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Industry leaders debate how-tos of standardizing Real Estate.

We all know the ABCs of real estate classification, but if some of the players in the industry have their way, valuing real estate assets in the future may be akin to rating bonds. That was the topic of discussion during a seminar at the Spring ULI meeting sponsored by Ernst & Young Kenneth Leventhal Real Estate Group called "Information Technology And The New Real Estate Paradigm."

Michael Evans: Real estate appears to be discovering technology, and I think it was one of the last industries to do so. And for the most part, real estate has been the dinosaur. Wall Street has had a very difficult time with real estate; they've gone through various phases, they tried to approach real estate as a commodity. And I think a great deal of difficulty revolves around the lack of information, the ability to have comparable data and technology.

Where do we see Wall Street today in terms of real estate? How successful are they in turning real estate into a commodity? And what role will technology play in the future in that? Will there be an acceleration of commoditizing real estate?

Randall Zisler: Well, first of all, there's different kinds of technology. There's information handling technology, and there's also financial technology. A lot of the technology that we use today in creating commercial mortgage backed securities is financial theory and concepts and algorithms that were created in the late-1970s and refined during the securitization of residential mortgages during the '80s.

In addition to that kind of technology, specifically options, pricing theory and things of that order, there is also what I call the institutional technology that has made the securitization of commercial mortgages possible. That institutional technology, again, was created by the securitization of residential mortgages, the existence of governmental programs and housing, and mortgage origination. And lately, the Resolution Trust Corporation, which had the awesome task of dealing with the walking dead, the excessive property in the United States, and the writing of these properties down to a point where the public markets would infuse capital into the industry.

Evans: David, how do you really get down to the core of real estate in terms of looking at one building versus another, or the real estate securitizing a loan? And does the market say all securitized loans are the same when you take them out to a pool?

David Henry: Well, clearly, the trend towards making real estate loans a standardized product, or a commodity, is there, and tremendous strides have been made to make it so. The challenge for the industry in technology is to make the more complicated underwriting processes and commercial real estate types more of a standardized product, such as single family loans. And I think a lot of strides have been made there, but it's very difficult for technology to substitute for the underwriting process in many types of lending

In terms of technology, asset management and loan servicing, I think we're there. There's no way you can service a portfolio, for instance, as large as ours, about $15 billion, without using very sophisticated forms of asset management and loan servicing.

William Wendt: Interestingly, within the industry in general of real estate, the comparison is between investors and portfolio managers who came out of a stock and bond mentality who are used to the level of information, the instantaneous information, and the level of sophistication, and marrying that with real estate professionals who actually go out and make the deals.

You have pricing models in terms of bonds. You have quality ratings. And there's a discipline to that because there's been statistical analysis. In real estate we still don't have a lot of that. While I was at Travelers we did a lot of work in terms of mortgage quality ratings, and we actually had developed some pricing models. But you talk to a real estate person who's a deal maker, and the concept of pricing mortgages individually based upon lease information input from a model, not a final decision maker, is still relatively foreign to them.

Henry: And don't you think part of that's because there's so many more variables in pricing a real estate loan and assessing the risk of a complicated commercial real estate piece of property than there is a bond?

Wendt: There are more variables. A lot of people, for instance, in commercial real estate, and in the institutions particularly, have tried to come up with quality ratings, including rating agencies. And they will contain within them 15 to 20 factors, and then they will try to quantify those and come out with a quality rating.

Anyone who has studied first year statistics in college knows that when you apply regression analysis, those 20 factors come down to five or six that are really significant. And that's exactly what we had done when I was at Travelers, and are continuing to do this now as a private company.

Dean Schwanke: You hear a lot about the technology, but how can technology help us deliver better quality information?

Sandy Apgar: The most objective way, short of a true transaction-based exchange mechanism, which we do not have in this country, is to ask the users themselves who actually are paying, how much they're paying and by extension examine their leases.

And in the Real Estate Scope system, Dun & Bradstreet, through its credit information reporters and our staff, are developing a proxy for effective rent, sourced from the users themselves rather than from the intermediaries or owners of the space. It's still a proxy, but it's the closest realtime definitive standard that we've been able to identify and systematize on a large scale across metropolitan areas and further.

Evans: Sandy, a big piece of that is a standardization of data, a standardization of measurements. I think at least the pension funds have been more reluctant to be in real estate because there's not a standardization of information. Now, there are different initiatives for standardization of studies, but isn't that the major problem why pensions aren't going into real estate full time now on a direct investment basis?

Apgar: Without question. And Bill Wendt and others have been pioneers in the science of standardization, if you will, of taking these metrics forward.

There's an interesting contradiction though, or perhaps irony, in the fact that the pension funds and insurance companies, as investors, demand a very high degree of refinement in data, but those on the other side of the table don't have even the crudest measures to use.

We've found, in addressing the user market, that simple definitions across large databases are far more important in standardizing the decision, the information and decision process, than a high degree of refinement in only a narrow range of data elements.

Evans: Randy, you were shaking your head no initially.

Zisler: Well, let's say that we had not had history's greatest real estate depression in the last five years. I would argue that the pension attitude toward real estate would be substantively different, number one.

