AI
Automation
IDP

The Only Way to Do Closing Disclosure Right (And Why it Matters)

Author
Priyanka Joy
Updated On
May 23, 2025
Published On
May 23, 2025
A Closing Disclosure (CD) is a critical five-page document that provides the final details about a loan.
With increasing compliance pressure and tighter timelines, automating the Closing Disclosure balancing is essential.
Infrrd’s CD Balancer automates and simplifies the verification and reconciliation of figures between the Loan Estimate (LE) and Closing Disclosure (CD) documents.
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Every time a loan closes, someone spends hours manually checking if the Loan Estimate (LE) and Closing Disclosure (CD) match, down to the last cent.

One missed fee or a wrong decimal? That’s not just a small mistake, it’s a compliance nightmare. And it’s not rare. It happens in nearly every single loan origination cycle. Reports say that 70% of post-close errors stem from mismatched fees and missing data between the LE and CD.

According to the Consumer Financial Protection Bureau’s (CFPB) report titled How Mortgages Change Before Origination, nearly 9 out of 10 mortgages go through at least one revision, whether it’s a revised Loan Estimate (62%) or a corrected Closing Disclosure (49%).

Moreover, data from the Federal Reserve found that Closing Disclosure violations under Regulation Z were among the most common compliance problems. These included common errors such as not showing the full finance charges or listing the wrong service providers. 

If you’re looking to speed up your loan origination process and steer clear of compliance headaches, there’s one silent killer you need to eliminate: manual Closing Disclosure Balancing.

Read till the end, you’ll have a clear, step-by-step guide to doing it the right way.

What Is a Closing Disclosure?

A Closing Disclosure (CD) is a critical five-page document that provides the final details about a mortgage loan. It includes the loan terms, projected monthly payments, fees, and other costs associated with the loan. This document is given to the borrower at least three days before closing, and it must accurately reflect the terms agreed upon during the loan process.

Before a borrower sees the CD, they typically receive a Loan Estimate (LE), a document outlining expected costs. The Closing Disclosure is the final version, and any major discrepancies between the two can cause compliance issues and potential delays.

What Is a Closing Disclosure (CD) Balancer?

A CD Balancer is a tool that ensures the fees and figures in the Loan Estimate match those in the Closing Disclosure, within compliance guidelines. It checks tolerance thresholds for each section of the CD, ensuring that lenders don’t overcharge borrowers and that all third-party fees, lender fees, and title charges are correctly disclosed and aligned with what was initially quoted.

Each section of the CD (like Sections A, B, and C) has specific tolerances. For instance:

  • Section A fees must match exactly. Any overages must be paid out-of-pocket by the lender.

  • Section B fees are allowed a 10% cumulative tolerance, meaning the total can’t exceed the estimate by more than 10%.

The Cost of Manual Closure Disclosure Balancing 

The Only Way to Do Closing Disclosure Right (And Why it Matters)

Manual CD balancing is a tedious, error-prone process that involves checking multiple fields across different documents and systems. With high volumes of loans and pressure to close quickly, even a small mismatch can lead to:

  • Compliance violations

  • Costly re-disclosures

  • Delays in funding

By automating this process with Intelligent Document Processing (IDP), lenders can drastically reduce errors, ensure consistency, and speed up the closing process, without needing to manually open or compare every document.

Infrrd’s Closing Disclosure (CD) Balancer: Step-by-Step Breakdown

Infrrd’s CD Balancer automates and simplifies the complex task of verifying and reconciling the numbers between the Loan Estimate (LE) and the Closing Disclosure (CD) documents. Here’s how the system works in detail:

The Only Way to Do Closing Disclosure Right (And Why it Matters)

Step 1: Document Upload 

Infrrd’s system starts by ingesting all relevant documents:

  • Loan Estimate (LE)

  • Lender’s Closing Disclosure

  • Title Company’s CD or Settlement Fee Sheet

Each document is automatically recognized, categorized, and prepared for comparison.

Step 2: Document Preprocessing 

At this stage, the LE, CD, and the title company’s CD are thoroughly scanned and automatically cleaned up for processing. This includes lighting, skew correction, cropping, rotation, and more.

Once pre-processing is complete, the documents are ready for accurate data extraction and validation.

Step 3: Section-Wise Data Extraction

Infrrd extracts data from the LE and CD documents using IDP. Both documents are structured with sections labeled A, B, C, etc. Each section has different compliance rules and tolerance levels: 

  • Section A (Zero Tolerance):
    The fees here (e.g., Application Fee) must match exactly between the LE and the CD. Even $1 over must be covered by the lender.

  • Section B (10% Tolerance):
    The cumulative total of fees in this section can’t increase by more than 10% between LE and CD. Any overages above this threshold must be absorbed by the lender.

  • Category C: No Tolerance Limit (Fees That Can Change Without Restriction):

These are fees that can increase or decrease between the Loan Estimate (LE) and the Closing Disclosure (CD) without violating any TRID tolerance rules. In other words, there's no set limit on how much these fees can change.

While not all sections appear in every document, Infrrd recognizes and extracts data from each relevant section and accounts for how each one should be treated for reconciliation.

