Fraud Detection in Telecommunications: History and Lessons Learned
Richard A. Becker, Chris Volinsky, Allan R. Wilks
AT&T (United States)
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摘要与影响
Fraud detection is an increasingly important and difficult task in today’s technological environment. As consumers are putting more of their personal information online and transacting much more business over computers, the potential for losses from fraud is in the billions of dollars, not to mention the damage done by identity theft. This paper reviews the history of fraud detection at AT&T, one of the first companies to address fraud in a systematic way to protect its revenue stream. We discuss some of the major fraud schemes and the techniques used to address them, leading to generic conclusions about fraud detection. Specifically, we advocate the use of simple, understandable models, heavy use of visualization, and a flexible environment and emphasize the importance of data management and the need to keep humans in the loop.
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计算机 / AIImbalanced Data Classification Techniques
Data Mining Algorithms and Applications
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