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WireVis: Visualization of Categorical,
Time-Varying Data From Financial Transactions


Project Summary:

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. We developed 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 introduced 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 demonstrated that using our tool, investigators are able to detect accounts and transactions that exhibit suspicious behaviors.

My individual contribution in this project was in the design and implementation of the Search-By-Example visualization. Once the investigator has located an account with suspicious behavior, they can use this visualization tool to locate other accounts which behave similarly.





Publications:

  • R. Chang, A. Lee, M. Ghoniem, R. Kosara, W. Ribarsky, J. Yang, E. Suma, C. Ziemkiewicz, D. Kern, and A. Sudjianto, "Scalable and Interactive Visual Analysis of Financial Wire Transactions for Fraud Detection," Journal of Information Visualization 7, 2008, pp. 63 - 76.   PDF

  • R. Chang, M. Ghoniem, R. Kosara, W. Ribarsky, J. Yang, E. Suma, C. Ziemkiewicz, D. Kern, and A. Sudjianto, "WireVis: Visualization of Categorical, Time-Varying Data From Financial Transactions," IEEE Visual Analytics Science and Technology 2007, pp. 155-162. (42% acceptance rate)   PDF   Movie