Algorithm for detection of illegal discounting in North Carolina Education Lottery
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The lottery is a very lucrative industry. Popular fascination often focuses on the largest prizes. However, less attention has been paid to detecting unusual lottery buying behaviors. Our paper introduces a new model to detect illegal discounting in the North Carolina Education Lottery by analyzing apparent purchasing habits` using statistical analysis of out of pocket costs and ticket buying habits. Nine potential outliers are flagged and are further examined by using a specially designed stochastic model to calculate their precise possible loss in the lottery. The unusual buying patterns of the players flagged as outliers are further confirmed using a K-means clustering analysis of lottery store visiting behaviors. The K-means clustering suggests that the eight out of the nine outliers are in the same cluster. This finding is insensitive to the selection of K. All these indicators point to the conclusion that everyone in that cluster is suspicious of unlawful lottery discounting.
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