I would even argue that looking at an office building and trying to evaluate it, even on a lease-by-lease basis, is a lot more transparent and a lot easier than trying to value all the pieces of General Motors.

Evans: Mitch, to what extent will an on-line service that could act as a trading desk solve some of those problems? Is there going to be a national network of trading of commercial real estate?

Mitch Schoch: I think that a national network is not a solution; it's a conduit upon which a solution can occur. I reiterate the point that I think it's the expectation that's created that's going to drive a lot of that into the real estate market, and also the proliferation and the technology that's enabled that.

The data is there; the fact is that it's not assessible quickly, it's not analyzable quickly, and it's not in a format in which it can be shown around so that quick decisions can be made. The industry will need to come together to simplify that process so that it can be reduced to a letter, a number, whether it's a BAA, or a one through five, or whatever. And then we'll have to have buy-in and support of those that are actually making markets in those instruments.

Hessam Nadji: To pick up on that -- I think Mitch hit everything right on the head. And just a constant standardization of information on a macro basis is hard enough as it is. I mean, we have sources of information today, right now as we speak, Black's, Grubb & Ellis, CB Commercial, Cushman & Wakefield, on and on. They're examples of major, major players in tracking property and other information. And we each try to have our own standards of the way we do it, which is different from the other form. So any user and distributor and analyzer of that information, such as Teleres, or anybody else, spend a lot of time picking which one to go with.

Zisler: Without standards you can't have securitization. And there's a lot of data out there -- I make a distinction between data and information. Information helps you make decisions, data don't. And on that issue, over the last 10 years there's been a proliferation of databases dealing with construction starts, vacancy rates, demographic -- variables of various kinds. The use of this has actually led to some pretty humorous exercises such as the top 10 cities to invest in and the top 10 cities to avoid.

The public markets will force an entirely different discipline, and this discipline will shape the kind of data we collect and the information that is extracted from the data.

When the Street does an underwriting, the Street looks at risk. Risk that it can price it feels comfortable with. If it can't price the risk, it doesn't do it.

Evans: Mike Bell, this sounds like a role Dun & Bradstreet should be playing in terms of real estate. Where do you see Dun & Bradstreet going?

Michael Bell: We're working with Sandy in marrying our business information capabilities with Sandy's knowledge and intellectual capital, and the analysis of the users of real estate. We have over 10 million enterprises in our databases. And much of the information that describes a business use of real estate is in our database -- the rents, the term, space used and so forth.

So we see a very significant opportunity frankly to bring our credit rating capability to the whole issue of upgrading the users side of the real estate equation, and by inference providing tremendous insight for the intermediaries, the developers, investors, brokers, who can begin to see now information over a very, very broad tenant population in terms of use, cost, space, metrics, etc.

Richard Mead: I began by saying that we're a publishing company. We actually then discovered that we have a database of some 50,000 office parks and industrial buildings across the country of which we track something over a hundred fields of data. And that's static data as well as availability and so on. And we see, our very humble role in all of this, in trying to help the brokerage firms and others with the grunt work of collecting data across the country, and allowing, as Hessam says, them to focus on doing the cleve things with the information and leaving us to the detail work.

Evans: Mark, as an owner and developer of real estate, are you willing to give these guys your information?

Mark Kroll: Absolutely. If there was some sort of standard I think it would be easier. The problem is that the data itself can be deceiving. The analysis of real estate on a local level is difficult.

But the point was made that regress analysis does show that you get down to a few basic points. But in a multitenant building it also gets down to the credit quality of some of your tenants, and it can be very deceiving to look at NOI and realize that somebody in that building who's 40% of the rent may be close to Chapter 11.

What we have found is that the technology today has gotten so much better as far as usability that we can now let the people who have a talent for being property managers give us the quality of data that we need to make decisions that they can implement.

Evans: So technology has caught up to your needs in real estate. What happens when technology exceeds? Maybe Jim can comment on the next generation. Where is it headed?

James Melson: Well, our perspective is very much at the grass roots level. We go out and deal with companies who are trying to determine how to do a better job of competing in the daily market place, howto better manage their business and how to access these new emerging capital markets.

There's a cultural change that we deal with in educating these clients. They're trying to decide what they need in the way of technology to help run their business. That's where we come into play and really go through a process of first understanding their business and objectives, and then try to align that with our knowledge of some of the things we've talked about here this afternoon, and help them bridge that with technology.

Micheal Evans, national director of real estate advisory services, E&Y Kenneth Leventhal Real Estate Group

Dean Schwanke, director of information services, Urban Land Institute

Sandy Apgar, founder & principal, Apgar & Co.

Michael Bell, director of corporate real estate, Dun & Bradstreet

Mark R. Kroll, executive vice president, Sares*Regis Group Of Northern California

Dave Henry, vice president, GE Capital

Richard Mead, president & CEO, Black's Guide Inc.

James E. Melson, chairman & founder, Melson Technologies

Hessam Nadji, vice president, research & information services, Grubb & Ellis Co.

Mitchell Schoch, managing director, Teleres

William Wendt, founder & principal, Hartford Realty Systems Associates

Randall Zisler, managing director, Nomura Securities International Inc.

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