CREFC Recap: No Fat Pitches

JOE MCBRIDE, DIRECTOR OF CLIENT ENGAGEMENT

I’ve been going to CREFC for around ten years and, during the bumper years of growth and relative stability before COVID, the constant trope was to ask what “inning” we were in at that particular moment. Some rambunctious speakers even suggested we were in extra innings after such a long, positive run. Based on the content and feel at the Marriott Marquis last week, I’d say the players are out on the field trying to finish the game…but they’ve brought in the left fielder to pitch and the coach, GM, and bat boy are peeling away from the stadium in the team bus.

The word I can best use to summarize the vibe of the conference was “eerie.” Nobody seemed to have a real read on when and if inflation would subside and the whole world seems to be talking itself into a recession, the only question being how soon.

Contradictions abound. Attendance was at all-time highs but there was no hot lunch. Unemployment is low but the markets are tanking. Originations and issuance are on pause but there are trillions on the sidelines waiting to be deployed. Loan coupons are only back to where they were in 2012 but nobody other than the septuagenarians in the room have lived through an economic scenario like this (cue all of our collective parents and grandparents telling us about their 15% mortgages in the 80s while conveniently leaving out the purchase price at 1/10th of today’s prices). We’re still open for business…as long as you’re multifamily or industrial. Capital market spreads are out 200 bps but balance sheet lenders will take three months to catch up.

Here are a few snippets and themes from the conference:

  • Investment sales in parts of the middle market are “grinding to a halt”
  • Class B commodity office buildings are “the new malls” (One Vanderbilt and Hudson Yards are the new Short Hills Mall and Ala Moana Center, while commodity office buildings East of Park Ave are the new “Town Center at [Insert Over-Mall’d Tertiary Market Here]”)
  • You would have been winning big if you had “negative leverage” on your bingo card
  • Cap rates aren’t moving up as fast as interest rates but the rent growth assumptions needed to make a deal work these days are getting less and less believable
  • Inflation, inflation, inflation…anybody building inflation into their operating expense, TI, or capex projections?
  • Barely a bid for refinancing anything but trophies in the mall and office space
  • Still “huge pockets of capital” floating around the market, although I’m not sure that means much when the markets are getting clobbered every day and rates are moving 25 or 50 bps a day
  • Multiple instances of “My golf game is going to get pretty good this summer” or “working on my tan this summer” from the originators and lawyers

I realize that this is coming across as quite negative. There were indications that the strong asset classes will continue to thrive, that much of the COVID distress has been worked through, and that bank balance sheets are stronger and more capitalized than ever…but none of that makes us feel much better when we’re filling up our tanks for over $100 or quoting loans at 5+ handles…

On a personal note, CREFC was a bit of a reunion for me, as someone who’s spent their entire career in and around CMBS/CREFC and who missed the Miami conference in January. It’s amazing how many names and faces you get to know through the years and how people tend to stick around in this funky CRE world. Here’s to hoping we’re through the hard part and back to serious positivity in Miami next January.

Until next time,

Joe


It’s time for a checkup: 5 Things to keep in mind when reviewing your portfolio

Geoffrey Eng, Client Engagement Director

Mixed messages in news media about the state of the economy signal a market fraught with uncertainty, and if you’ve been keeping up, it seems that despite optimism from the Federal Reserve, the outlook (at least in the short term) may not be so good.

Analysts have made consecutive reductions in 2022 earnings forecasts over the recent weeks for several reasons, chief among them being weak demand, the Russia-Ukraine war, and interest rate hikes. The market has been soft since the end of last year, and the last month has been particularly brutal in equities, which historically precedes softness in real estate as well.

With a record number of U.S. office leases set to expire this year (243 million square feet, or 11% of overall leased office space) it seems that real estate has caught up to the current market conditions sooner than we might have expected. But there’s more to unpack here. The ongoing conversation around hybrid and remote work is impacting the demand for office in general. And coupled with rising interest rates and looming debt, it’s likely that this will ultimately impact property values.

It’s not all bad news with certain industries buying up large swaths of CRE, but it’s certainly concerning. What to do about it? Check in on the health of your portfolio.

Even if you completed annual loan reviews in Q1 of this year, you may want to take a second look and here’s why: if those reviews were completed using stale assumptions or stress parameters, your findings may not hold up based on where we’re at today. In other words, with renewed volatility and uncertainty in markets, it’s a good idea to perform an updated review of your portfolio so you can tag those that are already displaying weakness for continued monitoring moving forward.

What may seem like an inconvenience, could end up saving you pain and trouble later on. Proactive reviews will provide your organization the breathing room you need to strategize ahead of these newer and unforeseen issues. This means you can be less reactive if downside scenarios play out.

To that end, we wanted to share a sample checklist of metrics and underwriting scenarios that may be valuable for your loan health checks.

1. Update the property actuals.

This includes rent rolls and profit and loss statements. You’ll also want to check that the 1st installment of property taxes were paid on time.

2. Review nearby comparable data.

You’ll want to get an understanding what is happening with market rents. What does the velocity of market sales look like? What is happening with cap rates? How much inventory is currently out in the market, and what upcoming inventory might add to that? How is absorption trending?

3. Stress test and review additional scenarios related to:

  • Debt Service Coverage Ratio (DSCR) – will rising rates prevent the borrower from meeting any payment covenants in place? Assuming a rising-rate environment, is permanent debt as an exit-strategy still a viable option? Was this a loan that was structured with an interest reserve? Is there enough reserve allocated to the loan based on projected future draws (or was this structured with a light interest reserve amount to help win the deal at close?)
  • Terminal Value – as the loan reaches maturity, you’ll want to know if the value of the property will still be favorable. Will it be sufficient for a refinance / takeout lender? Sufficient to be sold with proceeds in excess of the loan amount? Is it in breach of any LTV covenants in place? Etc.
  • Debt Yield – based on our fully funded loan amount, will rents/income being achieved by the property provide a sensible return in the event you have to take back the asset?
  • Timeline – is the current maturity coming up within the next 6-12 months? Is the current exit strategy valid? Will an extension be necessary (and if so, do the docs currently have language to support this?) Are any third-party reports needed to facilitate this?

4. Check for covenant breach and review default remediation.

Are there any loans trending towards a breach of loan covenants that would require further remediation? Do you need to think about getting legal involved or getting your ‘ducks in a row’?

5. Review and update borrower/sponsor/guarantor information.  

  • Have you received updated tax returns and run updated spreads on cashflow?
  • How does liquidity and net worth look if a capital call/infusion was required for the project?
  • Do your borrower/sponsor/guarantor still have enough “skin in the game” to stick with the loan and see the project through if market conditions deteriorate?

Keeping these things in mind as you check in on your portfolio is a good way to determine the overall health of your loans and help you identify those that might be at risk. That said, doing so isn’t always a simple task and running health checks can eat up a lot of time. The good news is it doesn’t have to.

