Global Head of Real Estate Applied Research, MSCI
GRI Club Interviews: Will Robson - “Lenders with rescue capital are looking at the data” | EN 🌐
Will Robson, Global Head of Real Estate Solutions Research at MSCI, discusses the power of data in managing real estate debt strategies in an exclusive interview during Europe GRI 2024.
🔗 Find out more about GRI Club Europe and join the club to network with the industry’s most senior players: https://www.griclub.org/club/real-est...
About Will Robson
Will Robson, Global Head of Real Estate Solutions Research at MSCI, discussed the firm's recent launch of a real estate debt fund index in a February 2025 interview. He stated that the index helps to "institutionalize" real estate debt and predicted continued growth in debt flowing through alternative lending routes. Robson noted that lenders and equity investors providing "rescue capital" are using MSCI's loan-level data to identify distressed assets, particularly in markets such as U.S. CBD offices that have seen significant price corrections. In earlier appearances, Robson addressed the use of data in multi-asset-class portfolios. In a 2022 interview, he argued that investors often rely on proxy data for private infrastructure, which can lead to "sub-optimal allocations" by misrepresenting correlations and volatilities. In a 2021 presentation on climate risk, Robson distinguished between backward-looking carbon footprinting and forward-looking measures like climate value at risk, which he described as assessing the potential financial implications of future climate hazards on portfolios.
Transcript (14 segments)
W
Will Robson0:07
I'm Will Robson, I'm Global Head of Solutions Research for Real Assets at MSCI. Me and my team write research about what's going on in markets and help clients solve their investment problems using our data and tools.
Real estate debt is an area that MSCI hasn't been tracking too deeply for too long, but we've seen a lot of our clients—we've been measuring their real estate equity portfolios for a very long time—and more and more of those guys are investing in real estate debt funds. So we recently launched a real estate debt fund just a couple of months ago, and it's been really interesting how much demand there has been from that.
I think capital has been allocated over the last few years really to real estate debt. It's become a bigger and bigger part of people's portfolios, but it's still quite a niche area from an asset allocation point of view. And I think bringing this index to the market helps to institutionalize it. I think we'll continue to see a lot more debt flowing through these alternative routes to real estate lending.
Because of the market conditions, real estate debt's become even more attractive given the equity position. But we get to that stage in the market where we're seeing equity markets start to kind of rebound, and maybe it becomes a more balanced allocation.
A lot of capital has been flowing through to private real estate debt funds, and so it's an index that we've created of debt funds in UK and Europe, measuring their total returns at the fund level. It's useful for any players in the market just understanding how real estate debt fund returns compare to private equity real estate returns.
It helps allocators understand the risk-return characteristics of real estate debt versus equity, but it also helps the managers make a much better presentation to those investors about how their fund is performing compared to their peers. It's been available—this kind of tool has been available for real estate equity investors for 40 years or so, and now it's available to real estate debt investors.
There's a lot of talk about kind of a debt maturity wall. There's lots of legacy assets that have been funded a number of years ago. There's obviously been price corrections across lots of asset classes, lots of countries. The vast majority of assets have seen some kind of price correction, but it's not been significant enough for a lot of assets to cause any issues.
But there are definitely lots of assets where that is a significant issue. Some of the CBD offices in America in particular have seen very significant price falls. I think it's really important to look through the details of the data to find exactly what kind of assets, in which locations, from which lenders, where the problems exist.
And that's what our Mortgage Debt Intelligence solution does. It's a loan-by-loan dataset with the lenders, the borrowers, the rate, where it was lent, when it was lent—all that information is searchable. So you can really hone in on markets where the expected LTVs today are going to be in kind of distressed levels.
I think we're finding that lenders and equity investors that are looking to provide rescue capital to some of these opportunities are looking at that dataset to find out where those issues are. So there's lots of generalizations made in this market, but I think it's more important to look into the details of the data and really find the true picture.
MSCI uses AI across all sorts of different use cases across all the asset classes. I think real estate is an opaque market where data itself is private and it's hard to come by. It's also quite often buried in documentation, and it's very cumbersome and time-consuming to get a hold of that information.
So the main area we've been using it so far is in extracting data from various documentation, making that process much more efficient, allowing us to get more of that data, and then feed it into signals and market insights. Also helping us find patterns in the data as well. So it's an area of growth we're putting a lot more resources and attention to, and it will kind of grow and grow from here on.
There's a lot of talk about AI and everyone's using it. I think we're using it in kind of very concrete areas to help with the data collection side of things first. We're using it to help summarize what the data says, because in private classes like real estate or private equity, it's the data itself that is the valuable thing, and just getting those insights across the market.
I think the danger is to overuse AI. Sometimes it's kind of like a hammer looking for a nail. You've got to really think about the use cases that are very important to use AI, and so we've been very selective about where we use it for the right reasons.