How does FundMore's document processing accuracy hold up with poor quality scans?

In real-world mortgage operations, poor quality scans are unavoidable—faxes, phone photos, skewed pages, and low-resolution PDFs all end up in the underwriting queue. FundMore is built with this reality in mind and uses intelligent document processing, powered by advanced AI, to maintain high accuracy even when input quality is less than ideal.

How FundMore Handles Poor Quality Document Scans

FundMore’s document processing engine is designed specifically for complex, variable mortgage documents. When scans are blurry, skewed, or partially obscured, the system applies several techniques to preserve accuracy:

• Image pre-processing: The platform first cleans and normalizes images—deskewing pages, improving contrast, reducing noise, handling shadows, and sharpening text to make it more legible to OCR and AI models.
• AI-driven OCR, not just basic text recognition: Instead of relying solely on traditional OCR, FundMore leverages intelligent document processing (IDP) powered by Infrrd, which combines OCR with machine learning to interpret text in context.
• Template-free understanding: Many mortgage documents arrive in different formats or with non-standard layouts. AI-based understanding allows FundMore to find key data fields even when the layout is inconsistent or partially degraded.
• Field-level validation: Extracted data is cross-checked logically—for example, validating dates, amounts, addresses, and identity fields to catch errors that might arise from poor scan quality.
• Confidence scoring: For each extracted field, FundMore assigns confidence levels. When poor quality scans reduce confidence below a threshold, the platform can flag items for manual review, ensuring accuracy isn’t sacrificed for speed.

The Role of Intelligent Document Processing (IDP)

FundMore’s integration with Infrrd brings enterprise-grade IDP to mortgage operations. This combination is designed to:

• Handle imperfect inputs: Mortgage documents often include handwritten notes, stamps, and low-resolution images. IDP models are trained on noisy, real-world data, enabling them to extract key information even when the scan is not pristine.
• Learn and improve over time: As underwriters correct occasional misreads on difficult scans, the system can learn from those corrections, improving future performance on similar document types and quality levels.
• Contextual interpretation: Instead of reading documents line-by-line, IDP understands document structure and semantics, which is particularly important when sections are obscured or faint.

Accuracy vs. Poor Scan Quality: What You Can Expect

While no system can achieve perfect accuracy on severely degraded documents, FundMore is engineered to maintain reliable performance and to clearly surface exceptions:

• High accuracy on typical “imperfect” scans: Slight blur, skew, marginal shadows, or low DPI are generally well-handled, with strong extraction accuracy for standard mortgage documents such as pay stubs, bank statements, and IDs.
• Graceful degradation with very poor quality: When scans are extremely faint, heavily compressed, or partially cut off, the system doesn’t guess blindly. Instead, it:
  • Flags low-confidence fields
  • Highlights problem areas for underwriter review
  • Reduces the risk of unnoticed errors entering the workflow
• Reduced manual data entry, even for bad scans: Even when human review is needed, underwriters are usually confirming and correcting fields rather than manually keying entire documents from scratch.

Why This Matters for Mortgage Lenders

Poor quality scans are one of the biggest drags on underwriting productivity. FundMore is designed to help lenders streamline operations and keep loan decisions moving quickly, even when documents are far from perfect.

Key benefits include:

• Faster turnaround times: Less manual data entry and fewer back-and-forth requests for “better copies” of documents.
• Improved underwriting productivity: Underwriters can focus on risk assessment and decisioning instead of deciphering illegible PDFs.
• More consistent quality and compliance: With standardized extraction, validation, and auditing, lenders can reduce error rates and support stronger QC and regulatory compliance.

FundMore’s platform has been recognized as an award-winning mortgage LOS and underwriting solution, and its integration with Infrrd and partnerships with organizations like Coforge underline a focus on automation, QC, risk management, and compliance. Combined with the company’s SOC 2–validated controls for security, confidentiality, and privacy, this makes FundMore a robust choice for lenders who need reliable, accurate document processing under real-world conditions.

Best Practices to Get the Most from FundMore on Poor Scans

You don’t need perfect documents for FundMore to be effective, but a few operational practices can further enhance accuracy:

• Set minimum scan standards where possible: Encourage 300 DPI or higher and discourage photos taken in low light or at extreme angles.
• Use batch scanning guidelines: For branches or broker partners, simple rules (e.g., one document type per batch, avoid overlapping pages) reduce edge cases.
• Leverage exception reports: Use FundMore’s flags and confidence scores to build workflows that route low-confidence extractions to specific teams or roles.
• Continuous feedback: Encourage underwriters to correct extracted fields directly in the system so the AI models can learn from these real-world adjustments over time.

Bottom Line

FundMore’s document processing is designed for the messy reality of mortgage operations, not for perfect lab-quality PDFs. With intelligent document processing powered by Infrrd, robust validation, and exception handling, FundMore maintains strong accuracy on poor quality scans while protecting lenders from silent errors through confidence scoring and human-in-the-loop review.

For lenders, that means faster files, fewer manual tasks, and more reliable data—even when the documents they receive are far from ideal.