How Check Fraud Detection Software Works

Funnily enough, AI-powered software depends on a much older form of technology – photography. Every check deposited at a financial institution is run through a check scanner, providing the raw data necessary for in-depth analysis.

But that image isn’t simply reviewed at a glance. Modern detection software evaluates each item across multiple dimensions, looking for inconsistencies that would be difficult – or impossible – to catch through manual review alone.

Here’s how Finovifi by Main Street determines risk, check by check.

The first layer of review starts with the check itself. Image analysis looks at the physical characteristics captured in the scan – signature, layout, spacing, and the relationship between written and numerical amounts.

Subtle inconsistencies in these elements can point to alteration or forgery, even when the check appears normal at a glance.

From there, the check is evaluated in context. Transactional analysis compares the item against expected patterns, flagging things like unusual amounts, out-of-sequence check numbers, or activity tied to new or previously monitored accounts.

What might seem like a routine deposit in isolation can stand out when viewed alongside prior behavior.

Certain issues are less about intent and more about execution. Operational review accounts for missing or mismatched details like dual signatures that don’t align, poor image quality, or inconsistencies in how the check is completed.

These signals don’t always indicate fraud on their own, but they contribute to a broader picture of risk.

Finally, the system considers the account itself. Is it active and in good standing? Does the transaction align with typical behavior for that account? By comparing the check against historical activity, account review helps identify deviations that might otherwise go unnoticed in a manual process.

Each of these layers contributes a piece of the picture. On their own, they may not be enough to confirm fraud – but taken together, they form a more complete view.

Finovifi by Main Street brings these signals together into a single, consolidated assessment. Instead of relying on one indicator, the system weighs multiple factors at once, producing a score that reflects how likely a check is to be fraudulent.

This approach doesn’t eliminate uncertainty, but it does create consistency. Every check is evaluated using the same criteria, and every potential issue is measured against the same standard before it reaches a human reviewer.

Once the multi-analysis score is established, the process shifts from analysis to decision-making.

Rather than reviewing every check that passes through the system, staff are presented with a focused report of items that exceed a defined risk threshold. These are the checks that warrant closer attention.

For most institutions, that review happens at the start of the day. Checks deposited through the branch, ATM, or mobile channels – during business hours or after – are analyzed continuously, then surfaced in a single report for manual review.

From there, the workflow is straightforward. Each flagged item is reviewed in context, using both the supporting data and the institution’s own risk posture to determine whether it should be accepted or escalated.

The difference is not in the decision itself, but in how that decision is reached. Instead of working through a broad queue of checks one by one, staff can focus on a smaller subset of items that have already been identified as higher risk.

The patterns identified through image, transactional, operational, and account analysis map directly to the most common forms of check fraud. While no system can prevent every loss, modern detection tools are designed to surface the kinds of activity institutions encounter most often, including:

For years, detecting check fraud depended on time, experience, and attention to detail. But as volumes increase and fraud tactics evolve, that model becomes unsustainable.

Manual review isn’t inherently flawed – but it is limited. It depends on what can be reviewed in a given window and what can be identified in the moment. As fraud becomes more subtle and more frequent, those constraints become more apparent.

After 25 years of service, Main Street knows what community financial institutions need to defend, grow, and thrive. Finovifi by Main Street represents a new defense against emerging threats powered by emerging technologies. Learn more about our AI-powered check fraud detection software and get the protection your institution deserves.