It’s not the market that’s slowing you down, it’s your process. These bottlenecks aren’t new, but the pressure to fix them is.
The CRE landscape in 2025 is presenting lenders with more complexity than a three-ring circus during a power outage. Circus content aside, banks and debt funds are juggling fluctuating property values, waves of maturing debt, stubbornly high interest rates, and increasingly risk-averse credit committees. Staying competitive? It’s no easy feat.
But here’s the thing: many of the biggest bottlenecks in commercial real estate lending didn’t start in the last few years. They’ve been quietly baked into the underwriting process for decades, slowing deal velocity, draining team capacity, and holding lenders back in ways that often go unnoticed.
This piece isn’t just about pointing out problems. It’s about clarity. About spotting what’s actually slowing you down—and showing what top-performing lenders are already doing to increase deal volume without compromising standards.
Let’s break it down.
Legacy friction points that still cost lenders time, money, and momentum.
CRE underwriting remains one of the most document-heavy workflows in finance. Underwriters still spend hours and even days manually transcribing and reviewing borrower documents, including PDFs such as profit and loss statements (P&Ls), rent rolls, and tax returns, into spreadsheets. Every file feels different. Every deal starts from scratch. The result? Underwriters spend more time formatting data than analyzing it.
Underwriters are not underwriting- they are spreadsheeting. With manual data entry and document chaos, time is wasted, staff burnout occurs, and critical decisions are delayed.
What smart lenders do: They standardize the intake process and automate data ingestion, using AI to aggregate documents into structured, usable data within minutes. This allows their teams to spend less time hunting numbers and more time making decisions. Essentially, equipping their teams with modern tools to stay competitive.
It’s no secret that commercial real estate underwriting is rarely a linear process. Even the most promising deals can get bogged down in internal delays—waiting on third-party reports, clarifying borrower-provided documents, reconciling version discrepancies, and rerunning models when assumptions change mid-stream. In commercial lending, time kills deals. Yet, the average CRE underwriting process still takes anywhere from 1 to 4 weeks, depending on deal size, property type, and internal committee structures.
What causes the lag? As mentioned above, it's rarely just one thing. Often, it's death by a thousand paper cuts—missing documents, disconnected systems, duplicated efforts, and credit committees overloaded with legacy deal reviews.
A 2024 Federal Reserve Staff Report attributed a 4.8–5.3% drop in new CRE loan origination to lenders being overly preoccupied with refinancing and extension requests from maturing loans, which limited their ability to evaluate and fund new opportunities. In short, underwriting teams are stretched thin, and it’s showing.
And as the underwriting burden grows heavier, deal teams are spending more time chasing clarity than driving decisions. One missed email, one missing rent roll, or one delayed appraisal can reset the entire clock.
What smart lenders do: They’re deploying intelligent pre-screening tools to identify high-quality deals earlier, before the underwriting team gets buried in files that won’t pass credit. They’re building workflows that reduce handoffs, automate manual steps (such as document parsing and data aggregation), and expedite the movement of viable deals. This frees up underwriters to spend their time where it matters most—evaluating risk, structuring terms, and moving good loans forward without the drag of administrative dead weight.
Few things slow a deal down faster than conflicting numbers. It’s a familiar pattern: the rent roll says one thing, the P&L statement says another, and the tax return tells a third story entirely. Sometimes it’s a matter of timing. At other times, it’s due to formatting, rounding, or a well-meaning borrower trying to simplify the math. Regardless of intent, the outcome is the same—underwriters are left to play detective.
These mismatches don’t just create back-and-forth; they create doubt. If the borrower can’t present clean, reliable numbers, how confident can a lender really be in projected cash flows or debt service coverage? And when multiple team members are working from slightly different versions of the same document, it’s not just frustrating—it’s risky.
A recent blog, "CRE Data Obstacles and AI Adoption," notes that fragmented and unstructured data are among the top barriers to efficiency and insight in the modern CRE workflow. It’s also a hidden drag on productivity: when a 20-minute review turns into a 3-hour reconciliation exercise, that delay cascades through the entire deal team.
What smart lenders do: They put intelligent systems in place to flag inconsistencies automatically, verifying rent rolls against P&Ls, matching borrower data, and tagging missing or suspicious values. By structuring data at the point of ingestion, they minimize rework between teams, reduce deal fatigue, and keep underwriting moving without sacrificing rigor.
Underwriting has always required judgment. But when that judgment is overly reliant on institutional memory or gut instinct, consistency suffers. Two deals with nearly identical fundamentals can produce two very different outcomes depending on who’s holding the pen—or which credit committee happens to be reviewing it that week.
This variability not only slows down decisions but also creates internal friction. It forces underwriters to over-explain, credit officers to second-guess, and deal teams to rerun scenarios just to reach a common baseline. In an environment where every loan must withstand greater scrutiny, this kind of ambiguity becomes a liability.
We explored this theme in our post on AI vs. Traditional Credit Risk Models, where we noted that traditional methods often fall short of providing transparent, repeatable frameworks, especially as portfolio complexity increases. Credit committees don’t just want to hear ‘we think this works.’ They want to know why, based on objective criteria.
