In the never-ending battle against check fraud, a new capability may help address a frequently overlooked area of risk. ParaScript, a company specializing in AI-powered document processing, has introduced 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, enables the system to identify phrases like “For mobile deposit only” or “Deposit only to account of payee.” It automatically detects the check’s orientation and matches the text against a customizable list of authorized phrases. Endorsements that appear missing, suspicious, or unauthorized are flagged immediately.
This enhancement helps ensure checks are deposited through authorized channels and reduces the risk of fraud. It’s important to note, however, that the tool doesn’t verify handwriting authenticity or match signatures to those on file—capabilities offered by some other investigative tools.
A “Practical Improvement”
There are key benefits to automating a task that continues to cause issues in remote deposits: endorsement verification.
“Most fraud tools focus on signatures or altered fields, but this fills a smaller gap by making sure 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 caught later in back-office review.
“It’s not a major leap in handwriting analysis, but it’s a practical improvement,” she said. “For banks dealing with high deposit volume or compliance requirements, it helps reduce manual review and enforces basic controls more consistently.”
AI Advancements
AI is developing into a key tool in the fight against check fraud. The federal government remains a strong user of paper checks, with 23% of benefit recipients receiving assistance in the form of checks or vouchers. It has been using AI to detect check fraud with very positive results. According to CNN, machine learning technology helped the Treasury recover $1 billion in check fraud in fiscal 2024—nearly triple the amount recovered the year prior.
Banks issue nearly 700,000 reports of check fraud each year. Nevertheless, many organizations are still not taking this type of crime seriously. Only 22% of companies surveyed by Javelin said they use check fraud detection solutions.
The post Filling a Key Gap in Check Fraud Detection appeared first on PaymentsJournal.