Blooma users have the ability to perform these types of portfolio monitoring exercises within the platform. In Blooma, you have the ability to run stress tests in each deal to identify areas of heightened risk by adjusting revenue, expenses, cap rate, and vacancy to analyze the affect they may have on the DSCR, Debt Yield and LTV of the loan.

In addition to the review of collateral valuations, Blooma also supports the analysis of Borrower / Sponsor / Guarantor financials. This includes the automated parsing and spreading of financial documents such as tax returns, personal financial statements, schedules of real estate, and liquidity statements.  The system parses through those returns, and similar to what you would normally do with Excel or a tax spreading software, Blooma can spread those values into an understanding of what the individual’s cash flow looks like from a pro forma perspective.  This analysis rolls up into a global view of the cash flow, or net worth or liquidity support for a deal.

Personally, what I find most helpful, is that the system keeps deal scores up to date based on real-time data so you can continuously monitor your deals without all the extra leg work. Just because we’re in uncertain market conditions doesn’t mean you need to be uncertain about your portfolio, too. Hopefully this checklist gives you a good baseline of what to review and update, and what you should look out for in the coming months.


The Blooma client experience: Five ways we deliver value from day 1

Laura Bohlmann, Client Experience Manager

Today we’re talking about Customer, or Client, Experience (CX).  

Much like digital transformation, CX has taken the world of business by storm over the last few decades, kicking off massive sea change in the way companies think about and engage with their customers. There’s no doubt that we are living in the ‘Age of the Customer’, but the concept that their experience should be prioritized and their loyalty hard-won is not new.  

What we’re really talking about when we say ‘Client Experience’ is a newfound mindfulness about brand relationships. If the customer is always right, we want to know what they know. For the first time ever, businesses of all shapes and sizes have roles, and oftentimes, entire departments dedicated to designing, cultivating, tracking, and measuring every single detail of the customer journey.

For us at Blooma, CX means Client Experience. We make this distinction not for the sake of being different, but because we believe it sets the tone for everything we do in service of building long-lasting and meaningful relationships with our customers.  When we think about customer experiences, we think about a journey that is more transactional in nature.  Customers come and go.  Clients, however, are people we engage with over the lifetime of a long-term relationship.  Empathy is front and center with helping to achieve our clients’ strategic initiatives that are part of short, medium and long term plans.

The reality is that some companies do this a lot better than others. Between chatbots and call centers, account reps and knowledge bases, there are a lot of ways to engage customers and make sure they’re happy. For software companies like us, there’s an added pressure to fine tune a careful mix between handholding and self-service that sets apart the helpful from the disengaged, or worse yet, annoying.   

At Blooma, we’ve got an opinion about client experience and pride ourselves on the fact that, for us, it’s as much a product as our platform.

Here are 5 ways we do CX differently to deliver value for our clients from day 1:  

1. We don’t do “implementation” 

If you’ve ever been through a really painful vendor onboarding, you know why implementation is a four-letter word for us. The entire process can take anywhere from 3-6 months and often involves a tedious back and forth before you can even start using what you’ve paid for. Our clients look for new software solutions to help optimize or offset an already heavy workload, so any additional effort added for an already overworked team is likely going to turn them off from using the solution altogether — no matter how great it is.

The entire experience is understandably traumatizing for many of our clients which is why we’ve taken such great pains to completely turn the onboarding process on its head.  By creating a platform that functions out-of-the-box, all we need to do to get our clients up and running is make a few minor configurations on the front end before they get access, which takes 30 days or less (and that includes discovery and training). That means that the moment you get your login credentials to the platform, you can start using it. Yes, really.  

2. We take time to understand your goals before you get started

This one’s important. From the moment you sign your contract with us, our Client Experience team gets to work piecing together all the relevant information needed to set you up for a successful onboarding. 

As part of our discovery process, we work with a few key stakeholders and our sales team to identify things like:

  • Current workflow (including key pain points & bottlenecks)
    • Exactly where Blooma fits into your unique process
  • Business targets & goals
  • Department size
  • Portfolio size
  • Deals reviewed during pre-flight vs. originated
  • Types of deals being reviewed
  • Who will be using the system, as well as any unique user personas
  • Underwriting & reporting templates (for mapping & export)
  • And so much more!

Once these details are reviewed and validated by the client, we set an onboarding date with all users of the system and get to work on prepping to ensure it’s as successful as possible. This includes spinning up the client site, template mapping, and setting up user credentials.

Doing it this way means that our client’s “go-live” and first onboarding session are simultaneous, so from the moment you’re done getting trained up on the platform, you also can log in and start using it– no downtime required.

3. We set you up for success from day 1

What may seem like overkill in pre-work on our part is actually a critical component to ensuring each one of our users starts seeing value from the platform as soon as possible. All the discovery work done in preparation means that we can truly personalize your experience with us, meaning that no two onboardings are the same. In person or virtual? One longer session or broken up over a couple of days? That all depends on what works best for the client.

During the onboarding itself, we take what we’ve gathered (including actual deals) from our clients to demo their specific site, aligned to their workflow, using deals they recognize to deliver a true “day in the life” experience and an onboarding that’s actually helpful. Not only this, but we clearly lay out the entire process through to adoption, including a defined plan demonstrating how (and when) we’ll start hitting client goals using the platform – and what we’ll do if we need to optimize or intervene at any point between now and then. We don’t leave your success up to chance, we prep, plan, and nail it together.

4. We make sure you are on target to reach your goals

In order for us to be successful, we need our clients to be successful, too. When we think about Client Experience, we put a major emphasis on the onboarding process because those first engagements out the gate really do make all the difference. But we don’t train and then leave our clients to muddle through the rest. As they say: “what gets measured, gets managed” and as a company that knows the power of data-driven insights we adopt a similar approach in how we think about the experience we provide for our clients.

We track all sorts of user stats inside of the platform to determine what’s working and what’s not. Be it low utilization of certain features, or changes in deal volume or size for example, we can help diagnose and prescribe actions to help get users back on track to reaching their goals. All this goes to say that we make a science out of understanding how, when and why our clients are using Blooma and what we can be doing to consistently add value for them.

While this is an important activity for us, we must also understand that there is a fine line on how much help is actually helpful. Checking in is important, but do this too often, and you might do more harm than good.

For us, that means openly communicating about what our clients want. When we’re first starting out, we want to be as present as possible to ensure that anyone using the platform feels confident to do their day-to-day work. But after that? It’s really up to you.  The important thing to remember is that regardless of the number of check ins we agree on with a client, we’re always keeping a watchful eye on how things are going so we can step in and help at a moment’s notice.

5. We take your feedback seriously

Whether it’s a feedback button on a website, or a follow up survey in your inbox, companies are constantly asking their customers how they’re doing. And if you’re someone who actually went ahead to give your opinion and didn’t hear back – you’re not alone. There are plenty of stories about customer service gone wrong (like the British Airlines fiasco in 2013) due to slow response times, or worse yet, no response at all.

