UK's first property-level cladding dataset launches

Insurtech firm teams up with RICS surveyors to create the dataset

UK's first property-level cladding dataset launches

A new cladding dataset has been developed with the help of over 600 property surveyors to provide property-level cladding details on tall buildings.

Insurtech firm WhenFresh said it has launched its cladding dataset – a result of a major project started in 2020, initially involving a wide range of remote inspection tools and data sources such as satellite imagery, drone footage, and building and planning records, among others.

This was subsequently enhanced on an ongoing basis by physical surveys and other inputs, all examined by a group of over 600 qualified surveyors from the Royal Institution of Chartered Surveyors (RICS).

Following six months of in-market testing with a group of existing clients, WhenFresh has launched the unique dataset to the wider market, providing property-level cladding data for each of the 485,234 properties within multi-dwelling units (MDUs) of 18 metres or more in height throughout the UK.

The surveyor team used its expertise to assign each property within these MDUs to one of three categories:

  • Green - building has no cladding, EWS1 form recorded in Cladding Database with classification A1, A2, or B1, or considered to be out of scope as per RICS’ Cladding Guidance Note
  • Amber - building potentially has cladding, merits EWS1 inspection and identified as potentially in scope, as per the RICS’ Cladding Guidance Note, no EWS1 form held currently
  • Red - building has cladding, EWS1 form recorded in Cladding Database with classification A3 or B2, or other known adverse factors from alternative sources

This means that mortgage lenders, insurers, local authorities, central government, housing associations, asset managers, and other parties are now able to readily access this cladding data, alongside any other property data attributes they may need from WhenFresh in real time.

Since the Grenfell fire in June 2017 and the cladding crisis that has since developed, owners, mortgage lenders, insurers, and developers of properties in tall MDUs throughout the UK with some form of cladding have found themselves facing massive, unforeseen financial exposure.

While key property risk factors such as flood and subsidence have routinely been assessed when deciding whether to offer mortgages or how to price insurance premiums, cladding simply wasn’t something that anyone considered. This is why little or no information about cladded buildings had been captured before WhenFresh’s cladding dataset project.

“We’re delighted to be able to bring this cladding dataset to market, alongside our existing property data assets, not least as it provides key risk insights into these 485,234 properties which are jointly worth in excess of £50 billion,” Mark Cunningham (pictured), co-founder and chief executive at WhenFresh, said.

“There are obvious applications for mortgage lenders and insurers of course, but we’re already seeing interest from local authorities, central government, housing associations, asset managers, and other sectors too.”

Cunningham added that the new dataset provides lenders with the means to fully understand how their mortgage books are affected by cladding issues, down to individual property level, so they can identify where risks lie and make better decisions moving forward.

“New mortgage applications can also be pre-screened against this cladding dataset,” he said. “It has now become a key component of our WRAP service, where a wide range of data variables are applied to packages of mortgages being prepared for securitisation, to give surety to the buy-side.”  

Max Griffiths, group head of quantitative risk at Together Money, said that WhenFresh’s wall cladding dataset enabled Together to assess their limited exposure to external wall cladding risk across the full book.

“Working with the WhenFresh analytics team has enabled us to establish a clear set of actionable data points that support our prudent approach to lending, and their data enrichment has helped us in preparing data for securitisation issuances where additional reporting requirements around ESG has been required,” he said.

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