Detect Lending Fraud with Ocrolus: Watch the Tools in Action

Fraud detection in lending: How AI-powered document analysis is changing the game

Fraud detection in lending is becoming more complex, with increasingly sophisticated tampering methods making it harder to manually verify documents. Ocrolus' Detect product is designed to help lenders, fraud analysts and leasing agents streamline fraud review by identifying signs of tampering and suspicious activity in bank statements, pay stubs and W2s.

In this session, Ocrolus experts break down how Detect works, what makes it unique and how lenders can leverage AI-driven insights to strengthen fraud detection.

Key takeaways

• Detect automates document fraud detection, identifying file tampering, metadata manipulation and anomalies in financial data.
• The solution supports high-risk documents like bank statements, pay stubs and W2s, which are frequently altered in lending applications.
• AI-powered fraud detection analyzes both visible and hidden document alterations, uncovering discrepancies invisible to the human eye.
• The Authenticity Score provides a clear, actionable fraud risk assessment, allowing lenders to quickly determine document integrity.
• Lenders can customize fraud detection thresholds based on their risk tolerance, filtering out highly suspicious documents while manually reviewing borderline cases.

How Detect identifies fraud in lending documents

1. Two core categories of fraud detection

Detect classifies fraud into two main categories:

• File tampering: Alterations made to the document itself, including metadata manipulation and text edits that are difficult to detect manually.
• Algorithmic anomalies: Discrepancies in financial calculations, such as unreconciled balances on bank statements or incorrect tax withholdings on pay stubs and W2s.

By combining both tampering detection and algorithmic verification, Detect provides a more comprehensive fraud assessment than traditional manual review.

2. AI-powered authenticity score for rapid decision-making

The Authenticity Score distills all fraud signals into an easy-to-interpret rating that helps lenders make quick decisions:

• 30 and below: Highly suspicious—often rejected outright.
• 30-70: Medium risk—may require manual review.
• 80 and above: Likely authentic but still subject to review.

This score provides lenders with an instant fraud risk assessment, allowing them to focus on high-risk cases while streamlining approvals for low-risk applications.

3. Visualizing document tampering for fraud analysts

Detect’s dashboard provides:

• Side-by-side comparisons of tampered vs. original text, highlighting edited amounts, names and account details.
• Metadata insights, including editing software detection (Adobe Acrobat alterations).
• Recovered document layers, peeling back alterations to reveal original content.

These insights empower underwriters and fraud analysts to validate suspicious documents efficiently without combing through every line manually.

Addressing fraud challenges in lending

1. Why lenders should avoid image-based PDFs

Fraud detection is significantly more challenging with image-based PDFs, as metadata is often stripped away. Detect can analyze numerical inconsistencies in images, but document authenticity scoring is capped at 80 due to the inherent risks of image manipulation.

Best practice: Encourage PDF submissions over image uploads whenever possible to enhance fraud detection accuracy.

2. How Detect leverages real-world fraud data

Ocrolus continuously refines Detect’s fraud signals using ground truth data from lenders. This allows for:

• Continuous improvements to fraud detection accuracy.
• Customization of fraud thresholds based on real-world lending risks.
• Ongoing feedback loops to address emerging fraud tactics.

Fraud detection in action: What lenders can expect from Detect

• Instant risk assessment with Authenticity Scores to streamline fraud review.
• Automated detection of altered account numbers, tax discrepancies and balance manipulations.
• Machine-learning-based tampering analysis that uncovers hidden document edits.
• Custom fraud detection thresholds to align with individual lender risk policies.

Detect is already uncovering fraud in 6–7% of bank statements submitted through Ocrolus, proving its effectiveness in protecting lenders from financial risk.

Next steps: Strengthening your fraud detection strategy

Fraud detection is no longer a manual game—AI-driven tools like Detect provide a proactive, scalable solution to mitigate lending risk before fraud impacts your bottom line.

Interested in seeing how Detect can enhance your underwriting fraud review? Request a demo to explore how AI-powered fraud detection can protect your business today.