In today’s day and age, gathering feedback oftentimes feels like a “check the box” exercise for brands – but it shouldn’t be. Getting direct input from your customers offers up a gold mine of insight for your business. And we’re here to argue that allowing them to clue you in on where your product has room for improvement is actually a good thing.

We built Blooma with our first few customers because we knew that with their expertise and guidance, we could create the best version of our platform possible. But we didn’t stop there. We’ve built in ways for our clients to request new features and couple that with the insights we gather from platform usage to prioritize getting these items on our product roadmap. But this isn’t just a one-way street. As we think up innovation tracks, we reach out to system users to pitch and validate new ideas to make sure that A) they’re helpful and B) we’re going about them in a way that makes sense for our clients.

Most importantly, we believe in open communication. From the moment a client submits feedback, we kick off a process to ensure they know we’ve received it, what we’re doing about it, and what they can expect moving forward.

At Blooma, we’re constantly evolving to meet the need of our clients — whether that’s changes to the platform itself, or even rethinking Client Experience. What remains constant is our commitment to value, and for our clients, that starts on Day 1. 


Five ways to assess the risk of a CRE loan…and how it’s simpler than ever with Blooma 

Laura Bohlmann, Client Experience Manager

When it comes to underwriting commercial real estate (CRE), getting the most accurate picture of risk possible is essential. Seasoned lenders have fine-tuned a ‘secret sauce’ built on tried-and-true processes, tools, and good old-fashioned intuition. But the fact of the matter is, even when you get it right, it generally takes a lot of time and a lot of work.

That’s where technology can help. Whether you’re fully on board and have already embraced new tech, or you’re still not sure where it fits in — there’s much to be gained by modernizing your CRE workflow. Here’s 5 key steps to assessing risk, and how Blooma can help you level up your lending.

1. Pull rent and sales comps to evaluate going market rates 

First thing’s first: you’re going to want to get as much information possible on the going rate for the property in question. Getting a wide range of sales and rent comparables for the area will give you a quick and clear picture of property value.  

At deal creation, Blooma automatically pulls rent and sales comps for the subject property and ranks them based on pre-determined scoring metrics (these are set by you). Blooma is designed to do the information gathering from trusted sources, allowing you to apply that information in your overall analysis. Even better, you can sort, filter, and edit the entire list – including and excluding comps as you see fit to find your perfect mix.  

You’ll also get a comparables summary that identifies useful data points like, average component square footage, average dollar / square foot, and average dollar / unit. These averages are then applied to the property unit mix to provide the going market revenue and sales comp valuation for your property. Pretty neat, huh?  

2. Create a proforma income valuation to see how well the property cash flows 

A proforma is one of the most important components of a commercial real estate transaction because it projects the potential cash flow of a property. The problem is, putting one together takes a lot of time.  

Blooma creates a proforma income valuation on your behalf by pulling market data to determine factors like revenue, expenses, NOI, and cap rate. The best part is that it is completely editable so it can be customized as you see fit. If you’ve got a model you’re already using, Blooma can map all of the proforma data to your existing template – no lift required.  

3. Calculate the DSCR to understand if income from the property can cover the debt of the loan  

The debt service coverage ratio (DSCR) helps lenders assess the risk associated with a given property as it measures a borrower’s ability to repay the loan based on the property’s income and performance.  

Blooma calculates the DSCR for the collateral, borrower and guarantor / sponsor of the loan. You can also perform single and multi-variable stress tests at the deal level. The single-variable stress test shows the value that can be reached before the minimum set DSCR threshold is broken. The multi-variable test calculates DSCR if there are changes in vacancy, revenue, expenses and cap rate of the property.  

4. …and determine the Loan to value percentage to ensure the borrower has enough skin in the game 

In addition to DSCR, you’ll want to calculate the LTV. LTV, or Loan-to-Value, indicates the borrower’s debt relative to the value of the collateral. Determining the LTV for a given property helps a lender gauge the risk and structure of the loan, as well as decipher if the property is worth the investment.   

Blooma calculates 6 different LTVs within your deal based on the valuations the system provides. You’ll have the option to choose which valuation and LTV you want to use when analyzing your deal. Blooma provides both multi-variable and single variable stress testing for the proforma LTV at a deal level, too.   

The biggest takeaway here though is peace of mind. Data is only as good as the timestamp associated to it. Blooma pulls real-time data and calculates metrics like DSCR and LTV throughout the life of your loan – from pre-flight through to close.  

5. Gather market data to get an understanding of current risks, such as vacancy percentages and absorption 

All of these factors are important to assess the value of a CRE loan, but when push comes to shove, market data can make or break a deal. Even when the numbers check out, market trends and larger forces at play might indicate something different. This is especially relevant today as we face an unprecedented number of global events that are having an impact on local CRE markets. Getting a good understanding of where the market is at is critical, but that puts a huge emphasis on the types of data you’re looking at, what sources you’re using, and how current it is.  And collecting all the information is no small task.  

Blooma pulls in thousands of data points per deal to help ensure the lender is getting the most accurate assessment possible with the least amount of effort and time. 

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

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.

Joe

Class Is In Session! Welcome To Cap Rate 101

Laura Bohlmann, Client Experience Manager

Alright class. Today, we’re talking all about Capitalization Rate. And while this metrics got absolutely nothing to do with grammar, when it comes to its use in commercial real estate, you’ll most certainly want to mind your p’s and q’s.

Capitalization Rate, or Cap Rate as it’s known on the street 😉, is used to calculate the annual return on a property and gives insight into the value of that property. For an investor, it helps them easily compare multiple properties to determine the best investment. It can also provide insight into the fair market value of a given property when looking to sell. On the lending side of things, Cap Rate can tell us about the level of risk associated with that property and can be used to measure and manage those potential risks. Tracking the Cap Rate over the lifetime of a loan can help lenders determine how much they can expect to collect back from a property ­— which is important, especially in the instance that the borrower defaults on their loan. Yikes.

To calculate the Cap Rate of a property you’ll need to know the Net Operating Income (read more about that here) and the overall Property Value:

While this formula might not look very intimidating, I promise you, there’s a lot more here than meets the naked eye. Let’s walk through an example: say our property has a sales price of $1M dollars and an NOI of $100k. In that case, you’d get a capitalization rate of 10%.

What does that mean, exactly? As I mentioned before, the Cap Rate is the amount of return you can expect to get on a given property. That means the higher the cap rate the better the deal, right? Not so fast. The Capitalization Rate is also tied to the risk that’s associated with that particular property, which goes to say that it’s got an inverse relationship to the property value.

