Taming the Naughty List: How Babel Street Helped Santa Check Twice

One of our primary drivers at Babel Street is ensuring we solve customers’ problems with our cutting-edge technology. This year, we were presented with a mission-critical challenge, and we were determined to deliver a solution. Timing was of the essence.

CEO Kris Kringle of North Pole Enterprises (NPE) discussed the situation. “Every year, our organization is tasked with ensuring accurate categorization of potential gift recipients into two camps: naughty or nice. But the amount of data available to make this determination has grown exponentially and we just can’t keep up. The elves are overworked and overwhelmed.”

NPE was experiencing the Risk-Confidence Gap, or the widening chasm between the escalating volume and variety of data that must be examined to make informed decisions, and the resources available to analyze it.

Kringle explained that the process for determining whether someone has been naughty has become increasingly complex. With numerous social media sites, blogs, forums, and other outlets to examine, NPE faced the near-impossible task of “checking it twice” in the month of December.

The numbers are daunting. In 2024, approximately 2.63 billion people around the globe will celebrate Christmas, or around one-third of the total population. By 2050, that number is expected to increase to 3.3 billion. [1]

Challenges included:

• Inability to rapidly analyze and match multilingual names
• High false positive rate due to identical or similar names of individuals
• Lack of automated and persistent processes for threat analysis
• Inability to make rapid decisions based on global situational awareness

The consequences of misidentifying someone are potentially dire, as that person would have to remain on the naughty list for an entire year.

Additionally, NPE needed the ability to protect executives, employees, and workplaces from potential threats. Enhanced situational awareness of natural disasters, social and political events, and supply chain disruptions could help NPE better plan its delivery route.

According to Kringle, “We need to make mid-flight decisions based on real conditions on the ground. And while we appreciate the tracking services provided by NORAD, they’re unable to assist with this real-time intelligence.”

NORAD confirms this on their website: “NORAD tracks Santa, but only Santa knows his route, which means we cannot predict where and when he will arrive at your house. Santa's route can be affected by weather, so it's really unpredictable. NORAD coordinates with Santa's Elf Launch Staff to confirm his launch time, but from that point on, Santa calls the shots.”

Finally, NPE has faced threats in the past and needs persistent monitoring of bad actors and organizations. Without mentioning names, Kringle indicated that a certain green character has been known to steal Christmas, a Burgermeister has banned toys, and a miser came close to ruining the holiday for a needy family.

Accurately matching names is a particular challenge for maintaining the naughty and nice lists. According to Ancestry.com [2], the ten most common names in the U.S. in 2023 were:  

• James Smith: 38,313
• Michael Smith: 34,810
• Robert Smith: 34,269
• Maria Garcia: 32,092
• David Smith: 31,294
• Maria Rodriguez: 30,507
• Mary Smith: 28,692
• Maria Hernandez: 27,836
• Maria Martinez: 26,956
• James Johnson: 26,850

The Solution

Babel Street approached NPE’s use case with leading-edge solutions from the Babel Street Ecosystem.

NPE provided the list of 2.3 billion individuals needing screening. For simplicity, NPE decided that any potential gift recipient that appeared on any sanctions or watchlist worldwide would be considered naughty — a fairly safe bet considering the nature of those lists. As a first step, NPE would use Babel Street Match to screen every name against every watchlist.

Using the match score and match threshold features, along with automated workflows, anyone with a high likelihood of matching an individual on a watchlist was immediately added to the naughty list. This completely eliminated money launderers, drug traffickers, other known criminals, and Russian oligarchs. They were all very naughty.

Some matches were less straightforward. Previously, these false positives required manual remediation — a time-consuming and labor-intensive effort for the elves. It could take hours for one elf to clear a single false positive. This is where Babel Street Insights enabled faster remediation through advanced People Search and Document Search capabilities.

Insights performs searches across billions of publicly available information (PAI) and commercially available information (CAI) sources with filters that can narrow results by language, region, and time frame (2024 only).

For those names being checked twice, NPE decided that even one naughty action was enough to keep someone off the nice list, so they included the filters for negative sentiment and violent intent. Insights analyzes content across hundreds of languages and can instantly translate it, enabling the elves to quickly and efficiently spot mean tweets, snarky posts, insensitive comments, or worse. Finally, the AI analysis enabled by Insights GPT Beta gave elves a summary overview of Insights’ findings.

With the assistance of Babel Street professional services, NPE set up persistent searches of the known bad actors with the propensity to disrupt gift delivery or otherwise jeopardize the spirit of Christmas. This enabled the analyst elves to monitor the evil-doers’ social media for threat indicators and warnings about toy bans, thefts, or the spreading of ill will.

Finally, analyst elves will use Babel Street Insights for advanced situational awareness in the days leading up to and including Christmas to make up-to-the-minute route recommendations based on weather and events on the ground.

The Impact

Kringle and NPE elves were extremely satisfied with the reduction of their workload enabled by Babel Street solutions. The ability to rapidly perform watchlist screening, and then quickly remediate the edge cases ensured that bad actors were not erroneously placed on the nice list.

They also appreciated that Insights’ search and monitoring capabilities could give them advance warning of potential threats to the holiday, Kringle himself, or the elves.

Kringle commented, “With a limited workforce, the capabilities of the Babel Street Ecosystem allow the entire team to focus on making the holidays bright.”

For its part, Babel Street was both honored and excited to take part in this project. According to Babel Street CEO, Michael Southworth, “We’ve known for a long time that our solutions can have a significant impact on our customers’ missions. Although this was well beyond our usual scope, I had confidence in the Babel Street team. For those of you on the nice list, we extend our congratulations and best wishes for the holiday season. And for those on the naughty list, better luck next year.”

End Notes

[1] Gordon-Conwell Theological Seminary,“Status of Global Christianity 2024”, https://www.gordonconwell.edu/wp-content/uploads/sites/13/2024/01/Status-of-Global-Christianity-2024.pdf 

[2] “Calling James Smith! 10 most common first and surname combinations,” Apr 2023, https://www.ancestry.com/c/ancestry-blog/calling-james-smith-10-most-common-first-and-surname-combinations 

All names, companies, and incidents portrayed in this document are fictitious. No identification with actual persons (living or deceased), places, companies, and products are intended or should be inferred.