[caption id="attachment_8625" align="alignright" width="200"] Credifi's Ely Razin[/caption] We've spoken a lot on the podcast about tools for institutional investors. Technology and data have changed the way they go about their business. But that's not really true for real estate investors. It's funny — in an industry where hundred million dollar transactions are the norm, there's surprisingly little data-enabled decision making. Corporate real estate finance is still predicated on relationships — between buyers, sellers, financiers, and brokers. Ely Razin wants to change that —his firm, Credifi, is developing big data solutions to provide transparency for the corporate real estate ecosystem. He's built and sold a previous startup to Thomson Reuters and joins us on the podcast this week to talk about how big data will change the way real estate investing is done, the opportunities and challenges of building a fintech startup in the CRE space, and how building a startup finance company has changed since his last go-around. Below are lightly edited and condensed highlights from the conversation. What role does data currently play in commercial real estate finance? It's really interesting -- real estate has been perceived as a laggard industry that didn't readily adopt data at the core of its decision making processes. And that's despite the fact that any real estate transaction is fairly large in size. These aren't hundred dollar stock purchases. Building purchases can be worth hundreds of millions of dollars. That's beginning to change and we're part of that change. How real estate investing changes once data and analytics become commonplace We have coverage of 2m properties and 2.5 loans that finance them. We have coverage of the real estate markets in the top 100 cities in the US -- from New York City to Spokane, WA. With a full view, an investor can decide where he'd like to invest, when he'd like to do it, and when you think a borrower is ready to move. By contrast, in today's real estate market, a buyer is completely dependent on brokers. One thing having information enables you to do is simply spot the right opportunities and go after them. It sounds like you're trying to create the Bloomberg of commercial real estate finance We often draw the parallel to Bloomberg. Aspirationally, Bloomberg is a fabulous model. We do take a few pages out of their playbook. First, we start by putting all the data available in one place. That's critical -- this is a market that was highly fragmented. We weave all the data together, so that our users can click through from a property to its owner to its lender. The second thing we take from Bloomberg is an understanding that it's not just about the data -- it's about moving the transaction forward. Bloomberg's messaging platform is a backbone for trading. We have the mindset that we want to help get deals done.