Latest / Fintech Conversations with Fexingo: Banking, Payments, and Financial Software Companies / How Digital Twins Are Transforming Commercial Real Estate Lending
Transcript
- Lucas: The commercial real estate market in September twenty twenty-six is still wrestling with a massive valuation gap. Lenders are hesitant because they can’t see inside buildings anymore, and appraisers are stuck using data that’s six months old at best. But there’s a quiet shift happening where fintechs are starting to use digital twins to bridge that void. Luna: You mean like a live, virtual replica of the physical structure? That sounds expensive to build out for every single property. Lucas: It used to be, yeah. The cost of scanning a whole office tower used to run into the tens of thousands. But now, with lidar getting cheaper and ai modeling more efficient, you can spin up a basic twin for a mid-sized commercial building for just a few thousand dollars. And the data flowing into it is continuous. Luna: So instead of waiting for an annual audit, the lender gets a live feed of how the building is actually performing? Lucas: Exactly. Think about it from a risk perspective. If I’m lending five hundred million dollars on a Class A office building, I don’t just want to know its square footage. I want to know if the hvac system is failing, if energy costs are spiking, or if occupancy is dropping in real time. A digital twin gives me all three. Luna: That’s way more granular than what we usually see in CRE loans. How do they even get that data without tearing walls open? Lucas: They’re tapping into the existing iot infrastructure. Most modern commercial buildings already have sensors tracking temperature, humidity, foot traffic, and power draw. The fintech platform aggregates that noise, filters it, and maps it onto the 3d model. So the twin isn’t just a visual; it’s a dashboard of operational health. Luna: And does that actually change the terms of the loan? Or is it just a nicer way to check boxes? Lucas: It changes the terms significantly. We’re seeing early movers offer lower interest rates for properties that maintain high efficiency scores in their digital twin. If the building proves it’s using less energy and staying comfortable for tenants, the lender sees lower risk. Lower risk means better pricing for the borrower. Luna: So it’s basically green finance, but powered by data instead of just paper certifications? Lucas: Precisely. Certifications like leed are static. You get them once, and then you hope you keep meeting the standard. With a digital twin, the verification is ongoing. If your energy usage spikes next month, the lender knows immediately. It turns sustainability from a marketing point into a financial metric. Luna: I love that. It forces accountability. But who’s actually building these twins? Is it the big banks doing it themselves? Lucas: Mostly it’s specialized prop-tech startups partnering with the lenders. Companies like buildingai and various climate-risk platforms are leading the charge. They handle the heavy lifting of data integration, while banks like jpmorgan and goldman sachs provide the capital and the distribution network. It’s a classic symbiosis. Luna: Does this work for older buildings too, or is it only useful for shiny new constructions? Lucas: That’s the interesting part. Older buildings are actually where the biggest upside is. They tend to have higher operating costs and more hidden risks. If a digital twin can prove that a retrofit has improved efficiency, the value proposition is huge. For a new building, everyone assumes it’s efficient. For an old one, you need proof. Luna: Proof that doesn’t require hiring a team of inspectors to walk around with clipboards. Lucas: Right. No more subjective judgments. It’s pure telemetry. And that reduces friction in the underwriting process. What used to take weeks of due diligence can now be partially automated. The lender sees the data stream, runs the model, and gets a clearer picture of the asset’s true cash flow potential. Luna: But what happens if the data shows the building is deteriorating? Does the loan get called? Lucas: Not necessarily called, but it triggers alerts. The lender might require specific maintenance interventions before allowing further draws or refinancing. It becomes a proactive management tool rather than a punitive measure. It’s about preserving the asset value over time, not just assessing it at closing. Luna: That makes sense. It aligns the incentives. The lender wants the building to succeed, so they help monitor it. Lucas: Exactly. And this creates a feedback loop. Property owners start optimizing their operations not just for comfort, but for their loan covenants. They know that keeping the digital twin healthy keeps their borrowing costs low. It’s a powerful behavioral nudge toward better building management. Luna: Do you think this will become standard for all commercial loans within the next five years? Lucas: I think it’ll become standard for anything above a certain size threshold. Small retail spaces probably won’t justify the setup cost. But for office towers, logistics centers, and mixed-use developments, it’s going to be the norm. The data is too valuable to ignore. Luna: And the lenders who don’t adopt it will just look outdated. Like they’re still using fax machines. Lucas: Pretty much. In a market this tight, being able to say 'we have real-time visibility into your collateral' is a competitive advantage. It builds trust. Borrowers know the lender understands their business, which makes negotiations smoother. Luna: It also reduces information asymmetry. Usually, the property owner knows more about the building than the bank does. This flips that dynamic. Lucas: It levels the playing field. Now both parties are looking at the same data. Disputes over valuation drop dramatically when you’re both staring at the same live metrics. It’s harder to argue about what a building is worth when you can watch it operate day by day. Luna: Are there any privacy concerns with all this sensor data? Tenants might not want their movement tracked. Lucas: Valid concern. But most systems aggregate data to the floor or zone level, not individual desks. It’s about heat maps and occupancy rates, not surveillance. The focus is on operational efficiency, not employee monitoring. Reputable providers are very clear about that boundary. Luna: Good to hear. Because if this feels like panopticon finance, nobody’s going to sign up for it. Lucas: Agreed. Transparency is key. The benefit has to outweigh the perceived intrusion. And since the benefit is lower interest rates and better building conditions, most owners are happy to trade anonymized data for those savings. Luna: It’s a fair trade. Data for dollars. Seems like a solid deal for everyone involved. Lucas: For now, yes. As the technology matures, we’ll probably see even more sophisticated applications. Predictive maintenance, automated insurance claims based on damage detection, maybe even tokenized ownership stakes tied to real-time performance. The possibilities are expanding fast. Luna: Tokenized performance sounds like a mouthful, but I get the concept. Shareholders getting dividends based on actual building output? Lucas: Exactly. Imagine investing in a building through an etf, and your returns are directly linked to how efficiently that building operates. It would make real estate feel more like a tech stock. Highly liquid, data-driven, and responsive to daily changes. Luna: That would definitely attract a younger investor base. People used to thinking of real estate as slow and opaque. Lucas: It democratizes access. You don’t need millions to buy a whole building anymore if you can buy shares in its performance. And the digital twin ensures that performance is visible and verifiable. It’s a huge shift in how we perceive physical assets. Luna: One last question. Do you think traditional appraisal firms will survive this, or will they get disrupted out of the picture? Lucas: They’ll evolve. Appraisers aren’t disappearing, but their role is shifting from sole determiner of value to validator of data streams. They’ll oversee the models, ensure compliance, and add context that algorithms miss. It’s a partnership, not a replacement. Luna: A hybrid model. Humans plus machines. Sounds like the future of almost every industry right now. Lucas: It really is. Whether it’s healthcare, automotive, or real estate, the pattern is the same. Data richness drives better decisions. And those who harness it first gain a significant edge. Luna: So if you’re running a commercial property today, maybe it’s time to look into those sensors. Lucas: Definitely. Your building is generating data whether you use it or not. Might as well put it to work for your bottom line. Luna: If these conversations are useful for what you're building or running, the way these stay ad-free is listener support — buy me a coffee dot com slash fexingo. Lucas: Yeah, and it helps us keep digging into these niche corners of finance. Every bit of support goes straight into keeping the show independent and focused on the details that matter. Luna: Thanks for helping us keep this going. It really makes a difference. Lucas: As we wrap up, I’m curious if you’ve noticed any changes in how your own workplace or local businesses are handling efficiency lately. Are you seeing more smart buildings around you, or is it still mostly theoretical?