space, more generally, is an extremely exciting one. There are a number of amazing companies doing incredible things with new sensors to increase the resolution in which we’re able to see damage after a disaster and the volume of satellites that we have access to is ever increasing.
If carriers haven’t already started using disaster response intelligence to evolve their claims processes, then they will be doing so very soon. The weight of expectation from policyholders, brokers, investors, and potentially in the future, regulators, to utilise the technology and data available to them to positively impact their response, is undoubtedly growing.
I also see AI being more involved in disaster response in the future, although it’s not quite there yet. Seeing that there was a building and now there isn’t after a tornado is one thing, but being able to detect the difference between damage and debris on a roof is an incredibly difficult task for AI to achieve right now, especially to be used at scale for all perils, globally.
Interview by Joanna England
