A Novel Statistical Approach to Detect Card Frauds Using Transaction Patterns

Chae Chang LEE  Ji Won YOON  

IEICE TRANSACTIONS on Information and Systems   Vol.E98-D   No.3   pp.649-660
Publication Date: 2015/03/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2014EDP7071
Type of Manuscript: PAPER
Category: Information Network
pattern mining,  fraud detection,  autoregressive,  Gaussian processes,  association rule,  

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In this paper, we present new methods for learning the individual patterns of a card user's transaction amount and the region in which he or she uses the card, for a given period, and for determining whether the specified transaction is allowable in accordance with these learned user transaction patterns. Then, we classify legitimate transactions and fraudulent transactions by setting thresholds based on the learned individual patterns.