When “Right” Isn’t: How AI Finds the Shipping Errors You Can’t See
In shipping, not every costly mistake wears a red flag. Sometimes the invoice looks perfect, the charges match the contract, and everything appears in order—until you dig deeper. Freight audits do a great job of ensuring invoices are correct, but what happens when the bill is technically correct, but the circumstances behind it aren’t?
That’s where AI-Powered Anomaly Detection changes the game. It’s an extra layer of protection against erroneous circumstances, going to deeper to analyze patterns, behaviors, and historical norms to identify the “almost invisible” errors that slip past even the most diligent audits.
The Hidden Costs Behind a Perfect Bill
Sometimes billing issues don’t come from obvious overcharges or blatant mistakes. They hide in plain sight—a misplaced decimal turning five pounds into five hundred, a misclassification that sends a shipment on the wrong route, or a small glitch in a carrier’s system that changes service selection without anyone noticing.
On paper, these charges might follow the contracted rates exactly. In reality, they can quietly drain thousands—or even millions—over time. Traditional audits are designed to verify compliance; AI-Powered Anomaly Detection is designed to verify what actually happened.
AI as a Microscopic Lens
Anomaly Detection works like a microscope for your shipping data. It’s not looking for rules being broken, it’s looking for patterns being bent. By comparing each transaction against normal operational behavior, it can identify errors within minutes that would take a person weeks or months to uncover—if ever.
This proactive approach means that anomalies, no matter how small, can be addressed before they snowball. Whether it’s a customs misbilling, a service glitch, or an outdated API pulling the wrong data, AI spots the inconsistencies that a standard audit simply isn't designed to flag.
Real-World Wins
In one instance, Anomaly Detection caught a customs duty misbilling that resulted in $519,000 in recovered costs. In another, it exposed a system glitch and outdated processes that, left unchecked, could have created a repeat loss of over $4 million a year.
These aren’t one-off cases—they’re proof that errors can look “right” while doing very real damage to the bottom line.
The Bottom Line
In a world where speed, complexity, and volume define shipping operations, relying solely on traditional audits is no longer enough. AI-powered Anomaly Detection provides the extra layer of insight needed to ensure that “right” truly means right. It’s not just about preventing overcharges, it’s about protecting your margins, tightening your processes, and making smarter shipping decisions every day.
Want to learn how to build this kind of protection into your own operations? Join us for our upcoming webinar, Essential Insights for Shippers with Bart De Muynck, where we’ll dive into how AI helps shippers catch costly mistakes before they make a major impact.