So typically, if you have a higher Cap Rate, you can expect to see a lower property value, and vice versa. In commercial real estate, high Cap Rates might mean that the property is located in a less than desirable neighborhood, or has a lot of maintenance fees due to the condition or the age of the building. If you have a property that’s located in a “low Cap Rate” area that might mean it’s in a great neighborhood, it’s a new building, or that it has a lot of appreciation potential.

Put more simply: the riskier a property is considered to be, the higher you’d want the Cap Rate to be. That ensures you’re getting a higher return on your investment to offset the higher risk associated with the property. And this checks out. Sure, you might be receiving a higher return, but you could also be spending a whole heck of a lot more on repairs for the building, or higher vacancy percentages due to unstable tenants. Conversely, the value of a property goes up when a property has a reliable tenant and/or is in great condition because it has a steadier income stream. There is less risk/work that goes into collecting rent on time or maintaining the condition of the building.

Generally speaking, anything between 4-10% is considered a good cap rate, however, this range is subjective because it can vary depending on someone’s investment or lending strategy.

Interpreting Cap Rate

While Cap Rate can tell us a lot about the value of the property, the associated risks, and the overall rate of return on investment, it’s not the only indicator of an investment’s strength. As a matter of fact, it falls short in that it doesn’t consider irregular operating costs/expenses or any value-adding variables. What’s more, is that the market Cap Rate can vary based off different factors like asset type, geographic area, submarket, and property class.  So, while the formula itself might be relatively simple, interpreting this metric is heavily nuanced.

It’s also highly sensitive to several different factors: Current market condition, current lease lengths, and in-place rents versus market rents can all affect the Cap Rate. The current market plays a large role in the property value which significantly affects the Cap Rate. In a down market, property prices drop causing Cap Rates to increase. In a high market, property values increase, and Cap Rates decrease due to the competitive nature of the market. The Cap Rate is also affected by rents because it is based off a property‘s in-place rent revenue. However, if a building has existing rents that are below market value, then the operator can increase the rent over time to better reflect the current market rents. This will increase the NOI of a property and therefore decrease the Cap Rate.

But wait, there’s more! Lease expirations can have a major effect on the risk of a CRE property — especially in a single tenant building. This is because the owner is relying on the rent revenue to cover expenses and make profits. In CRE it takes time and money to find new and reliable tenants to lease space. So, if you have a building that has a large percentage of expiring leases, then it is considered a riskier property which can create a higher Cap Rate. Not so simple anymore. See what I mean?

Here at Blooma, we pull in an extensive amount of market data and can provide the current Cap Rate for a property while taking many varying factors into consideration. Blooma also takes it a step further by then providing an income valuation based off the property’s current performance AND future proforma projections. This allows the investor and lender to see how profitable a property currently is and/or how profitable it is projected to be in the future. Blooma pulls in a ton of market data so we can provide our customers a Cap Rate that’s based on the asset type and the region that’s associated with their property. All that goes to say: when it comes to Cap Rate, we’ve got your back. No guesswork required.

And there you have it: Cap Rates 101. You passed 🤓 Any further questions? Feel free to stop by my office hours, or drop me a note at laurabohlmann@blooma.ai.

Until next time friends.

Bank FinTech Showcase Interview Series

Robert Albertson: Joining us is Shayne Skaff, Co-founder and CEO of Blooma. Also joining this interview is Carson Lappetito, CEO of Sunwest Bank a $2.2B asset bank based in Irvine, CA operating across four Western states.

RA: Shayne – Let’s start with you. Thank you for this opportunity. Let’s begin with your background and how you came to develop Blooma. Where did you begin your career, and why did you wind up in the commercial real estate space?

Shayne Skaff: Thanks for having me. I’m a career tech guy. So, I’ve spent most of my career building AI and ML platforms. My last company was a company called Maintenance Net. We automated how companies manage and transacted annuities. Mainly selling into kind of the service contract renewal and software license renewals space. I didn’t play in or really wasn’t around the lending or banking industry at all until January of 2018. My co-founder, a gentleman by the name of Mike Persall, is the chairman and founder of a bank called ABP Capital, out of Encinitas, California.

Mike and I have been friends for a number of years. In January of ’18 we began looking for insight into what was going on in and around the commercial lending space from a tech perspective. I had not been tracking that space. Over a series of conversations he got me interested enough to dig in a little bit. He was looking for a solution for his own banking needs. He wanted to automate how they originated loans and went through pre-flight within the bank on their commercial real estate loans, as well as automate how they monitor their current loan portfolio.

I looked at the solutions out there in the marketplace where there are gating factors that got me into this. When I looked at what was happening on the residential side, it seemed that commercial lending was at least 10 years behind from an innovation perspective. Yet, looking at those customers that were buying innovation on the residential side, they had massive commercial businesses that were just largely going unaddressed. That, for a technology sales guy, was huge. It told me there was just a lack of product in the marketplace. In June of 2018, Mike and I launched Blooma.

I brought over some of my old team members from my last company, specifically on the product side. Mike gave us access to all of their underwriters within the bank. We mapped out all of the manual processes that went into originating new loans. Then I asked my product and development team what can the machine do here to move these individuals to the art of their job? That was the summer of 2018. We started to build the product.

RA: You hit the bull’s eye in terms of banking, because commercial real estate is usually the largest asset class in any community or regional bank. Can you take a moment and describe the Blooma platform suite and make the case for data-driven analysis and decision making in the underwriting exercise? And then attaching an impressive dashboard for quality and performance indicators, all while reducing the paperwork stream and ultimately unnecessary labor costs? How well has this been working in real life since three years ago, compared to the more labor intensive model?

SS: When you look at the space, what you generally have everywhere from the national, even global banks down to the community banks, is lots of point solutions. You’ve got solutions that do OCR, you’ve got cash flow analyzer solutions, you’ve got your Excel spreadsheet models, you’ve got third party databases, like CoStar and REIS and such. None of them are really connected. What you end up having are humans bringing all of these disparate systems together, which really causes the massive time sink. We’ve bundled up all of these point solutions into our Blooma platform, our machine.

On the front end Blooma allows commercial banks, and really any CRE lender, the ability to actually create lending profiles. I can create profiles on Blooma like a Fannie profile, a Freddie profile, or maybe a regional lending profile. From aggressive to conservative. Those profiles have thousands of attributes that make up a lending profile, but most of our customers really only look at 10 to 15 items that really move their

lending decision. They can tell the machine basically what’s important to the bank within those profiles.

The machine learns what’s important to that lender.

On the side of OCR, we can read offer memorandums, broker packages, P&L unit mix, rent roll and the like so the machine can automate the way they’re digitized. We’re connected to a number of third-party databases, where we’re actually pulling in things like rent comparable sales, environmental data and tax assessor data. That’s all coming into the platform. We’re doing all of the cash flow analysis, all of the valuations in Blooma. On the borrower/guarantor side, we have the ability to read tax returns, K-1s, bank statements, do all the spreading.

