Fraud Detection in Telecommunications: History and Lessons Learned

被引:34
|
作者
Becker, Richard A. [1 ]
Volinsky, Chris [1 ]
Wilks, Allan R. [1 ]
机构
[1] AT&T Labs Res, Stat Res Dept, Florham Pk, NJ 07932 USA
关键词
Automated message accounting; Communities of interest; Data stream; Graph matching; Signatures; Social networks; Top-k;
D O I
10.1198/TECH.2009.08136
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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 sonic 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.
引用
收藏
页码:20 / 33
页数:14
相关论文
共 50 条
  • [1] Learned lessons in credit card fraud detection from a practitioner perspective
    Dal Pozzolo, Andrea
    Caelen, Olivier
    Le Borgne, Yann-Ael
    Waterschoot, Serge
    Bontempi, Gianluca
    EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (10) : 4915 - 4928
  • [2] A probabilistic approach to fraud detection in telecommunications
    Olszewski, Dominik
    KNOWLEDGE-BASED SYSTEMS, 2012, 26 : 246 - 258
  • [3] Electronic Fraud Detection in the US Medicaid Healthcare Program: Lessons Learned from other Industries
    Travaille, Peter
    Mueller, Roland M.
    Thornton, Dallas
    van Hillegersberg, Jos
    AMCIS 2011 PROCEEDINGS, 2011,
  • [4] Employing Latent Dirichlet Allocation for fraud detection in telecommunications
    Xing, Dongshan
    Girolami, Mark
    PATTERN RECOGNITION LETTERS, 2007, 28 (13) : 1727 - 1734
  • [5] A Network Embedding Based Approach for Telecommunications Fraud Detection
    Liu, Xiao
    Wang, Xiaoguo
    COOPERATIVE DESIGN, VISUALIZATION, AND ENGINEERING: 15TH INTERNATIONAL CONFERENCE, CDVE 2018, 2018, 11151 : 229 - 236
  • [6] The history of DES, lessons to be learned
    Veurink, M
    Koster, M
    de Jong-van den Berg, LTW
    PHARMACY WORLD & SCIENCE, 2005, 27 (03): : 139 - 143
  • [7] The History of DES, Lessons to be Learned
    Marieke Veurink
    Marlies Koster
    Lolkje T.W. de Jong-van den. Berg
    Pharmacy World and Science, 2005, 27 : 139 - 143
  • [8] BTG: A Bridge to Graph machine learning in telecommunications fraud detection
    Hu, Xinxin
    Chen, Hongchang
    Liu, Shuxin
    Jiang, Haocong
    Chu, Guanghan
    Li, Ran
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2022, 137 : 274 - 287
  • [9] Designing an expert system for fraud detection in private telecommunications networks
    Hilas, Constantinos S.
    EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (09) : 11559 - 11569
  • [10] An application of supervised and unsupervised learning approaches to telecommunications fraud detection
    Hilas, Constantinos S.
    Mastorocostas, Paris As.
    KNOWLEDGE-BASED SYSTEMS, 2008, 21 (07) : 721 - 726