1. ¹Department of Computer Science, University of North Carolina at Charlotte, Charlotte, NC, U.S.A
2. ²Bank of America, Charlotte, NC, U.S.A.

Correspondence: Remco Chang, Department of Computer Science, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC 28223, U.S.A. E-mail: rchang@uncc.edu

Received 1 December 2007; Accepted 5 January 2008; Published online 21 February 2008.

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 to discover 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. Our system can be connected to a database to handle millions of transactions and still preserve high interactivity. 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.