Water Damage Claims Could Be Cut by 70%

Ondo InsurTech Plc (“Ondo”) – the London-listed insurtech aiming to become the world leader in claims prevention technology for home insurers – has released new independent research which shows how IOT-based claim prevention system LeakBot can reduce the cost of water damage claims by up to 70%.

Water damage is the biggest single cause of home insurance claims, accounting for $17 billion of claims every year in the USA and UK. While Internet-of-Things(IOT)-based solutions have long promised to provide a new way to manage this risk, this new research is the first time there has been analysis based on such a large data set spanning 3 countries and deployments by 9 different insurers.

The research, conducted by Consumer Intelligence, included a customer survey of a statistically robust sample of 3,000 homeowners from the 43,000 homeowners on the LeakBot platform, representing over 56,000 device-years of data. The sample covered homeowners in the UK, US and Denmark.

LeakBot is a device that can be self-installed by homeowners, who clip it onto their mains pipe and download an app that tracks air and water temperatures. A leak draws colder water from outside, and creates a consistent drop in temperature. The customer receives an alert from LeakBot to let them know there’s an issue, and they can then access a plumbing service to find and fix the leak. This is usually all provided free of charge to the homeowner by their insurer.


The research results showed that in the UK LeakBot reduced water damage claims costs by 70%, with a 39% reduction in the frequency of claims, and a further 50% reduction in the severity of the remaining claims. The new data is an important update as it shows that the commercial return of LeakBot is twice as good as previously claimed when presenting the solution to insurance carriers.

Across the 3 countries the average reduction in water damage claims spending was 44%, which shows that the more developed UK model (where the plumbing services are fully integrated as opposed to being out-sourced to 3rd parties) is the most effective model (and is now already being deployed in the US and Denmark).

The research further showed that customers who had been given a LeakBot device from their home insurer were 37% were more likely to choose to renew with their existing insurer than before receiving the LeakBot.

The findings constitute an important update on the impact the LeakBot technology have on mitigating cost of claim to house insurers.

Craig Foster, CEO of Ondo InsurTech Plc, says: “We knew that LeakBot worked – now we know exactly how well it works. This landmark research by Consumer Intelligence is what the home insurance industry has been waiting for – hard evidence that IOT-based systems can have a dramatic effect on claims costs and consumer loyalty, and can be deployed at scale with an immediate return on investment”

Mass-market potential

The new study underlines that LeakBot has a very large addressable market. In the United States homeowners insurance water damage claims cost equate to $200 per policy. LeakBot is now proven to be able to reduce this by 70%, meaning on average LeakBot can save an insurer $140 of annual claims costs per installation – far in excess of what it will cost a carrier to provide the entire LeakBot product and service to their policyholders for free.

In March 2022, Ondo Insurtech Plc became the first InsurTech to IPO in London. Its LeakBot device is now used by 10 insurers in 5 countries,by carriers such as Direct Line Group, Hiscox, Mapfre and TopDanmark.

The independent report, “Counting the Savings: How IoT leak detection is radically reducing water damage claims”, can be downloaded from the company website.



About alastair walker 8997 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.