Title: Application of Cluster-Based Local Outlier Factor Algorithm in Anti-Money Laundering
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.
Publication Year: 2009
Publication Date: 2009-09-01
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 47
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