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Visual analysis of financial crimes: [system paper]

Published: 26 May 2010 Publication History

Abstract

This paper shortly describes a system, called VisForFraud, that uses Information Visualization techniques for the discovery of financial crimes.

References

[1]
V. Batagelj et al. Visual analysis of large graphs using (X,Y)-clustering and hybrid visualizations. In IEEE PacificVIS 2010, 2010. to appear.
[2]
R. Chang et al. Scable and interactive visual analysis of financal wire transactions for fraud detection. Information Visualization, 7(1):63--76, 2008.
[3]
H. Chen et al. Bordersafe: cross-jurisdictional information sharing, analysis, and visualization. In Intelligence and Security Informatics, volume 3495 of LNCS, pages 669--670, 2005.
[4]
W. Didimo and G. Liotta. Mining Graph Data, chapter Graph Visualization and Data Mining, pages 35--64. Wiley, 2007.
[5]
P. Eades. A heuristic for graph drawing. In Congressus Numerantium, volume 42, pages 149--160, 1984.
[6]
C. Westphal. Data Mining for Intelligence, Fraud, & Criminal Detection. CRC Press, 2009.
[7]
J. Xu and H. Chen. Criminal network analysis and visualization. Comm. of the ACM, 48(6):101--107, 2005.

Cited By

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  • (2020)FDHelper: Assist Unsupervised Fraud Detection Experts with Interactive Feature Selection and EvaluationProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376140(1-12)Online publication date: 21-Apr-2020
  • (2020)Combining Network Visualization and Data Mining for Tax Risk AssessmentIEEE Access10.1109/ACCESS.2020.29679748(16073-16086)Online publication date: 2020
  • (2016)Interactive visual analysis of anomalous accounts payable transactions in SAP enterprise systemsManagerial Auditing Journal10.1108/MAJ-10-2014-111731:1(35-63)Online publication date: 4-Jan-2016
  • Show More Cited By

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  1. Visual analysis of financial crimes: [system paper]

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    cover image ACM Other conferences
    AVI '10: Proceedings of the International Conference on Advanced Visual Interfaces
    May 2010
    427 pages
    ISBN:9781450300766
    DOI:10.1145/1842993
    • Editor:
    • Giuseppe Santucci
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 26 May 2010

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    Overall Acceptance Rate 128 of 490 submissions, 26%

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    Cited By

    View all
    • (2020)FDHelper: Assist Unsupervised Fraud Detection Experts with Interactive Feature Selection and EvaluationProceedings of the 2020 CHI Conference on Human Factors in Computing Systems10.1145/3313831.3376140(1-12)Online publication date: 21-Apr-2020
    • (2020)Combining Network Visualization and Data Mining for Tax Risk AssessmentIEEE Access10.1109/ACCESS.2020.29679748(16073-16086)Online publication date: 2020
    • (2016)Interactive visual analysis of anomalous accounts payable transactions in SAP enterprise systemsManagerial Auditing Journal10.1108/MAJ-10-2014-111731:1(35-63)Online publication date: 4-Jan-2016
    • (2014)Network visualization for financial crime detectionJournal of Visual Languages and Computing10.1016/j.jvlc.2014.01.00225:4(433-451)Online publication date: 1-Aug-2014
    • (2011)An advanced network visualization system for financial crime detection2011 IEEE Pacific Visualization Symposium10.1109/PACIFICVIS.2011.5742391(203-210)Online publication date: Mar-2011

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