Innovative Approach to Check Fraud Detection

In the ongoing struggle against check fraud, a fresh capability could address an often-neglected area of risk.
ParaScript, a company dedicated to AI-powered document processing, has rolled out a feature that can detect, read, and interpret handwritten or stamped endorsements on the back of checks.

The update to Parascript’s check recognition solution, CheckXpert.AI, allows the system to recognize phrases such as “For mobile deposit only” or “Deposit only to account of payee.” It automatically identifies the orientation of the check and matches the text against a customizable list of authorized phrases. Endorsements that seem missing, suspicious, or unauthorized are flagged immediately.

This advancement aids in ensuring checks are deposited through approved channels and lowers the risk of fraud. However, it is important to note that this tool does not verify the authenticity of handwriting or match signatures to those on file—capabilities provided by some other investigative tools.

A Practical Upgrade

The automation of endorsement verification—a task often problematic in remote deposits—is a key benefit.

“Most fraud tools focus on signatures or altered fields, but this fills a small gap by ensuring the back of the check says what it’s supposed to,” said Jennifer Pitt, Senior Analyst of Fraud Management at Javelin Strategy & Research. “It does this in real time, which means issues can be flagged before the check is accepted, rather than discovered later in back-office review.

“It’s not a major leap in handwriting analysis, but it’s a practical improvement,” she noted. “For banks handling high deposit volume or compliance requirements, it helps reduce manual review and enforces basic controls more consistently.”

AI Progression in Fraud Prevention

AI is emerging as a critical tool in combating check fraud. The federal government remains a significant user of paper checks, with 23% of benefit recipients receiving payments via this method or vouchers. It has been employing AI to detect check fraud, achieving positive results.

According to CNN, machine learning technology aided the Treasury in recovering $1 billion in check fraud during fiscal year 2024—nearly three times the amount recovered the previous year.

Banks issue nearly 700,000 reports of check fraud annually. However, many organizations are still not prioritizing this type of crime seriously. Only 22% of companies surveyed by Javelin said they use check fraud detection solutions.