Q&A: Turning building data into climate action.

Across Canada, financial institutions are being asked to back up their climate targets with real numbers. But when it comes to the homes and buildings they finance, most are still relying on provincial or national averages instead of actual energy use. That kind of guesswork makes it difficult to set believable emissions targets, understand climate risk, or show progress toward net-zero commitments.

Rather than accept those limits, Vancity partnered with Canadian clean-tech firm, Climative, to test whether modeled, building-level data could serve as a reliable stand-in for verified member data, provide more refined insights, and improve the accuracy of financed emissions reporting for its residential mortgages.

In this Q&A, Mandeep Sidhu, Senior Consultant, Climate Strategy & Performance at Vancity, explains what the improved data revealed, and how a scalable, replicable approach to better building data can help financial institutions manage risk, support clients, and turn climate commitments into action. For a detailed explanation of the methodology, findings, and limitations, see Vancity’s case study, co-authored with Climative.

1) Through this partnership, Vancity improved the quality of its financed emissions reporting for residential buildings, moving from Partnership for Carbon Accounting Financials (PCAF) levels 4 and 5, to level 3. Why is this improvement so important?

In an ideal world, you’d use actual energy consumption for each building and an emissions factor for each heating source. But that would involve collecting data from thousands of owners and utilities, and you’d quickly run into inconsistent formats, limited data-sharing agreements, privacy concerns, and a massive administrative burden.

Before this pilot, our financed emissions reporting for residential mortgages relied on B.C. averages which sit around data quality levels 5 or 4 under the PCAF framework, where level 5 is the most uncertain and level 1 the most certain. With Climative’s modelling, we were able to reach level 3, which gives us a much clearer picture without needing to ask members to hand over their utility bills.

This is a big jump in data quality, and that improvement strengthens everything built on these numbers: our climate risk assessments, annual disclosures, and our ability to design more targeted engagement for members.

2) What does better property-level data allow Vancity to do for members that couldn’t be done before?

Property-level data helps us see which homes are likely driving the most energy use and where the biggest opportunities are to cut emissions and costs. It turns a one-size-fits-all message into a more tailored conversation for each member.

However, a key limitation we face is the lack of readily available heating fuel type data for properties in B.C. In its absence, the model assigns heating types according to provincial averages, which reduces the reliability of emissions estimates at the individual property level, although results remain reasonably accurate when assessed at the portfolio level.

An important lesson we learned from this pilot is that we need to prioritize efforts to obtain or collect building-specific heating fuel type data going forward. This type of data is important because a member in an older, gas-heated home will get very different advice than someone in a newer, more efficient building. That kind of personalized support helps members lower bills, improve comfort, and shrink their footprint in ways that fit their lives.

3) What’s another example of the insights you gained from the higher-quality data? How could this help lenders in the real world?

Take risk management, for example. The insights that we’ve gained through the energy and carbon assessment data will help Vancity identify high emitting buildings and see how that risk is concentrated when we segment the portfolio by different loan characteristics. That gives us a more precise view of energy transition risk and builds confidence in our disclosures and regulatory filings.

It also feeds directly into strategy, shaping how we lend so we can manage risk while still growing sustainably.

4) How do you think this data will help Vancity turn climate commitments into climate action?

It basically turns a carbon footprint into a plan. Having a reliable, property-level baseline helps us see the gap between our current emissions and where we need to be to reach net zero. It lets us model realistic pathways and build a stronger case for decarbonization.

The dataset also revealed the reduction potential across our residential portfolio – that’s where it starts to get very practical. We can use it to plan what types of retrofits and upgrades will have the biggest impact as we work toward becoming net-zero by 2040 across all our mortgages and loans.

5) Looking ahead, what needs to happen next to build on this work?

As long as actual energy use and heating fuel type data isn’t readily available for most properties, there’s only so much any organization can do on its own. The sector needs to push for policies that make relevant property-level data more accessible so lenders can design evidence-based climate strategies and report with greater transparency.

That will take collaboration between governments, regulators, property assessment agencies, utilities, and lenders. Vancity and Climative are exploring a national registry of building-level carbon and energy labels to help make that possible.

6) What piece of advice would you like to share with other financial institutions that are looking into doing this?

We know that data challenges are real, and that this can be frustrating. At Vancity, we’ve chosen to stay focused on what we can do to improve by acting on the data we have today and strengthening it over time.

Financial institutions have an enormous influence on the direction of the economy, it’s hard to imagine tackling the climate crisis without this sector playing its part. This pilot shows that achieving higher data quality in carbon reporting is both feasible and scalable, even in a complex area like residential buildings, and that it can generate actionable insights to better measure, disclose, and reduce financed emissions.