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Big Data for Fraud Detection

  • Vahid MojtahedEmail author
Chapter
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Part of the Computational Social Sciences book series (CSS)

Abstract

Fraud is domain-specific, and there is no one-solution-fits-all method among fraud detection techniques. To make this chapter more specific and concrete, we provide examples concerning a common type of fraud which is food fraud. Food fraud has irreversible effects since it imposes risks to human life. The aim of this chapter is thus to present a conceptual and methodological solution for real-time fraud detection that can be implemented in the food sector by global food producers, regulatory bodies, or retailers but is generalizable to other domains.

Keywords

Big data Fraud detection Anomaly detection Clustering Multivariate statistics 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Avanade Ltd.LondonUK
  2. 2.Fera Science Ltd., National Agri-food Innovation CampusSand Hutton, YorkUK

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