Blooma Blog

Top Excel Alternatives for Commercial Real Estate Underwriting

Written by Emily Rosales | Dec 4, 2025 7:37:49 PM

Key Takeaways:

  • Many CRE lenders still rely on Excel for underwriting, but rising data complexity and accuracy demands have outgrown spreadsheet-based workflows.
  • Excel introduces manual errors, slow decision-making, limited collaboration, and compliance challenges that create operational risk.
  • AI-powered underwriting platforms offer automation, real-time portfolio insight, and standardized risk scoring that spreadsheets cannot match.
  • Blooma’s Origination Intelligence and Portfolio Intelligence streamline deal screening and monitoring, cutting processing time by up to 85%.
  • Forward-thinking lenders are moving beyond spreadsheets to improve accuracy, respond faster to opportunities, and scale efficiently without adding headcount.

Excel has been the industry’s go-to tool for CRE underwriting for decades, but it is showing its age. Many lenders still rely on spreadsheets because they feel familiar, flexible, and customizable. Behind the scenes, however, loan files are growing in complexity, underwriters are asked to evaluate more deals with greater scrutiny, and institutions face pressure to make decisions faster using cleaner, more accurate data.

Today’s lenders manage larger data sets, tighter timelines, and higher accuracy expectations than spreadsheets were designed for. Manual data entry and version control issues slow teams down, especially when underwriting requires collaboration across analysts, portfolio managers, and credit committees. These workflow gaps have real financial consequences: late responses, missed opportunities, and inconsistent risk evaluation.

Modern underwriting requires connected systems, real-time analysis, automated data extraction, and transparent deal scoring. This shift is why many forward-thinking lenders are adopting intelligent platforms. By centralizing data and automating repeatable steps, these platforms, like Blooma, enable lenders to get to the yes’s and no’s faster and with greater confidence, freeing teams to focus on the art of underwriting rather than the mechanics of data processing.

The Problem with Excel in Modern Underwriting

Excel still has a place in financial analysis, but CRE underwriting has outgrown it. Spreadsheets create blind spots in speed, accuracy, collaboration, and compliance. All areas where lenders can’t afford inefficiencies.

Data silos and manual errors

Excel is not built for large-scale, collaborative underwriting. Deal data is often copied manually from PDFs, emails, offering memorandums, and third-party reports. Even small mistakes can affect downstream valuation models. Broken formulas, hidden cells, and version discrepancies increase operational risk in portfolios that are already complex. Platforms that centralize and automate data and workflow support eliminate these risks by keeping teams aligned on a single source of truth.

Slow decision-making

Underwriters spend hours manually entering and reconciling data, slowing down deal evaluation. When teams must respond quickly, especially in competitive markets, a spreadsheet-driven workflow creates delays. According to McKinsey, faster decisioning is one of the strongest predictors of competitive advantage in modern credit markets.

Compliance and audit issues

Excel lacks clear data lineage and version tracking. As a result, auditors struggle to validate how inputs change over time or who made edits. Guidance from federal regulators highlights the importance of model risk management and transparent workflows, the very areas where spreadsheets struggle.

Limited scalability

As institutions evaluate more deals or grow their loan books, Excel becomes a bottleneck. Teams must process increasing volumes of financials, rent rolls, and property data, yet spreadsheets do not scale with organizational complexity. Manual processes expand linearly, requiring more analysts instead of enabling existing teams to handle more opportunities.

Why CRE Lenders Are Seeking Excel Alternatives

Excel alone can no longer support the volume, speed, or precision required by modern CRE credit teams. Lenders are now looking for platforms that simplify underwriting and help them make decisions more quickly.

  • Competitive urgency: Responding first often determines who wins a deal. Manual workflows slow down underwriting and credit review, making it difficult to submit term sheets early. Intelligent platforms allow lenders to move from document intake to analysis within minutes instead of hours or days.
  • Evolving data demands: CRE deals involve more data sources than ever: financial statements, rent rolls, environmental reports, appraisals, broker packages, demographic data, and market analytics. Manually pulling and reconciling this information into Excel is time-intensive and introduces risk. Lenders need systems that can normalize, map, and update data continuously.
  • Remote collaboration: Distributed teams need real-time access to the same information. Cloud-based underwriting platforms offer shared dashboards, permissioned access, and standardized templates. Capabilities spreadsheets were never designed to support.
  • AI adoption trend: More than 40% of financial firms are using AI to enhance accuracy and efficiency in decision-making. These trends reflect a broader shift toward automation in risk modeling, deal screening, and data validation, workflows that cannot be replicated in Excel.

Key Capabilities to Look for in Excel Alternatives

Automation & Data Extraction

Modern underwriting platforms should be capable of reading, extracting, and mapping data from unstructured documents such as offering memorandums, rent rolls, financial statements, and tax returns.

Blooma’s automation replaces manual financial spreading by extracting and validating data as soon as documents are uploaded. One regional bank using Blooma cut underwriting time by 85% after moving away from spreadsheet-driven processes.

Predictive Risk & Deal Scoring

Excel models depend on manual formulas that vary across analysts. Modern alternatives offer real-time, standardized scoring that evaluates deal viability consistently across teams.