At the end of that process, we have the capability of providing a lending score, which tells our client the probability that the deal meets one or multiple profiles which they’ve set up in the system. They can go in and interact with that analysis. Even if they’ve got an LOS system in place we can actually deliver all of that data back into a loan origination system that they’re using or even more importantly, Excel models. We can actually populate their own Excel models with the resulting analysis that we come up with within Blooma. For our customers, they experienced anywhere from an 80% to 85% reduction in man hours on the pre-flight side. More importantly, what they get is the increased production on the business side. Now the client can do a lot more with the same workforce that they have in place because they now have a machine that can help reduce those man hours.

RA: You’ve developed a pretty broad-blanket, technological solution for data analysis. I think a lot of real estate professionals are concerned with the paucity of quantitatively comparable information that could be very useful for the lending decision. Why do you think this lack of data developed in the first place? Analysts in the industry often wail about the repeatability of real estate credit loss cycles that seem to only become obvious well after the fact. You seem to have addressed this.

SS: We certainly are trying. The data side is probably the most complex piece of this. There are a number of different data systems out there. I would say that some of them match up and some of them don’t. So the complexity is in how you gather all of this data, how you normalize that data, and how you bring together a better, more complete data set that you can work off of. That’s where I’ve spent my career, in a very nerdy place.

These are the things that we know how to do really, really well. We look to build up our data library, and find the best pieces of data in very specific places. For instance, via asset class. There are some third party data systems that have better information on say, multifamily, than other third party data systems. We go looking for and finding the best-in-class data in very specific spaces. So, when it comes together in Blooma, our customers are experiencing a very complete and accurate data set that they can work from. When you get better rent comparables and better sales comparables, you get better valuations. That’s really what we tried to produce out of Blooma.

RA: I take it you can do this pretty much agnostic to geography. Are there any restrictions?

SS: Only by geography within the US. We are US only today. We certainly have plans to move out but right now we’re US only.

RA: So, is Blooma’s secret sauce basically the ability for artificial intelligence to synthesize various sources of data into hard, usable data for underwriting decisions?

SS: I’d say there are a couple of pieces where we have extreme IP on the AI side. We’re not using AI to make decisions for people. We’re really using AI in two main places. One is in the parsing of data. Two, is when users are interacting with things like rent comparables, sales comparables. They’re actually training the system on what’s important for each of those asset classes that they’re looking at. On the data side, as we talked about, how we aggregate and bring this data together, and normalize it, we’re doing some really interesting things there. We have a product called Blooma Central, where all of that data structure is coming together. I’d say that piece is as impactful and as important as what we’re doing on the artificial intelligence side.

RA: Artificial Intelligence is increasingly ubiquitous in FinTech, from what I can see. Yet, the artificial intelligence concept is probably not comfortably or sufficiently understood by your average banker. Can you take us into the machine learning weeds for an example, perhaps, that bears on your applications?

SS: The uncomfortable feeling that people everywhere – not just in banking – have with artificial intelligence or machine learning, is really around the replacement of people. We don’t look at that at all when we build or when I have ever been involved with building out an AI platform. It’s really about moving people to the art of their job and actually making their job better. Utilizing the machine to do a lot of the monotonous boring work that a person doesn’t need to do, and really move them to the place where people are needed. One specific example would be around new construction lending: There’s more nuance in new construction lending than in some other asset classes, like vanilla multifamily loans. Where we can actually provide freedom for people to move to the art of their jobs is needed within underwriting and analytics. That’s really what our goal is. It’s about providing results that a person could use to make quicker, better decisions off of, instead of having the machine make the decision for them.

RA: Tell us what your client list looks like at this juncture. Is there a range by size or geography or type? Do you have pilot programs for the larger banks in the system? How many clients are on the Blooma platform now?

SS: We have a dozen clients on the platform at present and they range anywhere from the $1B to upwards of $10B. I’d say most of them are between $3 to $10 billion in CRE AUM at this point.

RA: Any pushback when you’re trying to put this together? In your view is there a typical profile of a bank to make the most of the Blooma platform or is it pretty broad?

SS: I wouldn’t even consider any feedback to be pushback. We’ve gotten such an amazing positive response. I’d say that really the time it takes to get to a yes is primarily because there’s so much involved

with vendor onboarding. This is more on the commercial bank side. On the private bank side there’s less of that that we have to go through. So, I’d say that our hurdle on the commercial banking side is really regulation and going through the vendor onboarding process. Going back to where the art of lending lies. There’s a lot more art on the $100M+ loans. I’d say our sweet spot sits between the $5M to $100M mark. I say that only because that’s most of what we have in our system today. It seems to be where we’re seeing the most activity within the Blooma platform.

RA: I assume you’ve had contact with bank regulators. What are their attitudes about your platform and their general receptivity? Have you brought them into the tent?

SS: It’s a great question. We haven’t had direct contact with bank regulators. Through the clients there’s been that contact, but not directly with Blooma. We’ve had no pushback so far. We’ve moved through vendor onboarding, in which case there’ve been regulators that have seen what we’re doing. We’ve had no real obstacles that have held us back from onboarding a customer to date.

RA: How do you price Blooma to the client?

SS: Today, our pricing is based on the AUM that’s actually flowing through our system. So, it’s not user based. We want as many users in our system as possible within our client base. It’s a fixed subscription fee, based on AUM. It’s pretty simple.

RA: Let’s move to the profit and loss impact. I know you say there’s about 80%+ reduction in costs. What does that do for a CRE-oriented bank’s bottom line? Can you turn it into dollars or some sort of impact on profitability?

SS: That’s probably a better question for Carson. From an ROI perspective the 80 to 85% is on man hours. I think because our costs in general come in somewhere around a basis point on AUM, we’re fairly inexpensive for the value that we’re providing our client. We’ve had no real pushback on our pricing model. From a bottom-line perspective, we’ve heard less, and again, Carson, it’d be great to get your comments on this. We’ve heard less interest on the cost take out and way more interest on the production increase. They’re not letting people go by using Blooma. They’re just doing a whole lot more with less. Carson does that resonate with you?

Carson Lappetito: Absolutely, I can add on two ways. One being on the loan origination side, I think about it the same way I think about my salesforce cost. It’s very easy to do the math of what the Blooma platform is costing you and put it into the spread you’re originating off a loan. You divide the cost of Blooma divided in by your 2% spread, dropping to the pretax income line item. You say am I going to drive, incrementally, that many more loans, by having this platform? When you do that math on a platform like Blooma, that increases your efficiency and your ability to deliver term sheets and lending at speed, which is ultimately how we differentiate ourselves in the relationship and the commercial real estate lending business. It’s a no brainer decision.

RA: Thank you, Carson. Tell us how long you’ve been on the platform and what was it like to implement it? How are the results versus your initial expectations? What’s different now?

