First Community Bank and Trust reviews every check and cuts manual review time 65% with Socratix
First Community Bank and Trust deployed Computer Vision & Document AI for Fraud Detection & Prevention in Community & Regional. As reported by Socratix: 65% reduction in manual check review time.
Source-reported figures (cited source: Socratix)
What First Community Bank and Trust was trying to fix
First Community Bank and Trust, a community bank in Illinois with $200 million in assets, relied on a flat dollar-amount threshold to decide which checks warranted a closer look. The team reviewed roughly 18% of business checks and just 3% of consumer checks, leaving the remainder to clear without a second review. Check washing, signature mismatches and MICR amount discrepancies can be difficult to identify through manual inspection alone, especially when reviewers are responsible for thousands of checks each month.
What First Community Bank and Trust deployed
The bank worked with Socratix, which now evaluates every check against historical customer behavior and account activity and auto-clears low-risk items. Potential signature discrepancies, MICR mismatches and signs of check washing are identified automatically, and flagged checks arrive with supporting evidence and recommended next steps. Analysts see the check image, historical comparison and narrative explanation together in one view and can follow or override the recommendation. The pilot also surfaced issues that had previously gone undetected, including missing signatures, mismatched written and numeric amounts and inconsistent handwriting.
Results
Socratix evaluates 100% of checks and auto-clears 97.5%, expanding coverage from 18% of business checks and 3% of consumer checks to every check. The bank reduced the time spent reviewing checks manually every day by 65%, and its chief information officer said the time savings is a minimum of 65% with the remaining effort focused on items that have a specific reason for being looked at. In one case, a check written for $1,100 had cleared for $2,200, and the customer was able to address the discrepancy with the vendor right away after an analyst made contact.
Key Takeaways
- Replacing flat dollar thresholds with review of every item can expose problems that sampling leaves undetected.
- Putting the check image, account history and a written explanation together in a unified view makes analyst decisions more consistent.
- Auto-clearing low-risk items frees staff to concentrate on exceptions that need human judgment.
Evidence for First Community Bank and Trust's Fraud Detection & Prevention deployment
- Reported outcome metrics
- 2 cited below
- Cited source
- Socratix
- Last updated
- Source link checked
Explore Related
Details
- Industry
- Community & Regional
- Use Case
- Fraud Detection & Prevention
- AI Technology
- Computer Vision & Document AI
- Company Size
- SME
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