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Data Mining for Fraud Detection

Data Mining for Fraud Detection

Roberto Marmo
Copyright: © 2021 |Pages: 13
ISBN13: 9781799834731|ISBN10: 1799834735|EISBN13: 9781799834748
DOI: 10.4018/978-1-7998-3473-1.ch079
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MLA

Marmo, Roberto. "Data Mining for Fraud Detection." Encyclopedia of Organizational Knowledge, Administration, and Technology, edited by Mehdi Khosrow-Pour D.B.A., IGI Global, 2021, pp. 1150-1162. https://doi.org/10.4018/978-1-7998-3473-1.ch079

APA

Marmo, R. (2021). Data Mining for Fraud Detection. In M. Khosrow-Pour D.B.A. (Ed.), Encyclopedia of Organizational Knowledge, Administration, and Technology (pp. 1150-1162). IGI Global. https://doi.org/10.4018/978-1-7998-3473-1.ch079

Chicago

Marmo, Roberto. "Data Mining for Fraud Detection." In Encyclopedia of Organizational Knowledge, Administration, and Technology, edited by Mehdi Khosrow-Pour D.B.A., 1150-1162. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-3473-1.ch079

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Abstract

With the increased use online and electronic resources both by the companies and the customers the problem of fraud has been rising in the last decade. Data mining to classify, cluster, and segment the data and automatically find associations and rules in the data, that may signify interesting patterns, including those related to fraud. This chapter aims to introduces to the concepts of fraud, processes and tools involved in data mining techniques, as well as the importance, challenges, and use cases.

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