Key Takeaways
Many CRE lenders still depend on Excel for underwriting, a tool powerful in theory but fragile when used for high-volume, high-stakes decisions. And for large lenders, the scale is intense. Handling one to three loans per month may feel busy. Now picture evaluating 10 - 20, or even 30 - 50, every single month. Most will not advance, but each still requires detailed analysis, model updates, and documentation. That volume alone turns spreadsheets into a bottleneck waiting to happen.
Small issues in Excel can distort cash flow, alter DSCR calculations, or misstate NOI, ultimately influencing multi-million-dollar decisions. Research from the European Spreadsheet Risks Interest Group (EUSPRIG) shows that roughly 80 - 90% of spreadsheets contain significant errors. These issues rarely announce themselves. Excel will happily accept incorrect inputs, outdated assumptions, or broken formulas without alerting the user.
This article explores the most common Excel errors underwriters encounter, why they happen, and how automation eliminates the risks they create.
Underwriting requires pulling information from many sources: rent rolls, operating statements, T-12s, borrower financials, comp data, and third-party reports. Most of this data is manually keyed or pasted into Excel, and that manual work is the real problem.
Sure, “human error” sounds obvious. But the issue isn't that analysts are careless; it’s the sheer volume and repetition involved. When you're manually aligning hundreds of rows across tabs while juggling dozens of deals, even experienced analysts will occasionally misplace a value or paste data into the wrong column.
Common error patterns include:
Excel offers no guardrails to catch mistakes like these. A single miskeyed number can ripple across a model and remain undetected until a late-stage credit committee review, or worse, after closing.
Formulas are where Excel’s power becomes its biggest weakness. Underwriting models often span dozens of tabs, link multiple sheets, and rely on nested formulas referencing other nested formulas. Even small changes can break logic in ways that are hard to detect, and Excel does not warn the analyst when it happens.
Common formula-related issues include:
One of the most dangerous problems is the misplaced absolute reference (“$”). A single incorrect anchor can inflate DSCR, debt yield, or LTV, and Excel will quietly accept the faulty math without alerting the user. These errors often remain hidden until a late-stage review or, in the worst cases, after a deal is already approved.
Real-world examples reflect how damaging spreadsheet formula errors can be. Well-documented “Excel horror stories” include:
These aren’t just extreme edge cases. CRE underwriting teams see smaller versions of this every day such as formula references that quietly break, logic that becomes outdated as models evolve, or calculations that get overwritten during analysis. The impact can be significant:
Auditing large models is slow and rarely perfect. Even line-by-line reviews may miss buried logic flaws or hard-coded assumptions from long-retired versions of a template. As underwriting volume increases, the time spent on error remediation grows, consuming analyst capacity and slowing decision-making during periods when lenders need speed the most.
Underwriting requires collaboration. Analysts start the model, underwriters refine it, credit teams review it, and committees finalize decisions. Excel was never built for this level of collaboration.
Common issues include:
No audit trail, making it impossible to trace who changed cap rates, rent comps, or expense ratios.
Regulators consistently warn that manual spreadsheet workflows lack accountability. Without permissions, tracking, or history, lenders face operational and compliance risk if a model’s logic is challenged later.
McKinsey’s research on workflow digitization also highlights that institutions relying heavily on Excel introduce unnecessary friction, inconsistent outcomes, and slower decisioning.
From moving between different tabs and data vendors to portfolio monitoring with real-time updates, here is how high-volume lenders utilize automation as a strategy in their workflow.
Blooma’s Origination Intelligence automatically extracts financials, property data, and borrower inputs, removing manual data entry altogether. With best-in-class CRE data providers integrated directly into the platform, Blooma delivers validated numbers instantly.
This helps teams:
NOI, DSCR, LTV, and debt yield calculations become consistent across every deal, every analyst, and every template.
Blooma’s Portfolio Intelligence replaces fractured spreadsheet sharing with a real-time, centralized workspace. Every deal lives in one platform, with one version, with all assumptions aligned.
Benefits include:
Collaboration becomes structured and transparent which is the opposite of Excel’s ungoverned environment.
Wouldn’t it be easier for your team to monitor in real time, pre- and post-deal? Excel freezes time. Blooma moves with it. Portfolio Intelligence continuously updates:
And when anything shifts, Blooma generates proactive alerts. Instead of waiting for quarterly or annual portfolio reviews, lenders get immediate visibility into emerging risks. This aligns with Blooma’s mission to help clients “anticipate risks before they happen”.
CRE underwriting is becoming more complex, more data-heavy, and more competitive. Excel cannot scale with this evolution.
Automation offers the scalability and speed institutions need:
The Blooma platform acts as an intelligence layer that plugs into existing processes and infrastructure, allowing institutions to modernize without ripping out core systems.
Lenders who adopt AI-powered underwriting now will be positioned to move faster, outcompete peers, and protect portfolio quality in a dynamic CRE environment.
Excel may always have a place in finance, but its role in core underwriting is diminishing. The risks, from silent formula errors to inconsistent assumptions, grow exponentially as deal flow increases.
Automation changes that. With Blooma’s Origination Intelligence and Portfolio Intelligence, lenders move from reactive spreadsheet cleanup to proactive, data-driven decisioning built on clean, consistent, timely information.
See how Blooma can help you eliminate manual errors and modernize your underwriting process. Book your demo today.