How to review loan applications faster while catching first-party fraud

For every hour a loan application sits in review, you are losing a prospective customer to the competition. Because speed matters to borrowers, the dilemma for lenders is to move faster and risk fraud, or move carefully and lose customers.

Over the last five years, the time spent reviewing loan applications has dropped significantly as OCR technology became the gold standard in bank statement reviews. Lenders can extract account numbers, balances, and transaction histories in seconds. This eliminates the bottlenecks that come with manual data entry, and speeds up income verification.

But what if the numbers on bank statements were changed after the document was created? What is the cost of lending to a customer on the basis of false information?

Borrowers often misrepresent information to appear more credit-worthy. This is a kind of first-party fraud, and it accounts for an estimated 69% of the $9.2b fraud risk exposure in the automotive lending industry (Source: PointPredictive). The most common way that borrowers commit first-party fraud is by altering numbers on their bank statements, pay stubs and tax returns.

This article explains how to build a complete document verification stack that extracts key information from documents to speed up reviews and detects first-party fraud in seconds.

The Two Layers of Document Verification

There are two layers to comprehensive document verification for lenders:

1. Data validation and extraction

• Ensure that only the right documents get to your team. Your document verification software should reject bank statements and pay stubs that do not satisfy the recency requirement (e.g., bank statements older than 3 months). The software should also alert the customer when they upload a different document than is requested. This cuts down the time your team spends reviewing the wrong documents.
• Extract customer name, account numbers, balances and transaction history. Verify that the data matches the customer’s claims, and check the mathematical accuracy of the numbers.

If you’re doing this manually, you’re losing operational hours to application reviews, and possibly losing customers to competitors with faster review processes. Automate this layer with InfraRed.

If you’ve automated this layer, you've eliminated a major bottleneck.

2. Fraud detection

Inspect whether the document was altered after it was created. Detect content overlay and inconsistencies in the document metadata.

Most lenders still try to detect fraud manually or use software that is trained on bank statement templates. While these may catch some kinds of fraud, they miss content overlay fraud where the structure and format of the document remains the same, and only numbers have changed.

Why both layers matter

A borrower submits a bank statement showing $8,500 in monthly deposits. Your automated data extraction confirms that the name matches the customer’s name, the account number is valid, and the balance supports the loan amount. What it doesn't detect is that the originally-issued bank statement showed $850. The borrower used a PDF editor to overlay "$8,500" over "$850."

Document fraud may be costing more than you realise

Borrowers are often impatient and therefore abandon loan application processes when they seem to take time. Manual processes cost you prospective customer conversions. But the cost of fraud is higher. When altered documents pass through, you're building a loan portfolio on fabricated income statements. And the risk of loss is higher.

Build complete verification by reviewing loan applications by risk level

Don't treat all documents the same way. Create three pathways using automated risk analysis:

• Auto-approve documents that pass the validation and fraud detection layers.
• Auto-reject clear cases of tampering automatically detected by InfraRed.
• Only route the ambiguous cases for human review. With a great fraud detection tool, this should be less than 10% of total applications.

The Bottom Line

Manual document review, whether for data extraction or fraud detection, creates bottlenecks that costs your business.

The lenders winning in 2026 trust InfraRed’s complete verification tools where data extraction and fraud detection work together. Both tools are automated, fast, and reliable. Start automating document verification today or Book a demo.