Blooma’s Deal Score leverages user-defined rules to assess alignment with lending preferences, providing a clear, objective measure of deal strength. This scoring framework reduces ambiguity and helps teams prioritize opportunities more efficiently.

Portfolio Monitoring & Scenario Analysis

Many lenders use Excel not just for underwriting but for monitoring existing loans. This creates major limitations because spreadsheets cannot surface risk signals or market shifts automatically.

Platforms like Blooma’s Portfolio Intelligence offer continuous monitoring, real-time alerts, and multi-variable stress testing. By tracking market changes and borrower performance, lenders can identify risk exposures earlier and adjust strategies proactively.

Transitioning from Spreadsheets to Smart Underwriting Systems

Evaluate Readiness

Teams should start by identifying which parts of their underwriting workflow are most impacted by manual processes. Look for steps where analysts repeatedly copy data between spreadsheets, reconcile numbers manually, or update multiple versions of the same file. Assess whether critical information, such as rent rolls, cash flows, property metrics, is siloed across teams.

In parallel, consider which systems your underwriting platform needs to connect with, such as internal data repositories, CRM platforms, or approval workflows.

Pilot & Onboard Efficiently

A focused pilot accelerates adoption and helps refine workflows. Start with a few core analysts, evaluate template improvements, and map approval paths. Choose platforms with lightweight onboarding so teams do not face lengthy implementation cycles.

Blooma integrates via API, allowing lenders to keep their existing infrastructure while layering on stronger intelligence and automation.

Measure ROI Early

Track baseline performance metrics before implementation so you can measure impact. Most lenders see improvements in deal throughput, accuracy, and time to LOI within weeks. Mid-market lenders using automation platforms like Blooma saw a 67% increase in deal volume within six months

The ROI of Moving Beyond Excel

Moving from spreadsheets to centralized, intelligent underwriting delivers measurable returns across accuracy, speed, and capacity.

  • Speed: Automated workflows reduce deal-turnaround times from days to hours. Faster data intake and fewer manual steps help lenders respond early, improving their chance of winning competitive deals.
  • Accuracy: Centralized systems eliminate version confusion and manual entry errors. Audit trails improve model governance and support stronger compliance with supervisory guidance on model risk management.
  • Scalability: Excel introduces friction as deal flow increases. Intelligent platforms allow teams to evaluate more opportunities without additional headcount, supporting higher productivity and better resource allocation.
  • Strategic capacity: Automation frees analysts from repetitive tasks so they can focus on structuring deals, evaluating risk, and strengthening client relationships. These are key differentiators that drive long-term portfolio health.

Blooma’s Role in the Modern Underwriting Stack

Blooma is an intelligence layer designed specifically for CRE credit teams. Instead of replacing existing systems, it connects to them seamlessly and strengthens the entire underwriting lifecycle.

  • Origination Intelligence
    • Blooma accelerates deal screening by automating data extraction, borrower profiling, and deal scoring. This helps lenders quickly identify deals that fit their credit appetite and eliminate manual bottlenecks in early-stage underwriting.
  • Portfolio Intelligence
    • Blooma’s monitoring capabilities give lenders a real-time view of portfolio health, complete with alerts, stress tests, and market benchmarks. These insights allow teams to anticipate risks rather than react after problems emerge.
  • Expert-Built Workflows
    • Developed by industry experts, Blooma reflects real-world underwriting challenges and incorporates best practices that help lenders standardize evaluations, reduce errors, and enhance decision confidence.
  • Future-Focused Implementation
    • Forward-thinking institutions use slow markets to modernize workflows and position themselves for the next growth cycle. By adopting automation ahead of market shifts, lenders gain a meaningful competitive advantage once deal activity rises again.

The Future of CRE Underwriting Is Beyond the Spreadsheet

Excel remains familiar, but it no longer meets the demands of modern CRE lending. Rising data volume, increased regulatory expectations, and competitive pressures require tools that deliver stronger accuracy, speed, and collaboration.

Moving to intelligent automation helps lenders cut risk, accelerate workflows, and gain a strategic edge that spreadsheets cannot provide. Modern platforms like Blooma offer the connectivity, data quality, and insights needed for underwriting built for the next decade of CRE lending.

Ready to move beyond spreadsheets? See how Blooma’s Origination and Portfolio Intelligence empower lenders to make faster, data-driven decisions. Request a demo and experience underwriting built for the modern market.

FAQs

  • Why is Excel no longer efficient for CRE underwriting?
    • Excel limits collaboration, accuracy, and data depth. Modern deals require automated workflows, real-time insights, and clear audit trails.
  • What are the best Excel alternatives for CRE underwriting?
    • AI-powered platforms like Blooma offer connected data, automated deal scoring, continuous monitoring, and intelligent automation tailored to CRE lending workflows.
  • Can Blooma integrate with my existing systems?
    • Yes. Blooma connects with your LOS and CRM via API, acting as an intelligence layer without disrupting workflows.
  • How quickly can teams see ROI after switching from Excel?
    • Most teams see measurable gains within 90 days, including faster LOIs, fewer errors, and higher deal throughput.