The growth of artificial intelligence has made data a valuable asset. Though data has become ubiquitous, sometimes there are unexpected and untapped data sources waiting to be discovered. This presentation reports an exercise with banknotes printed by the United States Bureau of Engraving and Printing. Given that every banknote contains a unique eight-digit serial number, the objective is to build models that inform banknote collectors how much effort they must expend to find banknotes with matching serial numbers. These models generalize a classic problem from discrete mathematics, termed the sock matching problem. Analytical and computer simulation models provide insights that inform how much data is needed to obtain the desired prize. This talk provides a glimpse of new data opportunities exist that may be flying “under the radar”.