FloodFlash: How Tech-enabled Flood Insurers are Building More Resilient Businesses
Annual losses from UK flooding are estimated to be in the region of £500 million, with huge amounts of uninsured loss every year. “Parametric” or “event-based” insurance is one potential solution to this insurance gap. Unlike traditional indemnity insurance, parametric insurance policy holders pay an agreed premium and receive a pre-agreed payout when flood water reaches a pre-agreed depth. Policy holders know when their policy will pay out and exactly how much. What’s more, insurance underwriters have less uncertainty around the payout costs they incur if an event does happen – a win-win for the industry.
Making Flood Cover Available at Scale
Until now, this type of insurance was only available for multinational corporations and governments. Policies were designed to pay out hundreds of millions of dollars and were backed by small numbers of expensive measuring stations. True to its name, parametric insurance requires measurement of a parameter (e.g. flood depth), which requires data. When an event happens, it’s crucial to have a reliable source for this data. Using affordable IoT technology and platforms like AWS, FloodFlash is the first company to offer parametric flood insurance to small businesses.
When a customer buys a FloodFlash insurance policy, an engineer is sent to install a sensor at the covered property. It continuously monitors water depth and alerts us if there is a flood event that looks like it might trigger their insurance policy.
Each flood sensor has the AWS IoT Device SDK installed, and periodically opens a secure connection to the AWS IoT Core platform. Temporal water depth data is uploaded, and the integrations between IoT Core and other AWS services allow for seamless data processing. IoT Core allows the use a ‘rule’ that passes data to an SNS topic which can broadcast the data to multiple subscribers:
· One of these subscribers is a Lambda function that saves the raw data to S3. This enables FloodFlash to replay a stream of water depth measurement events if necessary (to another data store, for testing etc.)
· Another subscriber to the SNS topic is to send alerts to various teams at FloodFlash – who can get in touch with the customer to ensure they’re safe in the event of a flood, and begin to monitor the flood event as it develops.
· Finally, an SQS queue receives the data and funnels it to another Lambda function to be processed, analyzed and stored.
As the temporal water depth data is passed to a Lambda function, it is removed from the queue and sent into an auto-scaling set of time-series databases. From here the data can analyzed by FloodFlash’ data science or claims teams.
This architecture is almost all serverless: meaning that it’s extremely cost effective when compared to a solution comprised of traditional web servers. It’s also much more robust; if there’s a large-scale flood event that triggers many sensors, the Lamdba functions and queues ensure that the platform can scale to handle the increase in data seamlessly.
By using AWS FloodFlash have saved time and resources. Instead of building bespoke IoT capabilities they can concentrate on providing rapid-payout flood insurance to business owners across the UK. For more information, visit floodflash.co or email email@example.com.