CL: I’ll caveat this answer with I’m different than most bankers. I have approached Blooma a bit differently than a lot of other bankers. My answer is not indicative of all of Shayne’s clients. I was very focused on leveraging Blooma as a portfolio management tool, less so on the front end origination to start. We’re running our pre-flight through that process, in order to get to a quicker decision on putting a term sheet out to a client.

We’ve been engaged for just about three months now. We have our entire portfolio loaded up. A big chunk of our rent rolls, a big chunk of our appraisals have been OCR’d through their AI into the platform. Basically, we can look at our entire loan portfolio with real time comps. With real time cap rates from transactions generating real time values of what the portfolio looks like, both as a trend line from what the appraisal was when we originated it. What is the Blooma value today based on their public comps? Especially when we load in our rent rolls. Then we have a rating score of how we feel about the current rating compared to where we originated it. How does it stack in our aggregate portfolio? Should we be spending more time on this credit or less time, depending on how that ranking looks.

What we’re really driving here is the fact that banks, historically, go and look at how their portfolio performs on two occasions: one during the annual review, or two, when a payment is missed. They don’t do any portfolio management in between. In real estate, usually, you have a one-time check on a real estate loan. If you go back to the real estate world. You really aren’t tracking what’s happening in that local economy, that intersection, etc. on an interim basis between your annual reviews, and so especially in an environment like we’re in right now where we’re going through COVID, different asset classes are performing differently. Traffic patterns have changed.

You don’t necessarily know what the exact per square foot rental comp is happening on that corner, that sub market of the city. Blooma is pulling that data real time and telling you where you need to focus. So, for us, it puts us in the catbird seat of looking at our portfolio and saying, “What are we very comfortable with?”, “What are the emerging trends we have to be aware of?” It allows us to be really proactive in managing the portfolio as opposed to being reactive, which is how almost the entire banking industry manages their loan portfolio.

RA: So, is it fair to say that you feel a lot more comfortable with your credit exposure and your portfolio than you did before? Is it essentially no longer an annual review issue? It’s a real time, ongoing review.

CL: Yes, I feel a lot more comfortable. I’m an incredibly conservative underwriter. I would say the proper term would be that I feel a lot more knowledgeable. Therefore, the deals I feel uncomfortable about I’m on top of and dealing with, and the deals I feel comfortable about my team’s not spending time on. They’re spending time either managing the deals we’re worried about, or finding new business, which is ultimately how you pay for the whole platform.

RA: Okay, a question for you both. What is Blooma’s differentiation to the competition? Carson, you go first please. Why did you pick Blooma, and what advice or argument would you give to prospective clients?

CL: I don’t know of another platform in the space that is doing this. So, the decision really is, am I going to do it the way I’ve always done it, or am I going to implement Blooma? I think we’re on the edge of more companies and more technology entering our banking space to help make our whole industry more efficient. Today, if you want to do what I’m talking about here when Shayne was talking about either on the front end, or the portfolio management side, there are no other options.

SS: I’ll just add to that, Robert. We’re the only ones actually taking all of these point solutions out there and bringing them together. I’d say if you take any of those point solutions, there are all kinds of competition going on within them. I would say we’re not really competing against any of them, even the third-party data providers that we don’t have contracts with. I don’t look at them as competition. The reality is we may decide to make them part of our library six months from now because we like the data that they have. Right now, we’re in a pretty good position from a competitive perspective. There’s a lot of big players out there. I generally am looking at what they’re doing. It’s mostly the guy or the girl that’s sitting in a dorm room right now who’s building new crazy products that are going to come up that we’re going to see. I think we’re going to see a lot happening over the next couple of years as PropTech is really moving quickly now. Since 2018, when we started Blooma, I’m starting to see a lot more activity happening within the PropTech space specific to commercial.

RA: So, is it fair to say you’re unique at the moment? You’re the full package?

SS: Yes, I’d say so. I haven’t seen somebody that we’re competing head to head with that has the same solution as Blooma. There’s lots of companies that have pieces of our solution, but we’re kind of packaging up lots of these point solutions in a very unique way. I’ll add it’s not just the product build itself, but also how we’re implementing the product within our customer base. We recognized really early on the complexity of the commercial banks and the core systems that they had in place. We are very sensitive to not having to forklift out one system to put in our system. What we’ve done is very unique.

We’ve built a very flexible platform that can be integrated with, for instance, nCino, or any other LOS system that can feed your Excel model that you might want. Again, the results of our data are going into some other system that the bank might have. On the preflight side you can literally access our system in a few days. We can have a system up and running for a bank in a few days. They could be going in and loading OMs and actually doing deals in our system with very little effort and no implementation. The only time sink that we have is if we’re integrating into a system that the bank has that we haven’t seen before. Generally, if there’s an open API, it’s a very quick build to get us connected.

RA: You’re basically core agnostic?

SS: Yes.

RA: Let’s move over to the auditing and monitoring function of Blooma. How does that work?

SS: The portfolio monitoring? So basically, I walked you through the whole analysis when we’re doing the initial cash flow analysis and the valuation of that asset. When we consume a customer’s portfolio, we’re literally doing that every single day on every asset in that portfolio. What does that mean? Does it mean that they’re going to see a change in the lending score every day? No, because the times when there are changes are generally when there’s new data to be presented to the machine for the analysis. If that data changes, like an updated rent roll, if it changes to the positive, then it’s generally going to move the lending score up. If it changes to the negative, it’s going to move the lending score down. If there’s some dramatic increase in vacancy rates in a specific region and it impacts some of the assets that a bank might have there, then that will drive the lending score down. That’s happening every day. Our system is looking for the changes that might exist with that asset, or if they upload new financials for the borrower that could also have an impact on the monitoring of that specific loan.

RA: Carson, you’re unique as well, in that you cover a very large swath of geography in the west with a very thin branch network. Are there any examples so far of how this function has been turning up things that you appreciate in terms of warning signs or something you might otherwise have missed?

CL: There’ve been a lot of great examples. The first exercise our team did was a COVID analysis on all of our loans. We ranked them by risk level and in various tiers. We took that and compared it to the risk scoring that came out of Blooma. We looked at the differences and asked “Why?”. There were a number of loans on that list that we thought were better than they actually were. We’re very strong underwriters, but the goal is to figure out what you don’t know so you can solve it, and there were a handful of loans that had higher LTV than we had thought based on rental rate compression in their market. As a result, they’re a bit higher risk than you initially anticipated. Then you can adjust accordingly when you have your covenant testing periods.

You want to make sure you’re on top of those from a portfolio management perspective. Banking’s a risk- based model. You can’t be a hawkeye on everything when you have a big portfolio. You have to make sure you’re on top of everything that’s got a little more risk to it. Just the fact that it is teasing out something that you should be looking at and directing an RM towards is very valuable. Helping that RM focus on the art of their job.

