Giacomo Mariotti
20.01.2022
5 min read
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How Tractable's Property Estimator can help homeowners rebuild faster
Today, when a home is damaged, homeowners face an obstacle before recovery can begin: how long it takes for an insurance claim to settle.
This is especially true when the damage has been caused by an event that impacts a lot of people at the same time, like a storm, hurricane or flood – all, unfortunately, more and more prevalent due to the impact of climate change.
When such events strike, assessors may have hundreds or even thousands of houses to evaluate at once, and the weather conditions may have made them hard to reach. That means it can be impossible for an evaluator to get to the properties affected to evaluate the damage – a critical step towards ultimately unlocking the funds needed to fix it.
Introducing Property Estimator
That’s why we introduced Property Estimator, a solution that allows policyholders to gather the necessary information themselves through their smartphone. After damage occurs, a homeowner’s insurer will send them a link to a web app, via which they can take photos of the impact. In a few minutes, Tractable’s AI creates a full repair estimate, accelerating claim resolution remotely.
This might sound too good to be true, but Property Estimator is currently being used live in Japan, on real natural disasters, such as October 2021’s Typhoon Mindulle. Previously, the “cycle time” from claim to settlement during a natural disaster was typically between 20 to 50 days. Our solution has reduced this to often as fast as a single day – and our record was three hours. In the US, where we’ve recently launched the product, the time to settlement is normally a few weeks: we’re hoping to get it down to a day.
Expanding our AI platform
Our property product builds on the back of our successful automotive offering, which has been in use by major insurers around the globe for seven years. For both insurers and customers, using AI to accelerate property claims is compelling. When a storm or a hurricane hits, the number of claims spikes, creating bottlenecks that are impossible to overcome by relying solely on on-site inspections.
Lifting the lid on our tech
However, the challenge is also more complex. While cars are relatively uniform – and some models are widely used around the world – houses don’t come in set models or specific dimensions. So how does the technology work?
We started by breaking down the questions the AI has to answer so they become quite narrow. We might ask what material a damaged object is made of, what its dimensions are, and whether the damage can be repaired. Once we have extracted this information, we can use expert rules that we’ve developed to bring everything together in a cost estimate.
For example, with a damaged window, AI Property would extract the dimensions, the glass type and frame material from the image. Then after analysing the image and comparing it to others in its database, as well as local pricing guidelines and standards, it would say, “This is repairable: and for this damage, we need these materials and one person working for a half a day. In this region, it will cost X.” The claim is then approved and paid.
Widespread benefits
The reduction in cycle time is the most obvious benefit. But the overall processing cost is lower too. The estimate is more reliable and consistent (as contractor quotes for jobs may vary). Companies can better manage large numbers of assessors for short bursts of work and, by having AI deal with the bulk of claims, specialist staff are freed up to deal with more complex ones where they can make the biggest difference.
All this feeds through to savings for customers but perhaps most importantly, it means customers are happier. They have a better, less stressful experience during what can be a very difficult and upsetting time.