Step 4: Comparison Across LE, Lender CD, and Title CD

Infrrd’s CD Balancer compares:

  • Values in the Loan Estimate

  • Values in the Lender’s CD

  • Values in the Title CD or Settlement Statement

  • System Business Values (from the lender’s LOS or internal platform)

For each line item, the system determines:

  • If the amount in the document matches the system record

  • If the LE and CD figures match within the allowed tolerance

  • If pay-to-party names align across documents

Step 5: Discrepancy Detection and Flagging

If any discrepancy is found, such as:

  • A mismatch in the fee amount

  • A missing value

  • A difference in the pay-to-play name

The system flags it with a visual icon. These icons indicate the nature of the discrepancy, e.g., amount mismatch or party mismatch, and guide the user to the exact field that needs review.

This ensures:

  • Quick identification of mismatched fees

  • Prevention of payment to incorrect parties

  • Avoidance of compliance issues during funding

Step 6: Pay-to-Party Validation

Infrrd also validates the pay-to-party, the entity that should receive each payment. For example:

  • If the Title CD says the payee is “ABC Title Agency,” but the system shows “XYZ Title,” it is flagged as a mismatch.

  • This prevents funding errors where the wrong party might receive funds due to a mismatch in documentation.

This is critical because funders rely on accurate payee information to disburse payments correctly.

Step 7: Visual Reconciliation Table

Infrrd provides a detailed, section-by-section view where:

  • Loan Estimate, Lender CD, and Title CD values are compared side by side

  • Business system values are shown in parallel

  • Discrepancy icons highlight issues immediately

Each section (A, B, C, etc.) is laid out clearly, helping users focus their attention where it matters most.

Step 8: Handling Missing Values

The system also identifies where values are present in the LE but missing in the CD, or vice versa. This includes scenarios like:

  • A fee was estimated but never charged

  • A fee is charged without being disclosed in the estimate

This comprehensive matching ensures full transparency and accuracy.

Step 9: Tolerance Handling (Upcoming Feature)

Currently, Infrrd’s CD Balancer matches values exactly between documents and system records. It does not yet incorporate tolerance thresholds, but this feature is planned for future development to automate compliance-level validations.

Step 10: Continuous Learning and Feedback Loop

While the tolerance logic is under development, the system already identifies discrepancies. Once users correct flagged issues, these corrections are captured and can be fed into a feedback loop to improve future accuracy.

Bonus: Document Flexibility

The system accepts CD-style documents even if they aren’t in the standard format, such as:

  • Title fee sheets

  • Settlement statements

  • Non-standard CD formats provided by title companies

Infrrd maps values from these documents to the appropriate CD sections (e.g., Section J) automatically.

Why Lenders Choose Infrrd’s Closing Disclosure CD Balancer

Infrrd’s CD Balancer isn’t just another automation tool. It’s a mortgage-specific, industry-trained IDP solution that understands the nuances of Closing Disclosures. It:

  • Works with Lender and Title CDs

  • Supports fee validation across sections

  • Flag tolerance breaches

  • Validates payee details

  • Supports future automation of tolerance-based compliance

In short, Infrrd eliminates the chaos of CD comparison, turning a manual headache into a touch-free, confidence-boosting automation flow.

In a Nutshell 

With increasing compliance pressure and tighter timelines, automating the Closing Disclosure balancing process is no longer optional. It’s essential.

Infrrd’s CD Balancer ensures your Loan Estimates, Closing Disclosures, and Title CDs match seamlessly, protecting your compliance, accelerating your closings, and giving your team one less thing to worry about.

Priyanka Joy

Priyanka Joy is a product writer at Infrrd who approaches automation tech like a curious detective. With a love for research and storytelling, she turns technical depth into clarity. When not writing, she’s immersed in dance, theatre, or crafting her next narrative.

FAQs

How does a pre-fund QC checklist help auditors?

A pre-fund QC checklist is helpful because it ensures that a mortgage loan meets all regulatory and internal requirements before funding. Catching errors, inconsistencies, or compliance issues early reduces the risk of loan defects, fraud, and potential legal problems. This proactive approach enhances loan quality, minimizes costly delays, and improves investor confidence.

What is a pre-fund QC checklist?

A pre-fund QC checklist is a set of guidelines and criteria used to review and verify the accuracy, compliance, and completeness of a mortgage loan before funds are disbursed. It ensures that the loan meets regulatory requirements and internal standards, reducing the risk of errors and fraud.

What is the advantage of using AI for pre-fund QC audits?

Using AI for pre-fund QC audits offers the advantage of quickly verifying that loans meet all regulatory and internal guidelines without any errors. AI enhances accuracy, reduces the risk of errors or fraud, reduces the audit time by half, and streamlines the review process, ensuring compliance before disbursing funds.

How to choose the best software for mortgage QC?

Choose software that offers advanced automation technology for efficient audits, strong compliance features, customizable audit trails, and real-time reporting. Ensure it integrates well with your existing systems and offers scalability, reliable customer support, and positive user reviews.

Why is audit QC crucial for mortgage companies?

Audit Quality Control (QC) is crucial for mortgage companies to ensure regulatory compliance, reduce risks, and maintain investor confidence. It helps identify and correct errors, fraud, or discrepancies, preventing legal issues and defaults. QC also boosts operational efficiency by uncovering inefficiencies and enhancing overall loan quality.

What is mortgage review/audit QC automation software?

Mortgage review/audit QC software is a collective term for tools designed to automate and streamline the process of evaluating loans. It helps financial institutions assess the quality, compliance, and risk of loans by analyzing loan data, documents, and borrower information. This software ensures that loans meet regulatory standards, reduces the risk of errors, and speeds up the review process, making it more efficient and accurate.

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