AI-Powered Mileage Verification: How Platforms Are Using Machine Learning to Catch Mileage Fraud

package, which could add a significant premium, perhaps $15-$30 per user per month, depending on the overall contract. Buyers aren't paying for a single feature; they are paying to stop fraud and enforce compliance across their entire expense setup. Newer players like TripActions (now Navan) and Rydoo have entered this space with their own approaches to automated mileage. Navan compares reported mileage against booked travel itineraries and public transit schedules to spot inconsistencies. Rydoo relies on GPS data and geo-fencing to suggest mileage claims automatically, cutting down on manual entry errors and the temptation to pad the numbers.

The Doctor's Verdict

I have watched companies bleed money through inflated mileage claims for years. Machine learning for mileage verification is now a baseline requirement. The technology catches the bulk of the fraud that manual reviews miss. False positives happen—a legitimate detour for a forgotten laptop might trigger an alert and require a quick explanation from the employee. Human oversight still matters, but the software does the heavy lifting.

These systems process data volumes and spot subtle patterns that no human auditor could catch. They give managers an objective, data-driven reason to question a suspicious claim, removing the personal friction from a difficult conversation. The mere presence of this software acts as a deterrent. When employees know the system checks their routes, they report accurately. If you want to plug one of the oldest leaks in your budget, pay for automated mileage verification. It solves an age-old problem, and it works.