• DocumentCode
    2109432
  • Title

    Application of Cluster-Based Local Outlier Factor Algorithm in Anti-Money Laundering

  • Author

    Gao Zengan

  • Author_Institution
    China Center for Anti-Money Laundering Studies, Fudan Univ., Shanghai, China
  • fYear
    2009
  • fDate
    20-22 Sept. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Financial institutions´ capability in recognizing suspicious money laundering transactional behavioral patterns (SMLTBPs) is critical to antimoney laundering. Combining distance-based unsupervised clustering and local outlier detection, this paper designs a new cluster based local outlier factor (CBLOF) algorithm to identify SMLTBPs and use authentic and synthetic data experimentally to test its applicability and effectiveness.
  • Keywords
    financial management; pattern clustering; unsupervised learning; SMLTBP recognition capability; antimoney laundering; cluster based local outlier factor algorithm; distance based unsupervised clustering; financial institution; money laundering transactional behavioral pattern; Algorithm design and analysis; Artificial intelligence; Clustering algorithms; Financial management; Pattern analysis; Pattern recognition; Support vector machines; Terrorism; Testing; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science, 2009. MASS '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4638-4
  • Electronic_ISBN
    978-1-4244-4639-1
  • Type

    conf

  • DOI
    10.1109/ICMSS.2009.5302396
  • Filename
    5302396
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2109432