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Filling a Key Gap in Check Fraud Detection

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In the ongoing struggle against check fraud, a novel feature might offer relief to an underappreciated aspect of risk. ParaScript, known for its AI-driven document processing technology, has rolled out an innovation that can recognize, scan, and interpret handwritten or stamped endorsements on the reverse side of checks.

The addition to Parascript’s check recognition platform, CheckXpert.AI, permits 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 predefined list of authorized expressions. Any endorsements deemed missing, suspicious, or unauthorized are promptly highlighted.

This enhancement ensures checks are submitted through legitimate channels and mitigates fraud risk. However, it’s worth noting that the software doesn’t authenticate handwriting or match signatures with records—features provided by certain other forensic tools.

A Practical Boost

Streamlining a challenge in remote deposits: verifying endorsements is seen as a significant advancement.

“Most fraud solutions target signatures or altered fields, but this fills an underserved niche by ensuring the back of the check aligns with expectations,” commented Jennifer Pitt, Senior Analyst for Fraud Management at Javelin Strategy & Research. “It performs real-time checks, allowing issues to be identified prior to acceptance, thus preempting potential complications in back-office reviews.

“While not a major leap in handwriting analysis, it represents a practical enhancement,” she added. “For financial institutions handling high-volume deposits or stringent compliance standards, this aids in minimizing manual scrutiny and maintaining basic controls more consistently.”

AI Progress

The advancement of AI is pivotal in combating check fraud. The federal government continues to utilize paper checks, with 23% of benefit recipients receiving payments via this method. AI has proven effective here; according to CNN, machine learning techniques helped the Treasury recover $1 billion in check fraud during fiscal 2024—a figure nearly triple what was recovered the previous year.

Banks issue approximately 700,000 reports of check fraud annually. Despite this, many organizations remain lax about this form of crime. Only 22% of surveyed companies by Javelin use check fraud detection solutions.

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