“How did I get here?”: The story of how (and why) an old soul CRE / CMBS guy ended up at a SaaS company 

After spending most of my life working in the CRE / CMBS space, I know that not everything can (or should) be automated. Here's my take on what Blooma gets right and why it inspired this self-proclaimed 'old soul' to take a leap of faith on modern tech.
Joe McBride, Director of Client Engagement

The Preamble

Before joining Blooma at the start of 2022, I had spent most of my life at Trepp, a CRE/CMBS data, modeling, and analytics firm. I started there at the age of 16 as an intern rolling CMBS deals in a DOS prompt (hence the ‘old soul’ designation) and began working full-time after I graduated from college. For the first few years, I was helping some of the largest banks in the US build CRE default and loss models using Trepp’s historical loan data. After that, I spent time on a small team that built, launched, and sold Trepp’s own default model, which is still in use today at more than 30 lending institutions. In my final years, I helped drive significant growth for Trepp’s CRE and Banking products and data. In the midst of all this, I was also helping with research, PR and client service efforts, including taking part in the launch of the TreppWire podcast in early 2020.

In my time at Trepp, I’ve worked with and learned from some of the most intelligent people in the industry. This access introduced me to many of the CRE Tech startups in the space, including Blooma. After learning about Blooma’s story, people, and product I was inspired to make a big change (and many would say a big risk) in my career. The following is what I know so far, coming from the perspective of an old soul CRE/CMBS guy at a modern software firm.

The Context

I love Excel, grainy scans of PDFs, handwriting, and mom-and-pop accounting statements on fast food napkins. I don’t think everything can be replaced by computer algorithms. Every commercial property is unique. The spectrum of granularity in real estate is endless and there is always another level of detail available if you’re willing to look hard enough. Complexity and opacity leads to asymmetrical knowledge and, ultimately, profit for those willing to do the work. What I’m trying to say is: despite what your 12-year-old might tell you, not everything can be found on an iPhone or computer screen. Not everything can be automated.

This is especially true for underwriting commercial real estate. The finance industry isn’t one that’s known for fast-paced innovation, and there’s some wisdom behind that. True underwriting means understanding every single nook and cranny of the property, the borrower, and the market.

Getting to that level of understanding requires hard work, time-earned knowledge, internal data, external data, and a reasonable process to synthesize all of it. Reservoirs of information, data, and specific knowledge are trapped in spreadsheets, protective third-party data vendors, internal broker databases, and, in many cases, people’s intuition.

Intuition is important, the “gut feel” is there for a reason. That said, there is clearly room for improvement. Whether you’ve been on the borrowing, lending, or underwriting side of things, any way you slice it, commercial real estate underwriting takes a long time. And in today’s culture of instant gratification, that doesn’t really cut it. So, how do you speed up underwriting without sacrificing all the nuance required? The key is knowing what can or should be automated and what can’t or shouldn’t.

Many commercial real estate technology companies say they will “automate your entire lending process.” All I can say to them is: good luck. Every lending institution has its own flavor, process, niche, institutional knowledge, and configurations of internal and external systems. In many cases, these are institutions that have been around since the carbon copy was an actual paper copy you tore off the back, a memo was delivered by hand, and a phone was that clunky thing on your desk that you actually answered when it rang. This level of nuance means that technology and systems have been adopted at varying degrees and speeds across different divisions and with varying levels of success and integration. Because of this disparity across lending firms, a monolithic system will rarely work for more than one institution. In a similar sense, a system originally built for a different asset class and adopted to CRE, or a set of legacy solutions duct taped together, will always be suboptimal.

The future of software and data is modular and stacked. Lenders will use different, best of breed third-party systems for different parts of the lending and asset management processes. The best providers will focus on exactly what it is that makes them great and rely on other vendors to plug in where they have gaps. These systems will connect to each other more easily over time through open API architecture and internal systems will more and more be plugged into that flow. Companies developing these software and data systems will continue to realize that cooperation across providers will provide the best overall solution for lenders looking for more efficient and profitable origination, portfolio monitoring, and risk management.

Going Forward

Fast forward to today, and I’m sitting on the other side of things working for one of these tech companies. Given everything I’ve just told you, you might be a bit confused. But it’s because Blooma has built its software with this vision of the future in mind that I knew I wanted to be a part of it. Blooma’s document scraping and parsing tech can be plugged into the beginning of the lending process as a data and evaluation funnel into a Loan Origination System (LOS) (think: significantly faster decisions at the very front-end of origination). Its third-party comping and valuation calculations can be called by, and returned to, your LOS or Excel underwriting models (think: easier, faster underwriting package creation). The stress testing calculations, updated market data, and dynamically updated valuations can be pushed into your portfolio or risk management systems (think: more accurate input values for credit risk models and, potentially lower reserves and/or capital requirements).

In other words, Blooma can provide what you need, where you need it. If that “where” is on a standalone platform that can be up and running in a day, we can do that. If the “where” is seamlessly plugged into your existing tech stack, we have that, too. It’s tech as it should be.

As a guy who’s spent most of his life modeling in Excel, reading PDF prospectuses, writing SQL queries, and building VBA macros, this is about as exciting as it gets and it makes me optimistic that we’re headed in the right direction. I’m also excited to participate in the future of modern tech in the CRE space, and as I do, I will continue to translate it for all you other old souls out there.  

Until next time.


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