WireVis: Visualization of categorical, time-varying data from financial transactions

Remco Chang, Mohammad Ghoniem, Robert Kosara, William Ribarsky, Jing Yang, Evan Suma, Caroline Ziemkiewicz, Daniel Kern, Agus Sudjianto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

72 Scopus citations

Abstract

Large financial institutions such as Bank of America handle hundreds of thousands of wire transactions per day. Although most transactions are legitimate, these institutions have legal and financial obligations in discovering those that are suspicious. With the methods of fraudulent activities ever changing, searching on predefined patterns is often insufficient in detecting previously undiscovered methods. In this paper, we present a set of coordinated visualizations based on identifying specific keywords within the wire transactions. The different views used in our system depict relationships among keywords and accounts over time. Furthermore, we introduce a search-by-example technique which extracts accounts that show similar transaction patterns. In collaboration with the Anti-Money Laundering division at Bank of America, we demonstrate that using our tool, investigators are able to detect accounts and transactions that exhibit suspicious behaviors.

Original languageEnglish (US)
Title of host publicationVAST IEEE Symposium on Visual Analytics Science and Technology 2007, Proceedings
Pages155-162
Number of pages8
DOIs
StatePublished - Dec 1 2007
Externally publishedYes
EventVAST IEEE Symposium on Visual Analytics Science and Technology 2007 - Sacramento, CA, United States
Duration: Oct 30 2007Nov 1 2007

Publication series

NameVAST IEEE Symposium on Visual Analytics Science and Technology 2007, Proceedings

Other

OtherVAST IEEE Symposium on Visual Analytics Science and Technology 2007
CountryUnited States
CitySacramento, CA
Period10/30/0711/1/07

Keywords

  • Categorial and time-varying data
  • Financial data visualization
  • Fraud detection

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