Automating Multi-Jurisdictional Surcharge Audits: A Compliance Shield for Car Rental Aggregators

Our client, a leading car rental aggregator in North America, was facing a silent but existential threat. Their business model relies on aggregating listings from hundreds of independent and franchise rental partners. While this provides customers with choice, it created a massive compliance headache. Each state, and often each major airport, has its own unique set of mandatory surcharges and fees that must be included in the advertised price. New consumer protection laws were putting the onus on the aggregator to ensure the prices displayed on their platform were not deceptive.

The client's Head of Legal and Compliance explained their predicament. 'We were spending thousands of hours manually spot-checking our partners,' she told us. 'A team of three auditors would spend their entire week pretending to book cars in different cities—from LAX to JFK to DFW—just to see if our partners were including the 'Airport Concession Fee' or the 'Tourism Surcharge' in the total price. It was inefficient, impossible to scale, and we knew we were missing things. One major lawsuit could jeopardize our entire business.' They were terrified of 'drip pricing' accusations, where a low initial price entices customers, only for mandatory fees to be added at the last step of the booking process.

Our challenge at Iceberg Data was to build an automated shield for them. We needed to create a system that could audit thousands of listings across hundreds of jurisdictions daily, flagging any partner who wasn't playing by the rules. The core of our solution was a sophisticated, geo-targeted web scraping engine. We configured our crawlers to simulate users from specific locations, which is critical because many rental websites display different fees based on the user's IP address.

First, we built a comprehensive 'Regulatory Fee Database'. Our team researched and cataloged all known mandatory car rental fees for the top 200 airports and downtown locations in the US. This database became our ground truth. It listed fees like the 'Consolidated Facility Charge' in Las Vegas or the 'Customer Facility Charge' at Denver International Airport.

Next, we deployed our scrapers. These weren't simple data extractors. They were designed to navigate the entire booking process on each partner site, right up to the final payment page, to capture a fully itemized price breakdown. They extracted the base rate, every line item listed under 'fees' or 'surcharges,' and the final, bold-print 'Total Price' shown to the customer. This process was repeated for different car classes and rental durations to ensure compliance across the board.

The real magic happened when the scraped data hit our matching algorithm. For each audit, the system would look at the jurisdiction (e.g., 'NV-LAS' for Las Vegas) and pull the corresponding required fees from our database. It would then parse the scraped fees from the partner site, sum them with the base rate and taxes, and compare this calculated, compliant total with the total the partner was actually displaying. The output was simple and powerful: a dashboard with a clear 'is_compliant' flag for every single partner listing we audited. When the flag was false, as shown in the example JSON, it detailed exactly which fee was missing and the monetary discrepancy.

The results were immediate and impactful. Within the first month, our system identified that nearly 15% of partner listings had some form of compliance issue, ranging from minor miscalculations to the blatant omission of significant surcharges. The client used this data to automatically notify non-compliant partners, giving them a deadline to correct their pricing displays before being delisted. This proactive approach reduced their potential fine exposure by an estimated 95% and completely eliminated the need for their manual audit team , freeing up those employees to focus on higher-value contract negotiations. It transformed their compliance strategy from a reactive, manual chore into a proactive, automated, and data-driven function, protecting both their customers and their bottom line.