How Long Does Underwriting Take in Commercial Real Estate Lending

Key Takeaways:

• CRE underwriting typically takes 1 to 4 weeks, depending on deal complexity and documentation.
• Automated platforms can reduce underwriting time from weeks to days for standard transactions.
• Factors like property type, sponsor strength, and third-party reports significantly influence timelines.
• Lenders can increase throughput and reduce risk using intelligent underwriting tools like Blooma.
  Human-AI collaboration helps teams scale without sacrificing credit standards.

In today’s commercial real estate environment, speed is essential. Whether you're competing for a time-sensitive acquisition or managing a high-volume pipeline, the ability to move quickly can be the difference between winning and losing a deal. That’s why so many lenders ask a simple but important question: how long does underwriting take?

In CRE lending, underwriting refers to the process of assessing the borrower’s creditworthiness and evaluating the risk profile of the loan. This includes reviewing the property, the sponsor’s financials and experience, current market conditions, and required third-party reports. The process must be thorough, but it also needs to be efficient.

Blooma supports this goal by helping lenders complete underwriting faster without compromising accuracy. In this article, we’ll explore typical CRE underwriting timelines, the factors that influence speed, and how automation is changing the game for modern lenders.

Typical Underwriting Timelines in CRE

Underwriting usually takes between one and four weeks. Timelines vary based on asset type, deal complexity, and the lender’s internal workflow.

Straightforward deals involving stabilized properties and experienced sponsors may be completed in 5 to 10 business days. In contrast, construction loans, bridge financing, and deals with complex legal structures often require extended review periods.

Manual workflows can also create bottlenecks. Lenders using spreadsheets, email, and disconnected processes typically experience longer cycle times. By comparison, lenders leveraging intelligent automation can significantly accelerate underwriting.

Key Factors That Influence Underwriting Speed

Deal Complexity
The asset type directly affects the underwriting timeline. Stabilized, income-producing properties are generally faster to evaluate. Transitional assets or developments require deeper analysis due to higher risk exposure. The loan’s purpose also affects complexity. Refinances are usually simpler to underwrite than construction or repositioning loans.

Borrower and Sponsor Profile
CRE borrowers are often sponsor groups or investment entities. Underwriting moves faster when sponsors have institutional experience, strong financials, and transparent ownership structures. Complex partnerships or limited documentation can slow things down.

Document Completeness
Missing or inconsistent documentation is a major cause of delay. Lenders need full access to rent rolls, T12s, financial statements, and third-party reports in a usable format. The more complete the package, the sooner the evaluation can begin.

Third-Party Reports
Appraisals, environmental reports, and property condition assessments are essential to the underwriting process, but they depend on external vendors. Scheduling delays or red flags within these reports can significantly extend the timeline.

Internal Workflow and Technology
Without centralized systems or automation tools, underwriters waste time locating documents, re-keying data, and coordinating across teams. Platforms like Blooma streamline the process by automating data extraction and surfacing real-time insights so teams can focus on higher-value tasks.

How Automation Accelerates Underwriting Timelines

Automation has become essential for lenders operating in a competitive, fast-moving market. Blooma’s underwriting platform enables lenders to evaluate deals with speed and confidence.

Instead of manually reviewing financials, Blooma uses AI to extract, analyze, and summarize key data. This reduces the burden of repetitive tasks and allows teams to prioritize strategy over administration.

Blooma supports end-to-end deal analysis, asset and sponsor evaluation, and pipeline management in a single platform. Machine learning models offer real-time insights into comparables, risk, and market trends, allowing for faster, more informed decision-making.

On average, lenders using Blooma can underwrite up to four times more deals without increasing headcount, creating a scalable foundation for growth.

How to Improve Underwriting Efficiency Without Compromising Quality

Here are seven best practices that align with Blooma’s automation-first approach:

1. Standardize Documentation Checklists
   Provide borrowers and brokers with clear, consistent checklists that include T12s, rent rolls, offering memorandums, entity documents, and third-party reports. This ensures complete submissions and reduces review delays.
2. Use Automated Scoring Tools for Pre-Screening
   Platforms like Blooma quickly assess deals using criteria such as sponsor history, DSCR, and NOI. Low-risk deals can be fast-tracked, while more complex cases are flagged for additional review.
3. Segment Low-Risk and High-Risk Loans
   Establish tiered workflows to streamline straightforward transactions while reserving manual review for complex loans. This helps teams stay focused and manage pipelines more efficiently.
4. Automate Workflow Tracking and Audit Trails
   Centralized platforms track document status, reviewer assignments, and decision points in real time. This improves transparency, ensures compliance, and prevents handoff-related delays.
5. Extract and Spread Financials Automatically
   AI can parse rent rolls, income statements, and other documents into clean, standardized financial spreads. This speeds up analysis and frees underwriters to focus on risk and strategy.
6. Leverage Live Market Data and Comparables
   Real-time market insights such as cap rates, comps, and vacancy trends can be integrated into underwriting tools to improve accuracy and eliminate the need for manual data collection.
7. Use AI to Detect Risk Flags Early
   Blooma can identify inconsistencies in submitted documents, such as mismatched figures or missing data. Early flagging reduces the need for rework and improves overall analysis quality.

Why These Strategies Work

• Standardized inputs reduce delays from incomplete submissions
• Automated triage focuses human effort on deals that truly require it
• Tiered workflows improve team efficiency
• Workflow automation ensures consistency and accountability
  Real-time market data and AI flag potential issues before they become bottlenecks
• Overall cycle times shrink without sacrificing credit standards

By combining these strategies, lenders move from asking how long does underwriting take to delivering decisions within days.

The Future of Underwriting: Human + AI

AI doesn’t replace underwriters. It enhances them. Automation handles repetitive tasks, while humans focus on nuanced risk analysis and strategic decision-making.

This hybrid approach allows lenders to increase deal velocity without taking on additional risk. It leads to stronger performance, faster closings, and more satisfied borrowers.

Speed, Risk, and Opportunity

CRE underwriting timelines are shaped by many variables, but they don’t have to be unpredictable. With the right mix of process improvements and intelligent automation, lenders can close faster and more confidently.

Blooma helps lenders modernize underwriting without compromising rigor. Whether you’re scaling your pipeline or trying to stay competitive, Blooma can help you move faster and smarter.

Ready to accelerate your underwriting process?
Schedule a demo with Blooma to see how automation can transform your operations.