Why Better Upfront Data is the Secret to Faster Closings

Anyone who has spent even a week in mortgages knows the appraisal revision request headache. You are right there at the finish line, ready to close the loan, when everything grinds to a halt. Usually, it is something tiny like a blurry photo, a typo, or a vague comment about a boundary line that pulls the whole loan back to square one. It is frustrating and a momentum killer.

To an outsider, a revision request looks like a minor “to-do” item. However, for those in the thick of it, it’s a pipeline killer.

Cost of the Review Loop

When an appraisal gets kicked back for a revision, it rarely goes to the top of the pile. Instead, it usually sits in a secondary queue while everyone else waits. The underwriter has to freeze the file, the Loan Officer has to break the news to a frustrated borrower, and that lock-in clock just keeps ticking away.

The stakes are actually much higher than people think. Around 30% of appraisals need at least one fix [1]. When you realize how much time each of those back-and-forth cycles adds to the process, you can see the damage it does. It eats into your efficiency and drives up the cost to close, which is already a huge pain point across the industry right now [2].

Why are we still doing this?

Most revisions happen for avoidable reasons. According to feedback from review desks and industry analysts, the most common culprits are:

  • Missing commentary: The reasoning behind an adjustment isn’t clear to the reviewer.
  • Inconsistent data: The basement square footage on page one doesn’t match page three [1].
  • Lack of support: Underwriters needing more proof for comparable sales in complex markets [3].

These aren’t usually errors of judgment; they are errors of initial data collection.

High-Quality Data from Day One

One of the most effective ways to reduce revisions isn’t to ask appraisers to work faster. It’s to give them and the underwriters better data right from the start of the process. This is what we call “moving left.” If you get the property details right at the inspection stage, the rest of the dominoes fall into place.

To actually move the needle, “good data” needs to be three things:

  1. Complete: Every characteristic, from the HVAC age to the exact condition of the roof, is captured the first time.
  2. Structured: Instead of messy handwritten notes, the data is digital and standardized, so it plugs directly into the report without manual entry errors.
  3. Verified: Using professional inspectors to gather the “ground-truth” details of a property.

How ValINSPECT Helps You Win

We designed ValINSPECT as one solution to help solve the workflow gaps that often lead to those avoidable little errors. Our goal is to make the process smoother for everyone. By providing professional and structured property inspections, whether they are in person or virtual, we ensure appraisers start their work with data that is both accurate and exhaustive.

When an underwriter opens a report backed by ValINSPECT, they generally find everything they need right away, because the data is already organized and verified, the usual clarifying questions often disappear. This shifts the entire appraisal process from a cycle of back-and-forth updates into a clear and streamlined approval.

The Big Picture

Revision cycles do not have to be a standard part of your day. By focusing on high-quality data collection from the very start, you can create a much better experience for your team and your borrowers. It is a simple way to protect your margins and keep your pipeline moving confidently toward the closing table.

Want to see how ValINSPECT can help you hit a “first-time final” more often? Learn more here: ValINSPECT | Valligent, a Veros Software Company

Sources:

  1. Appraisal Buzz, “Common Causes for Appraisal Revisions,” (Industry Data Survey).
  2. Mortgage Bankers Association (MBA), “Annual Mortgage Cost-to-Close Trends and Performance Report.”
  3. STRATMOR Group, “Insights on Appraisal Turn Times and Secondary Market Quality Control.”

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