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Filling a Key Gap in Check Fraud Detection

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In the ongoing war against check fraud, a new capability could address an often neglected area of risk.

ParaScript, a company that specializes in AI-driven document processing, has introduced a feature to detect, read, and interpret handwritten or stamped endorsements on the back of checks. This update to Parascript’s check recognition solution, CheckXpert.AI, allows the system to identify phrases such as “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. Any endorsements that appear missing, suspicious, or unauthorized are immediately flagged.

This enhancement helps ensure checks are deposited through authorized channels and reduces fraud risk. However, it is important to note that the tool does not verify handwriting authenticity or match signatures to those on file—capabilities offered by some other investigative tools.

A Practical Improvement

The automation of a task that frequently causes issues in remote deposits—endorsement verification—is key here.

“Most fraud tools focus on signatures or altered fields, but this fills a smaller 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 caught later during back-office review.

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

AI Advancements

AI has become crucial in combating check fraud. The federal government remains a significant user of paper checks, with 23% of benefit recipients receiving assistance via checks or vouchers. It uses AI to detect such fraud, achieving 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. Despite this, many organizations are not taking such crime seriously. A survey by Javelin Strategy & Research found that only 22% of companies use check fraud detection solutions.

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