In the 2018 documentary In Search of Greatness, Wayne Gretzky credits the baseball and lacrosse he played as a boy with making him a better hockey player. Practicing and integrating methods from outside of our traditional approach can yield unique insights that propel us ahead.
Earlier this year, I polled about a dozen real estate investor focused subreddits to gather some perspective on how other professionals analyze a potential acquisition. One investor, active in small multifamily and mixed-use properties, replied and explained to me that the analysis wasn’t the hard part. The hard part was closing the gap between “this looks good” and “my partners and lender will fund this.” He wanted to be able to compare how the bank would look at a deal with his own projections in order to ascertain where his story is too aggressive relative to the bank’s view and have a way to backfill the analysis with actuals through an exit. In other words, it’s important to him to probe for blind spots throughout the full lifecycle of the investment, gain insight, and to use the lessons learned to improve future decision making.
Understanding what exists in the delta between underwriting approaches matters more every quarter. NOI and cash flow have been experiencing growing pressure over the past 5 years from increasing maintenance, renovation, insurance costs, costs of capital, opportunity cost, and regulatory interventions. As a case in point: Federal Reserve economists found that the average cost to insure an apartment unit rose more than 75% from 2019 to 2024, after adjusting for inflation. In my view, the rising cost of owning and renting out property in markets like California and New York, along with tighter regulation, is one reason capital is moving elsewhere. According to 1031 exchange intermediary IPX1031, investors leaving those markets are reinvesting in the Southeast, in states such as North Carolina, South Carolina, and Georgia.
The demand side for capital is arguably responding in kind. Capital flow into non-QM mortgages (I interpret this as seeking relaxed lending standards) has accelerated rapidly over the past 4 years. According to Optimal Blue data, from January 2022 through August 2026, DSCR and investor loan lock volume rose about 130%. Jacob Washburn, branch manager and senior mortgage adviser at Cornerstone Home Lending, said in a recent interview that most of these borrowers are small, local real estate investors, not Wall Street institutions – a similar investor profile as our subreddit respondent. This reflects perhaps a few trends – redeployment of equity from COVID and ZIRP era driven appreciation, an increase in unconventional/non W2 employment, sustained conviction and resilient demand for investment properties, demand for flexible capital, and the quest for better operating margins.
This is meaningful velocity in a market where standards vary widely, even if losses have so far stayed low and manageable. To that point, a late-August Moody’s Ratings review of roughly 30 DSCR lenders and aggregators found that 40% of programs permit DSCR floors between 0.75 and 0.99, and 73% let borrowers use cash-out proceeds to meet reserve requirements. Despite that apparent risk, a June Bank of America report put cumulative losses on roughly $281 billion of securitized non-QM loans made since 2018 at just 3.6 basis points. When every lender’s tolerance is different, independent non institutional borrowers need a standard of their own to test the gap in standards and make a judgement, allocate capital appropriately, time their exit, and roll to the next property.
I’ve been working on understanding how to make sense of this and find appropriate entry points in a market also swimming in high valuations. Here is the core framework around how I’ve been thinking about pre-vetting opportunities. Each starts from seller claims and tests it against independent evidence. Anything I have to estimate is labeled as such so I don’t conflate fact with approximation.
The general themes I strive to get my head wrapped around are 1/ understand if the information in the listing or OM aligns with reality, 2/ dissect income integrity, and 3/ understand the relationship between price and debt. To do that I use the following seven filters and some good judgement.
- Listing/OM: I keep the figures from the listing or OM and check the unit count against the rent roll.
- County record: I use these records to fact check what’s in the listing document(s). Generally, I check datapoints like unit count and year built, run a permit check against any renovation claims, and pre-foreclosure filings.
- Timing of taxes: Under state property tax law, a sale resets the assessment in several states: California is reset at the transfer, with a supplemental bill; Florida resets on the following January 1; Michigan and South Carolina reset the year after the sale. Whereas in Arizona and Oregon, the seller’s capped value carries over. As equity moves between states seeking less friction and cost these nuances matter in managing projections, rental schedules and associated capex/improvement needs.
- Comps: To keep rent comps relevant, I use units listed in the last 90 days and within 20% of the size of the ones I’m evaluating. I score and rank them by distance from the property I’m evaluating, with size counting half as much as distance, and pre-select up to three per bedroom count. In markets like Southern California and Chicago, a mere handful of blocks can be a tale of two cities.
- Expenses: Compare the stated expenses with a minimum share of income that rises with the building’s age. According to Arbor Realty Trust and Chandan Economics’ Q3 2026 Small Multifamily Investment Trends Report, financed small multifamily operating expenses averaged about 42% of income in the second quarter, and about 45% on purchase loans.
- Price: Compare the asking price with recorded sales (following the same methodology for determining rental comps) per unit and per square foot, essentially to challenge the seller’s comps.
- Debt coverage: I apply commercial standards to all deals from 2 units on up. I calculate DSCR the commercial-lending way (net operating income / annual debt service), evaluate cash-on-cash return and year-one cash flow. Then I stress the deal four ways: with flat rents, a higher exit cap rate, higher expenses, and higher vacancy.
Where I diverge a bit is in how I think about net operating income. For my purposes, it starts with the rent roll, plus laundry, parking, garage rentals, cell towers, and other income. From that I subtract vacancy, taxes at the buyer’s assessment, management fee, and operating costs including insurance, repairs and replacement reserves. Fundamentally, it’s somewhere between cash flow and NOI.
Debt service is a full year of payments on the proposed loan. Below 1.0, the property doesn’t cover its own debt – even with a Non-QM loan that a lender may pass at a substantially lower ratio. Megan Castleton, chief credit officer at Constructive Capital, told National Mortgage News that a ratio below 1.0 often requires offsetting factors, such as more liquidity, more documentation or lower leverage.
For me, it’s about scenario testing first, then determining how to make it pencil out – whether a lower price or more money down, with and without raising the rents. Ultimately, the standard and investment thesis is yours to set.
Jared Criscuolo, President, Altio Finance