Graph Theory-Based Fraud Detection in Banking Check Transactions


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Behşi Z., Memiş E. Ç., Ertuğrul S., Sayar A., Güneş P., Çakar T.

2025 10th International Conference on Computer Science and Engineering (UBMK), İstanbul, Turkey, 15 - 17 September 2025, pp.1141-1146, (Full Text)

  • Publication Type: Conference Paper / Full Text
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.1141-1146
  • Istanbul Gelisim University Affiliated: Yes

Abstract

Traditional banking fraud detection systems rely on rule-based approaches that analyze individual transactions in isolation, failing to capture complex relationship patterns indicative of coordinated fraud schemes such as check-kiting and artificial credit score manipulation. We p resent our study, a novel similarity-based graph theory approach that constructs weighted networks between check issuers using Jaccard Similarity Index and employs advanced graph analysis to identify suspicious entity clusters without requiring complete transaction relationship data. Our approach combines Jaccard Similarity Index for behavioral pattern analysis (addressing payee information unavailability) with comprehensive graph analysis including centrality measures, community detection, and anomaly identification. Through comprehensive evaluation on real banking data containing 458,399 transactions from 121,647 unique …