Closing a chasm of missing EPC data for the mortgage book: Just Group

Just Group is a lender with ambitious climate targets. By 2030 it has pledged to reduce emissions by 50% (including those generated from its £24bn+ investment portfolio), and to be net zero by 2050.

These targets give the company a huge emissions reduction task – especially in terms of financed emissions from their later life mortgage lending portfolio, which they knew would be responsible for a large proportion of the company’s overall emissions.

The challenge: Missing EPC data for 63% of the mortgage book

Unfortunately the team at Just Group found they had gaps in their insight: when they attempted to measure the extent of financed emissions from their mortgage book, they found that they were missing emissions data for the majority of the book.

Of the 51,000 loans in the mortgage book only 19,000 had a valid EPC. That left a huge 63% of the portfolio with missing EPCs and emissions data.

Missing EPC data is a problem for all lenders, but especially so for later life lenders like Just Group where many customers have owned their home for a long time and so have not needed an EPC.

The solution: Predictive EPC modelling by Kamma

Just Group partnered with Kamma to model the missing EPC data for their mortgage book.

Kamma’s unique approach combines geospatial analysis with machine learning to predict EPCs with one of the highest levels of accuracy on the market.

We were able to predict the EPC rating for all of the 32,000 missing properties in Just Group’s mortgage book – successfully closing data blind spots.

For 80% of those properties the EPC was found to be modelled to the correct EPC band. On top of this, a further 19% of properties were found to be off by only one EPC band.  

Besides the lack of valid EPCs, it’s also well-known that EPC data is unreliable as a measure of property emissions where it does exist, especially due to the outdated carbon intensity factors used within the methodology. 

Using Kamma’s enhanced dataset we were able to significantly improve the accuracy of financed emissions calculations – achieving a much improved PCAF score of 3.58, on par with even the largest high street lenders.

“We’ve achieved some great results working with the team at Kamma. We’ve been able to enhance our approach to emissions data and develop a much more accurate picture of the emissions from our lifetime mortgage portfolio.”

Tom Kenny

Group Property and Credit Risk Director

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Planning for the future: the path to decarbonisation

Alongside a robust baseline, we also modelled the decarbonisation pathway for Just Group’s mortgage book to 2030, a unique capability offered in the market. This enabled an understanding of whether Just was projected to achieve the 50% emission reduction target by 2030 if their current pace of emissions reduction continued. 

The key finding was that there is a 9% gap between the pace of decarbonisation needed to hit the target and the current pace. Gaining clarity on this has galvanised the wider team to develop new actions and propositions to ensure progress stays on track.

“Working with Kamma is all about confidence. Confidence in the Kamma team, confidence in the data and analysis they provide, and confidence that we’re on the right track with our emissions calculations and plans for reducing those emissions.”

Tom Kenny

Group Property and Credit Risk Director