RA: I will compliment you on your speed of implementation. It is unusually short for within the FinTech arena, which I think is quite impressive.

Let’s finish off with a question to Shayne on scope and scalability of your organization. He recently received an injection of capital from Canapi. How comfortable are you with your funding to date and your scalability going forward? Specifically, where do you think your client base will be in another year or two?

SS: Very comfortable with the capital that we have right now. We have a very strong balance sheet and will need it to do the things that I’m forecasting to do over the next 18 to 24 months. We’re using that

capital to bring on a sales and marketing organization. We’ve been heavily driven by R&D and product. Bringing on sales and marketing is something that I started doing at the beginning of this year. We brought in a head of sales, we brought in a head of marketing, we brought in sales directors, we’ve increased our customer experience (onboarding) team. They’re the ones that bring our customers on and train them.

It’s a pretty easy onboarding because we’ve got a platform that’s fairly intuitive. Users only really require an hour or two of training. The Canapi guys have been phenomenal to us. I believe in raising capital where capital is the least of what you get. It’s really the intellectual knowledge and the help on the other side. That’s when you know you’ve got a great partner, and that’s what we’ve got with Canapi. They’ve given us great introductions. Not just into clients, but into resources which are extremely important for a company of our size.

We’re looking to basically triple the quantity of customers over the next 12 months. I feel very, very good about doing that. I’ve got a great operator in place that understands what we need to get to certain places. He was my COO at my last company. So, we’ve been together a long time. I’ve also operated with my CTO before. This is the team that I have in place – the core team that has been here since the beginning. We’ve all actually operated together and that makes for much easier momentum. I tell them what we’re doing from a sales and marketing perspective. They know what I need from a product and R&D perspective to make that happen.

RA: It sounds to me like the Blooma story has a lot of impact, and Canapi is a great partner. They’re best in class in terms of industry knowledge and connections.

Have I missed anything, anything either of you want to mention?

SS: I think you’ve done a great job, Robert, of hitting some key points that I would want to put out there. I want to thank Carson for his time for being a part of this. It’s always wonderful to have a client doing these interviews with me. So, thanks, Carson for spending the time especially what it sounds like in a very crowded environment that you’re in out there.

CL: Happy Shane brought a product like this to market. The more innovation we can drive in our industry, the better. I’m a happy client, and thanks for including me in the interview.

SS: I’ll just say, Robert, for those banks that are going to view this, the process is probably abnormal for them. I think this specific space has been stuck in a software environment that has been a super heavy lift for many decades. This is not that. That’s very important for them to understand. Initially, when we come in and start talking to a bank they don’t understand until we get through our meeting and they actually understand that this is a technology that’s built in a very different way than the system that they’re running on today. I look forward to talking to a lot of those banks over the next year.

RA: This has been a very helpful, thoughtful interview. I appreciate your time. Both of you. Shayne, if a financial institution reading this would like more information or maybe connect with you, would you be willing to provide your phone and email coordinates here?

SS: Yes. You can email me at ShayneSkaff@blooma.ai. I also can be reached by phone at 858-442-3696. I am happy to talk to anybody interested.

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We Need To Talk…About DSCR

Laura Bohlmann, Client Experience Manager

“We need to talk”.

I know they’re not words you want to hear, but I promise this time it’s worth your while.

About what exactly? Nope, you’re not getting fired, and we’re not breaking up. Today, we’re talking about DSCR — or debt service coverage ratio and why it’s basically the Holy Grail of CRE metrics.

DSCR is a calculation used to see the cashflow of your property after you’ve removed all of your annual debts, but what you really need to know is that it’s important. Like really important, and it’s generally the first thing lenders look at in the borrowing process. Why? Because it can determine the structure of a loan. For example, if someone isn’t even close to the minimum DSCR they are looking for, then the lender will decline the loan right away. If someone has a DSCR that comes very close to the minimum DSCR amount, then a lender might cut back the total loan amount which will then require a larger down payment. This will increase the DSCR amount AND lower the LTV amount which will mitigate the risk in two ways. See what I mean? Important.

How Do You Calculate It?

To calculate the DSCR of a given property, you’ll take your Net Operating Income (NOI) (more on that here) and divide it by the total annual debt.

Typically, a CRE loan has a business listed as the primary borrower. So, in this case the annual debt includes all of the current year’s business debt obligations (or borrowers’ debts). This would include debts such as line of credit payments, minimum credit card payments, business lease payments or any type of business loan payment (this can even include business equipment loans). The most common mistake I see in calculating DSCR is not including all of the borrower’s debts. Some people only account for the loan payment but forget to include all other business debts, so be sure to keep an eye out for this.

Let’s Practice!

In this case, let’s say you’re looking at a property with an NOI of $150,000 dollars and there’s a $10,000 dollar monthly payment. Over the course of the year (annual, or x12), that monthly payment would amount to a total Annual Debt of $120,000.

Divide the NOI by the total annual debt and that gives you a Debt Service Coverage Ratio of 1.25. So, what does that mean exactly? A DSCR of 1.25means that you have 1.25x the amount of cashflow on that property than you do debt (FYI, that’s good).

It’s important to note that preferences and requirements on what makes a ‘good’ or ‘bad’ DSCR value can vary from lender to lender. Generally, a lender will create a covenant saying that the property must have a “minimum DSCR of X” and then they track it through the life of the loan to ensure that the property is still making an adequate amount of money to make the loan payments. If the borrower doesn’t meet the minimum DSCR requirement at any point during review (typically tracked once per year at annual review) then the lender might start reviewing that loan more frequently (like every quarter, for example). Or, if this trend continues for long enough, they may possibly force the borrower to pay off the loan entirely.

While there is no ‘set range’, here’s generally how DSCR gets broken down:

No matter how ‘good’ the DSCR is at the outset, it always gets tracked throughout the year and here’s why: it fluctuates, and sometimes, a lot.

The DSCR value can change because the NOI can fluctuate, too, based on changes in things like vacancies and expenses. So, if your NOI decreases then your DSCR will decrease as well. Also, the total debts can increase as the borrower takes on more debt. If the borrower’s debts increase, then the DSCR will decrease.

Here Is What A Borrower Can Do To Work On Increasing Their DSCR:

  1. Increase their NOI by increasing their revenue (which they can do by raising the rent, for example).
  2. They can also decrease their expenses to increase NOI. For example, they can analyze their spending and cut down any unnecessary expenses.
  3. Lastly, they can pay off business debts. By paying off as much debt as possible it will decrease their overall total debt expense and in turn increase their DSCR.

We’ve established that DSCR is important, but today, it matters more than ever.

