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Statistical Methods for Fighting Financial Crimes

Summary: [This abstract is based on the authors' abstract.] The use of statistical methods to address financial crimes is challenging. Criminals quickly change tactics to conceal their actions and investigative delays make it difficult to verify crimes in a timely manner. In addition, the complexity of financial data requires algorithms that are effective and efficiently executed. Two types of financial crimes, fraud and money laundering, are investigated. The application of traditional statistical techniques is discussed, as well as more recent machine learning and data mining algorithms. A survey of broad classes of methodologies accompanied by illustrative examples is provided.

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  • Topics: Statistics
  • Keywords: Variance (statistics), Classification, Financial industry, Statistical methods, Algorithm, Event detection
  • Author: Sudjianto, Agus; Nair, Sheela; Yuan, Ming; Zhang, Aijun; Kern, Daniel; Cela-Díaz, Fernando
  • Journal: Technometrics