What smart lenders do: They establish structured, data-driven underwriting frameworks grounded in repeatable risk metrics—like DSCR, LTV, occupancy trends, and sensitivity-tested NOI. These frameworks don’t replace judgment, but they anchor it, so decisions are based on shared logic rather than individual memory. The result? Faster alignment, fewer bottlenecks, and more predictable outcomes.
In commercial real estate, yesterday’s data has a short shelf life. Yet, too many underwriting models still rely heavily on trailing 12-month financials, dated comps, and assumptions pulled from market snapshots that are no longer applicable. When volatility is the norm, not the exception, this backward-looking approach can lead to significant mispricing of risk.
Consider what happens when interest rates jump 100+ basis points between the LOI and the credit memo. Or when a comp set includes leases signed before a major anchor tenant vacated the submarket. Without real-time context, even the best-built model can quickly lose relevance.
Moreover, the challenge isn’t just access—it’s also accuracy and timing. Delays in interpreting market shifts or relying on stale indicators can lead to slower reactions and distorted projections, particularly in dynamic markets where fundamentals shift quarter to quarter.
What smart lenders do: They integrate real-time data streams—from live rent comps and market vacancy trends to interest rate forecasts and regional economic signals—directly into their underwriting. They utilize dynamic models that adjust in response to shifting market inputs, enabling more accurate sizing, improved pricing, and proactive risk identification.
Recent headwinds that are compounding risk and slowing decisions even further.
According to the Mortgage Bankers Association, $957 billion, or roughly 20% of all outstanding commercial and multifamily mortgages, are set to mature in 2025, up from $929 billion in 2024. This is only the beginning. Industry analysts project a steady rise in maturities through 2027, creating a years-long wave of refinancing pressure across office, multifamily, retail, and industrial sectors.
Refinancing those loans isn’t the simple rollover it once was. Deals that were sized at peak valuations and originated during the low-rate environment of 2020-2021 now face a very different set of underwriting assumptions:
What does that mean for lenders? That creates a different kind of challenge: bandwidth. Every legacy loan that requires re-underwriting for extension, modification, or restructuring pulls focus away from new deal flow, slowing origination, stretching teams thin, and increasing the opportunity cost of inaction.
What smart lenders do: They use centralized dashboards to track upcoming maturities, run quick stress tests across rate and valuation scenarios, and flag loans that are likely to need attention months in advance. With tools like Blooma, lenders can segment their portfolios, identify files requiring early intervention, and avoid bottlenecks, keeping their underwriting engines focused on opportunity, not just obligation.
Prominent submarkets, such as Class B office or legacy strip centers, are now in flux. With shifting occupancy patterns and post-COVID occupation trends, underwriting these assets requires more than standard projections. Deals now hinge on “what-if” scenarios: Can it be converted? What’s the repositioning timeline? How sensitive is it to cap rate compression?
Lenders who treat transitional assets like traditional office or retail risk are getting blindsided. Instead, agile firms are running multiple outcome scenarios, pairing performance stress tests with external market signals (e.g., absorption pace, trade area rents, construction deliveries).
What smart lenders do: They deploy a modular underwriting model where key assumptions (e.g., rent, NOI, occupancy) can be stress-tested across scenarios. They tie in regional indicators—like vacancy trends or office-usage data—to catch emerging shifts early, ensuring diligence reflects on-the-ground realities.
Insurance is no longer a minor P&L line item. Premiums for U.S. commercial properties have surged 88% over the past five years, according to JLL. Deloitte forecasts the average monthly cost to insure a commercial building could reach $4,890 by 2030, up from $2,726 in 2023—an 8.7% compound annual growth rate. In high-risk states that face extreme weather events, those numbers can be even more alarming.
These rising costs aren’t abstract, they bite. In wildfire-prone California, insurance premiums surged by as much as 40% in 18 months, posing a threat to the viability of both affordable housing and commercial complexes. And insurance isn’t just more expensive—it’s sometimes unavailable. Insurer pullbacks in high-risk zones result in inadequate coverage, leaving collateral exposed and underwriting gaps unaddressed.
What smart lenders do: They proactively model regional climate exposures—from wildfire to flood zones—then bake current insurance costs and projected increases directly into their underwriting. With tools like Blooma, they can surface these risks early through portfolio stress testing by automatically integrating third-party hazard data, mapping geographic exposure, and flagging underinsured assets during diligence.
The most successful CRE lenders in today’s environment aren’t just closing deals faster—they’re doing it with greater confidence and less risk. They’ve addressed the legacy friction points. They’ve adapted to new headwinds. And they’ve built workflows that are built for what CRE looks like now, not what it looked like five years ago.
The bottlenecks are real. But they’re solvable. And for lenders ready to lead the next cycle, now’s the time to clear the path.
Not sure where to start? That’s normal.
We talk to lenders every day who are looking to improve, but don’t know where to start. Blooma helps CRE lenders eliminate bottlenecks, surface better deals faster, and stay in control no matter what the market throws at you. Our team can walk you through what to look for, and AI can help ease those bottlenecks.
Or, if you’re ready to talk strategy, reach out here and we’ll walk you through what a modern CRE underwriting process can really look like.