With market changes brought on the by the pandemic, we’re looking at a level of instability that makes lenders wary — and for good reason. In most cases (and pre-COVID), a ‘good’ DSCR value would be anywhere between 1.25 and 1.5. Today, you can expect that lenders are likely looking for DSCRs in a higher range than usual because of that volatility in the market. Raising the bar on DSCR helps lenders mitigate risk in uncertain times (like now) where expense rates and vacancies are higher than normal. As such, it’s extremely important for lenders to be able to consistently monitor the DSCR of a property with real-time data. This way, they can get the most accurate picture of performance possible and get ahead of unfavorable changes that may be coming.

And there you have it: DSCR. Hopefully this gives you a good overview of why it matters, how it’s calculated, and how to stay on top of it. Your takeaway for today? Keep your blood pressure down and your DSCR up! Doctor’s orders!

Until next time,

Laura

Still have questions? Drop me a note: laurabohlmann@blooma.ai.

Let’s Make Some (NOI)se For NOI

NOI. This powerhouse metric is a staple in CRE lending. And today, we’re breaking it down to the basics for you.

  • What is it?
  • How do you calculate it?
  • Why does it matter?

These are some of the questions I often get asked on the job – and for good reason. NOI, which stands for Net Operating Income is a critical measure of whether an income generating property is going to be profitable or not. Which, if you’re reading this and are in the world of commercial real estate, you definitely care about.

NOI measures a property’s ability to produce income based on the income from its operation and is often confused with cash flow. But make no mistake, these two things are not the same. NOI is different than cash flow because cash flow includes debt service for the property (debt service = debt payments). Cash flow is the income generated after the debt is taken out. Basically, that means the cash that the owner makes off the property after all the expenses are factored out.

If you want to understand what the NOI of a property you’re considering is, you’ll need to know how to calculate it:

First, we need to determine the Total Revenue of the property. So, for example, let’s say you have an investment property that makes $15,000 per month in rental income, after you subtract out any of the vacancies and concessions (more on that in a moment), you’ll multiply that by 12 – which puts you at $180,000 per year (your Total Revenue).

Next, you’ll need to subtract out any of the operating expenses. What falls into that category? Things like repair fees, maintenance fees, property management fees, insurance, etc. Now, I know what you’re probably thinking: where’s the mortgage payment in that list? Surely that would be included in your list of expenses for the property, right? Not exactly.

Technically, we don’t consider your mortgage as an operating expense, but rather, what’s known as a ‘finance expense’. Here’s why that matters: finance expenses are incurred by the owner/investor of the property rather than the property itself. (This is important to note because NOI is only intended to capture the income produced by that property. Finance expenses, on the other hand, can vary from borrower to borrower depending on how much they are financing their loan for and the structure of that specific loan. In other words: It’s not relevant in this case.) So, for this example, let’s say you have $50,000 of operating expenses each year. You’ll subtract that from your $180,000 which leaves you with $130,000. Your NOI.

The math is simple enough, but the result matters. A lot. Not only is NOI a really simple and reliable way to get at the value and potential of an income producing property – it’s also used to calculate lots of other critical CRE metrics as well. For example, you’ll use NOI to determine things like:

  • DSCR (NOI / Annual Mortgage Debt)
  • Cap Rate (NOI / Current Market Value)
  • Property Value (NOI / Cap Rate)

A Brief Interlude on Vacancies and Concessions:

Let’s get back to vacancies and concessions for a moment. Vacancies take into account the % of rental space at a property that is not currently leased, or is currently vacant. We remove vacancies out of the calculation because we currently aren’t collecting any rental revenue from that space. Concessions are typically given to someone as an incentive to sign a lease. Typically, this would be in form of free rent for a new tenant. For example, many places will give you one month of free rent if you ‘sign today’. In cases like these, you’ll want to make sure that the one month of free rent is not included in total revenue because it was not technically collected.

…Aaaaand that’s a wrap on NOI! Hopefully this gives you a better understanding of how it’s used and its importance to CRE lending. Still have questions? Drop me a note: laurabohlmann@blooma.ai.

Until next time!

Connect with Laura on LinkedIn

The Power of Curated and Consolidated Information

Shy Blick, Chief Technology Officer

Answer to any question: 10 cents. Correct answer to any question: 10 dollars.

The information revolution has brought access to data to the masses. “Knowledge is power” is not specific enough anymore – the true challenge is in making sure the information used in decision making processes is reliable.

If you want to purchase a product, you spend time scouring the web, learning about the product’s characteristics, comparing it to its competitors, finding different suppliers and their pricing, etc. In order to make an informed decision you know that you must become a mini expert on that specific product. Businesses make this process more efficient by building information harvesting systems which automate a portion of the research, but these still require employees to invest their most valuable asset – time. Time to make sense of the information, to make sure that it is relevant to specific business needs, etc.

First, every piece of information has a finite lifespan. When you check the weather, you know that the information you just gathered is good for today only. The value of a commercial real estate property fluctuates as market conditions change, and a year-old credit score may not reflect the current financial status of a borrower. Therefore, it is important to identify the age, rate of accuracy degradation and expected expiration of each piece of data that you harvest.

A successful information harvesting and processing system is characterized by the user spending little to no time gathering and processing information and most of their time making decisions.

Next, you need to identify the credibility of the source of the data. Did you get the borrower’s net worth valuation from the borrower or a third party impartial source? Try reading about the same event at two different news outlets. The same story looks totally different if you experience it through different sources. You may have to read multiple sources and find the truth yourself somewhere in between them. This is fine when objective truth is not so important, but when information needs to be consumed in a path that leads to the success of the person or business entity, truthful data is crucial.

The situation gets even more complex when we consider the concept of infobesity. Information obesity is just what it sounds like – an epidemic that exposes humans to an overload of information, leading to a situation where we can’t see the forest for the trees. When an underwriter is onboarding a loan, they put a lot of effort into harvesting huge amounts of information, and at some point they need to make a decision based on a forest of data points. It’s like telling your doctor that you are not feeling well and explaining your symptoms, and in response he or she simply gives you a list of the hundreds of possible causes for those symptoms rather than telling you their qualified diagnosis. That’s the experience we are used to today when we use search engines, and it’s very similar to what decision makers face when they need to decide based on thousands of data points around a loan.

So, in our era, rather than saying “knowledge is power,” it is more precise to say that “curated and consolidated information is power.” The most valuable information must be curated by an expert (human or AI) to fit the needs of the business, automatically harvested by a computer system, and continuously checked for its lifespan, credibility and accuracy. And when all of that is done, the business must take the next step of consolidating the information in a form that will still deliver the powerful insights without causing an outbreak of infobesity.

Today, decision makers spend most of their time preparing and processing information and only a small fraction of it making business crucial decisions. A successful information harvesting and processing system is characterized by the user spending little to no time gathering and processing information and most of their time making decisions. Such users can conduct much more business in the same amount of time, which leads to a higher chance of business success and a lower “cost of doing business.” Such a system allows its users to look at information like a judge on “America’s Got Talent” might look at a contestant. They can watch just a few minutes of a performance and make an informed final judgment without further investment.

Now that’s power.

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