Data-Driven Fraud Detection Using Detectlets
نویسندگان
چکیده
Fraud detection is becoming increasingly important to managers of organizations, to internal and external auditors, and to regulators (Apostolou and Crumbley, 2005). Recent large frauds in many countries of the world and the Sarbanes-Oxley Act in the United States stress the importance of early detection of fraud. Financial statement frauds have weakened investor confidence in corporate financial statements (Castellano and Melancon, 2002), led to a decrease in market capitalization (Palmrose, et al, 2004), and contributed to five of the ten largest bankruptcies in U.S. history. These four include WorldCom at $104 billion, Enron at $65 billion, Conseco, Inc. at $61 billion, Pacific Gas and Electric at $36 billion, and Refco, Inc. at $33 billion. In addition, the impact of recent investment scams were most visible in the alleged $50 billion Madoff fraud. Internationally, financial statement misstatements such as Parmalat (Italy), Harris Scarfe and HIH (Australia), SKGlobal (Korea), YGX (China), Livedoor Co. (Japan), Royal Ahold (Netherlands), and Vivendi (France) indicate that fraud is a worldwide problem.
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