Commercial Real Estate Credit Investing

Tingting Zhang:

Thanks Elana for having me.

Elana Margulies-Snyderman:

Absolutely, Tingting. So to kick off the conversation, tell us a little about TerraCotta and how you got to where you are today.

Tingting Zhang:

Sure. TerraCotta is a middle-market-focused private credit shop. We specialize in commercial real estate, including multifamily assets and credit across the spectrum from direct lending to distressed.

Elana Margulies-Snyderman:

Great. And given your focus on commercial real estate credit investing, I would love to hear your high-level outlook for the space.

Tingting Zhang:

While this is a fascinating space [inaudible 00:01:12] the great financial crisis, banks have been retreating from lending. So a lot of private funds get in, and private credit really became an institutional asset class since the great financial crisis. And we continue to go through various cycles. So the industry gets stressed and grow. For instance, this is a first meaningful distress since the onset of the private credit investment as an institutional asset class. So the assets are growing and institutional investors becoming more sophisticated, understanding this investment asset class, how it performs during good times, how it performs in distressed times, and understanding a variety of specialty credit as well. We're in the real estate credit and you have a corporate mezzanine credit. So the whole area is becoming more robust, is growing. The understanding of the behavior of asset class is becoming more nuanced and more sophisticated.

Elana Margulies-Snyderman:

Tingting, with AI being such a hot topic, I would love to hear how TerraCotta is integrating it into the firm's investment decisions.

Tingting Zhang:

Yes. So since the get-go, we always felt that the real estate credit investment business can be more scientific, more data-driven, more evidence-based. So over the last 20 years, we have built a very large data warehouse and the transition from classical regression models to machine learning to AI algorithms, are very natural for us because that's our footprint from the get-go as a quant shop. And over the last 20 years, the data doubled every year and the computing algorithms have becoming more robust, more sophisticated, and more deep-probing. So along the process that we are adopting the newest algorithms to trying to figure out the real world. So in what we do in real estate credit investment, a big part of it is to track the macro market. So there are 200 variables that we consider as relevant to the performance of real estate assets, and they include variables reflecting demographic, economic and secular trends. For instance, if you move, you have to tell USPS where you move to. So this change of address at the macro level give us a view as to where people are moving towards and where people are moving out of. So locales with the population joined rarely perform as well in the real estate asset class and locales that have attracted a lot of population inward migration usually do better. So that's an example that we track the macro level. And in what we do a lot is about locational variables. If we look at a multifamily asset in the given neighborhood, we want to understand from a renter's point of view, is this neighborhood livable? Can you walk to your grocery store? Can you have access to medical care? Do you have drug stores? So those parts of reality, they're actually very complicated mathematically. So we use a modern algorithm to capture the essence of locational variables and introduce them in our evaluation analysis.

Elana Margulies-Snyderman:

Tingting, as a follow-up, what are some of the greatest opportunities you see in your space and why?

Tingting Zhang:

I think the greatest opportunity is in the middle market. Banks continue to retreat. Within the bank industry, very large banks have a more variety of business lines, whereas in the middle market, commercial banks and community banks oftentimes have a much more focus on CRE credit. With Basel IV and its potential implementation, it is becoming more and more challenging for a regional or community banks to be solely focused on making commercial real estate loans. So as a result, we see banks further retreat from the space, and it so happens that middle market commercial real estate credit is a smaller supply of talented fund managers. So we see that this is really both the great opportunity to grow as a private credit investor and the most challenging space to operate in as well.

Elana Margulies-Snyderman:

Tingting, on the other hand, what are some of the greatest challenges you face in your space and why?

Tingting Zhang:

I think the challenges in the middle market is one is it is fragmented. So because of the fragmentation from a dual-sourcing point of view, from how to underwrite the asset more efficiently, all the way to how do you continue to have a robust business flow, continue to book loans, to book assets without being spoiled by the spoilers? And so these are areas we have really known data to create solutions for our investors.

Elana Margulies-Snyderman:

Tingting, to shift gears a bit, being a woman money manager in the industry obviously stands out. Love to hear your thoughts about this and what you're in doing to inspire others.

Tingting Zhang:

I appreciate the question. I usually don't think too much about it, and it has been for me all about substance. But looking back at my journey in the last 20 years, I feel that obviously there's certain barriers that we have to overcome on daily basis, but if we just focus on the substance of the ability to solve complex problems in the investment world, over time we would be able to take on more responsibilities and do better things. We have a number of the women colleagues, the younger women professionals in the office, and so I feel that since I've gone through the journey, I feel that oftentimes I make an emphasis to them that everything can be overcome. We just need to pay attention to substance and our own growth.

Elana Margulies-Snyderman:

Tingting, we've covered a lot of ground and want to see if you have any final thoughts you would like to share with us.

Tingting Zhang:

Well, we're excited about the growth of the private credit market in real estate in particular, and we're excited about the large data platform we've built over the last 20 years. We look forward to making real estate credit approval real-time, not a hundred percent of the situations, but a fair percentage of the situations. I believe real estate credit could be [inaudible 00:07:56] in real time. So we're excited to rolling out the capacity in the coming years.

Elana Margulies-Snyderman:

Tingting, I want to thank you so much for sharing your perspective with our listeners.

Tingting Zhang:

Thank you for having me.

Elana Margulies-Snyderman:

And thank you for listening to the EisnerAmper podcast series. Visit eisnerampere.com for more information on this and a host of other topics. And join us for our next EisnerAmper podcast, when we get down to business.  

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