This article first appeared in the May issue of Leader’s Edge Magazine, the award-winning content platform for The Council of Insurance Agents and Brokers.

In recent years, parametric insurance has gained traction as a great way to address a policyholder’s most pressing needs immediately after a flood. Taking advantage of the emergence of several new technologies, it has fast become an important solution to the global flood under-insurance problem, offering greater resilience at a fair price. In the headline piece of our annual magazine, we discuss the key factors that make a good parametric trigger. We also reflect on how co-founders Adam and Ian came to choose the FloodFlash smart sensor.

What makes a good parametric trigger?

Parametric insurance is a type of insurance that pays out based on the occurrence of specific predetermined events or conditions, rather than the actual financial loss incurred by the policyholder. It typically covers natural disasters such as floods, earthquakes, and hurricanes.

Measurements determine play a fundamental role in parametric insurance as they determine when a policyholder receives their payout. Insurers need a robust system in place to collect, process, and validate measurements in a timely manner, to allow for the fast and efficient payment of claims for which parametric insurance has become known. When it comes to parametric cover, the transparency of a good measurement system represents a clear advantage over traditional insurance. In traditional insurance, the possibility of a poor loss adjustment process can risk delays, anxiety and shortfalls in coverage.  

Choosing a parametric trigger measurement for flood insurance

When we started FloodFlash a major task was to explore what trigger measurement to use. A good parametric trigger measurement for flood insurance needs several key features to ensure accurate and reliable data. These features include:

1. Related to loss: a parametric trigger should provide a good proxy for the costs of loss caused by an event. The trigger should be related as closely as possible to the loss in order to minimise basis risk.
2. Accuracy and resolution: if a policy is tuned to the costs which are expected by a customer, the measurement needs to be accurate enough to make sure that it can determine reliably whether a threshold has been met. 
3. Reliability: we must be able to guarantee that the measurement can be made relatively easily. We also need to ensure the likelihood of a missing measurement is very low. In particular, this means that the method of measurement should be resilient enough not to be impacted by an event itself.
4. Transparency: trust is an important part of an insurance contract. The nature of parametric claims (if this event happens, then the policy pays) makes for a more transparent claims process provided the customer can easily interpret the trigger.
5. Cost-effectiveness: the cost of taking measurements and processing the data for the lifetime of a contract must be affordable.
6. Speed: making payments quickly in the aftermath of a disaster is a key benefit of parametric insurance and a great predictor of financial recovery. We need measurements that can be taken and delivered in near-real time.

Having established what makes a good trigger, we had two further questions to answer: what should we measure? And what technologies should we use to measure it?

What to measure – depth as a proxy for loss

In parametric flood insurance, the widely used trigger measurement is depth of water, because, typically, it scales positively with loss. For example, a building that is submerged under several feet of water is likely to have sustained more damage than a building that is only partially flooded. In a few applications, such as agriculture or larger-scale governmental projects, the total area flooded or number of buildings affected might also provide a good proxy.

Depth-damage curves have been developed using large datasets from historic flood events (e.g. USACE). These curves relate the depth of water at any given property to the level of cost. They are deployed in engineering-based risk assessments, as well as catastrophe models that have become widely adopted within the insurance industry.

The relationship between depth and damage will be specific to a particular building, both due to its construction and the value of any contents. Other factors such as water quality, duration of flooding, and the velocity of flowing water can also influence the amount of damage, although for any location their scale and impact are likely to be related to the depth of flooding that happens.

How to measure – assessing available technologies

The choice of technology to measure a parametric flood trigger comes down to the specific application, and its ability to fulfil the six criteria outlined above. When we started our journey, solutions typically fell into one of two categories: satellites and river or tide gauges. 

While it makes sense to use satellite technology for area-based parametric insurance, even the most advanced technology has limitations. Satellites give a snapshot of flooding over a wide area. However the approach compromises on both accuracy and frequency of measurements. Like an impressionist painting, satellite data give pictures that look clear at a distance but lack detail and accuracy under the closest scrutiny. What’s more, to become more accurate, satellite data typically needs “ground truthing” to verify any view of a flood. This process relies on independent methods of measuring a flood to calibrate the images from the satellite – often ground-level sensors. 

That leads us neatly onto river and tidal gauges. Pre-existing gauges are often maintained by public agencies, such as the Environment Agency in the UK, or NOAA and USGS in the USA. They provide accurate and high-frequency measurements of river depth or tide levels that are both transparent and reliable. Using these for parametric triggers solves some of the problems posed by the satellite approach but introduces one of its own. 

Gauges can provide measurements that relate closely to loss for neighbouring locations. However, basis risk emerges very quickly as the distance between the insured property and the gauge increases. Existing gauges have usually been established to serve another purpose and would always be within an existing water body. The cost and maintenance required for an individual gauge is too high to be justified in the context of anything but the largest insurance contracts. Even for these larger contract, they would often be somewhat removed from the insured location. 

The best of both worlds

We needed to combine the ability for a satellite to provide data about flooding at any floodable location with the accuracy and reliability of measurements from river and tidal gauges. In 2018, we recognised that the emergence of IoT communications technology and low-cost electronic manufacturing had now made this possible. We developed a low-cost IoT water depth sensor which we can attach to the wall of any building or structure at ground level. Our sensor is designed to capture high-resolution measurements of water depth at very high-frequency during a flood. This small, battery-powered device can be placed in any areas that might be at risk of flooding. 

The FloodFlash sensor uses ultrasonic technology to provide millimetre-accurate water level measurements with an extremely high sampling rate. It works much the same way that a parking sensor on a modern car does. It measures the return time of an ultrasonic pulse within a tube, which reflects from the surface of water as it rises. The sensor takes a measurement every 5 minutes and processes the data in real-time. That means it accounts for environmental factors such as air temperature and humidity. It also takes into consideration the speed with which flash flooding can occur. 

Due to its size, ease of installation, and low cost, a FloodFlash sensor can be installed directly at any location(s) a customer wishes to insure. On-site installation drastically reduces basis risk compared to using river or tidal gauges without compromising on accuracy. The ease of installation means that we can create a network of readings across a country, or a client’s single property. That allows us to provide the broad picture of a satellite without compromising on reliability.

Measurements in action

The first major test of our sensor technology and cloud platform came in the UK in February 2020 during Storm Ciara. Several of our customers experienced devastating levels of flooding. In the first live run of our claims process we paid claims within 48 hours of water reaching their properties.

It’s a clever but simple piece of technology, it’s flexible and the payout is a big selling point.

Olivia Brown, FloodFlash broker

Over time, in subsequent storms, we have reduced this claim time even further. Last Autumn we paid one client in 3 hours and 50 minutes. Less than half a business day between water triggering the policy and money in the bank.

Speed of payment, enabled by our proprietary IoT sensor, is the crowning achievement of our efforts to deliver an accessible parametric flood insurance policy. Fast access to funds has a range of benefits for our clients. It can limit damage by preventing damp and mould, alleviate the stress involved, and provide a head start to recovery. More profoundly, studies in the aftermath of hurricane’s Irma and Harvey have shown that a business which can re-open within days of a catastrophe is more likely to survive in the long-term. What’s more, the number of businesses that do re-open is key to the recovery of a community overall. In this way, the sensor is much more than just a depth measurement device, within a parametric insurance policy, it is a lifeline for business survival.

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