I’d like to tell you about one of our customers – we’ll call him John – who went through a very painful New York City tax audit. He lives in Westchester county in NY and was being audited by New York City for 2014, 2015 and 2016. $4M in NYC tax + interest + penalties was at stake for each year. Proving that he spent less than 183 days in New York City in each of those years would dictate whether he’d pay millions of dollars to NYC.

You may have read one of our previous blog posts about the intricacies of residency tax audits. Residency audits are highly intrusive and personal, as the auditor seeks to understand where you are spending your days. Auditors will subpoena and dig through the details of your life, such as credit card statements, EZ-Pass records, social media accounts, key-card entry logs, cell phone records and more. In this particular audit, the auditor was trying to prove that John spent more than 183 days in New York City each year. If John spent more than 183 days in New York City, then it could consider him a resident of the city and tax his full year’s global income as a resident. (You can read more about the 183-Day Rule here.)

John needed to prove that he was NOT in New York City for more than 183 days for each of the years 2014 to 2016. One thing about residency audits, which is captured nicely by Tim Noonan, Partner, Hodgson Russ: “The auditors will generally start the audit with the assumption that the taxpayer spent 365 days in New York.” The burden of proof is on the taxpayer to get that number down to 183 or lower.

John signed up for Monaeo in early 2015, which meant that he had Monaeo data for the 2015 and 2016 audits. Monaeo is a personal audit defense system that creates a complete digital record of your location to protect you in residency audits. It does this through a proprietary combination of cell tower, GPS and WiFi signals. This accurate and reliable digital record can then be submitted to tax authorities, which is what John did for 2015 and 2016. The audits for those years were wrapped up quickly and he was able to prove that he was not in NYC for 183 days and hence was not a statutory resident for those years.

For 2014, John did not have Monaeo data but he kept a diary and credit card receipts whenever he could. John’s records put him in NYC for 181 days, 2 days under the magic 183 day number. However, on a number of days, the auditor was unsatisfied with his records showing a credit card charge for a coffee in the morning and one in the evening, as the auditor claimed that John could have gone to NYC during the day in between those purchases. As a result, the auditor claimed that John spent 189 days in NYC.

NYC’s claim was based on data they received from a subpoena of John’s AT&T data. What AT&T handed over was very extensive – it had an inventory of John’s cell phone records, which showed “location pings” whenever he was on a phone call, sending or receiving texts and using the Internet through his phone. It turns out that the cell phone tower data wasn’t accurate, though.

Please view the image accompanying this post. This is a re-creation of a snapshot of cell phone tower pings for John’s cell phone for one of the 6 days in question. The boxed area with the arrow shows the greatest number of pings, which is at John’s house. The line further down on the map, just above the middle 8:37pm ping, is the boundary line between Westchester County and the Bronx borough of New York City. According to the AT&T carrier pings, John crossed the line into the Bronx at 8:37pm on this day, putting him in New York City. However, John was not in New York City on this day in question, and was instead in Westchester County the entire day, which is not part of New York City.

We analyzed the cell phone data and found some discrepancies, particularly with the 8:37pm ping. We labeled those on the map with green dots. As you can see, there are three of them. How can John be in three places at once? And if you had to choose which one was accurate, it would most likely be the one closest to the 8:36pm ping, which you can see just east of the northernmost 8:37pm ping. This means that the other 8:37pm pings are inaccurate, proving that John was not in New York on this day. In addition, if you continue looking through the pings, you can see multiple pings for other times, too, such as 8:35am, 10:35am and 5:28pm, which further degrades the credibility of this as evidence in the audit case.

We did this analysis across all of the days in question and found similar discrepancies. This is alarming, since these cell tower records were the primary form of evidence that the auditor was using for the days in question.

John and his accountant submitted our analysis to the auditor. The AT&T records for those dates were then declared inadmissible as proof of John’s whereabouts. His day count went down to 181, he won the audit and he kept his $4M.

This case highlights the need for better tools and to move beyond the current forms of proof that today’s taxpayer uses in residency audits, which include paper receipts, credit card swipes, EZ-Pass records, boarding passes, etc. These forms of proof can be helpful, but if the auditor comes to the table with cell tower records and the taxpayer can’t refute them, then that will win. And as we see from this case, those cell tower records may not be accurate. The hand that wins against cell tower data is a more accurate digital record of location and travel, as John’s story highlights. This is what will protect the taxpayer and level the playing field in residency audits.

Additional Reading

If you’d like to learn more about the use of cell tower data in audits, Hodgson Russ recently wrote a detailed and compelling article about the topic. They discuss the details of the location data that various cell phone carriers will provide as well as the difference between real-time location data vs. historic cell site location data. When it comes to historic cell site location data, there are “pinging” issues, as the authors, Timothy P. Noonan, Andrew W. Wright, and Kristine L. Bly, explain:

When attempting to establish the strongest signal, cell phones connect to a number of cell sites within a close proximity. This becomes clear when you examine a cell phone’s historic cell site data. Often, this data will show a number of different locations, in the span of only a few minutes. While this is typically the nearest cell site, there are a number of factors that impact a cell site’s accuracy, including: the density of towers in the surrounding area, the height of the tower, the location of the tower, the time of day, and the user’s location in relation to landscape, physical obstructions, and bodies of water. In short, your cell phone signal is not always going to connect to the tower that is closest. Rather, it will seek out the tower it can reach the fastest and with the best signal strength. This can lead to “false positive” data or what we often refer to as “pinging issues.”

Nothing in this article should be considered or construed as tax advice. Monaeo does not dispense tax advice and always recommends that taxpayers consult their accountants or lawyers.