Healthcare fraud is an increasingly large problem in the United States for patients, taxpayers, and the government, with the National Healthcare Anti-Fraud Association (NHCAA) estimating the costs to be more than tens of billions each year (NHCAA, 2018). To address this issue, government agencies and insurers can utilize data analytics to detect and prevent healthcare fraud. The American Senior Communities (ASC) case is a recent example of a complex healthcare fraud scheme committed by several high ranking officers involving kickbacks, fictitious vendors, and money laundering through shell companies. The indictment details how $16 million was stolen is particularly given the population cared for by ASC—the elderly, individuals with disabilities, low income adults, pregnant women and children. This case demonstrates several ways healthcare fraud can be perpetrated, highlights the role of the auditor, and introduces students to the importance of employing data analytics to prevent and detect fraud.