LENDERS Fuel Bill Prediction Tool

In 2017, working via the BRE, we conceived and led research that asked what seemed like an obvious question — one that, remarkably, the mortgage lending industry had never systematically addressed: should the energy performance of a home affect how much a buyer can borrow to purchase it?

The answer, we found, was clearly yes. The data to support that argument was more compelling than we had anticipated. And the tool we built to make it tangible — a fuel bill prediction calculator available to any householder — was the practical result of a year of work with a consortium of eight organisations.

The gap that nobody had filled

At the time, approximately 90% of mortgage lenders were using fuel bill data drawn from the Office for National Statistics' Family Spending Report — a dataset derived from just 4,900 UK households. That figure was used to set a notional fuel bill allowance in affordability calculations, with no reference whatsoever to the energy performance of the specific home being purchased.

In practice, this meant that a buyer purchasing a draughty, poorly insulated Victorian terrace and a buyer purchasing a modern, well-insulated home were being treated identically by their lender — despite the fact that their monthly fuel bills could differ substantially. Those real-world cost differences were invisible to the mortgage market.

If a home's energy performance affects what you pay to heat it, it should affect what a lender thinks you can afford to borrow.

What the data showed

The LENDERS project — Levering Economics for New Drivers to Energy Reduction & Sustainability — drew on analysis of 40,000 property datasets to establish robust, statistically reliable links between Energy Performance Certificate ratings and actual household fuel costs. The findings were striking.

The monthly fuel bill savings available in a more energy-efficient home — the equivalent of two EPC bands — could translate into around £4,000 of additional mortgage finance, if lenders incorporated that efficiency into their affordability assessments. The implication was clear: the mortgage market could become a significant driver of energy improvement, not just a passive bystander.

The prediction tool

Alongside the research, the consortium developed a working fuel bill prediction calculator, available at www.epcmortgage.org.uk. The tool allows anyone — homebuyer, landlord, or adviser — to enter a small amount of property information and receive a reliable estimate of likely annual and monthly fuel costs, based on EPC band and household type.

The intention was to give the mortgage industry a free, accessible tool they could use to improve the accuracy of affordability calculations — and to give homebuyers a clear, comprehensible way to understand the financial implications of a home's energy performance before they committed to purchasing it.

The consortium

The project was funded by Innovate UK and brought together a consortium of organisations from across the housing and finance sectors.

Building on a 2015 UKGBC–UCL Energy Institute report that had established the conceptual case, LENDERS was designed to produce the large-scale quantitative evidence that the mortgage industry would need to act — and to demonstrate, through a working tool, that the practical implementation was achievable.

Why it still matters

With approximately £127 billion of mortgage lending occurring every year in the UK, the mortgage process represents one of the most powerful potential levers for influencing the energy performance of our existing housing stock. At the moment of purchase — when a buyer is most attuned to the financial details of a home — is precisely the moment at which energy performance could be made most vivid and most consequential.

The project envisaged a virtuous circle: buyers able to borrow more for efficient homes, creating a premium for energy performance in the market, which in turn incentivises sellers and landlords to invest in improvement. That circle has not yet fully closed, but the evidence and the tools to support it exist. The argument was made in 2017. It remains valid today.