TY - JOUR
T1 - Scalable and interactive visual analysis of financial wire transactions for fraud detection
AU - Chang, Remco
AU - Lee, Alvin
AU - Ghoniem, Mohammad
AU - Kosara, Robert
AU - Ribarsky, William
AU - Yang, Jing
AU - Suma, Evan
AU - Ziemkiewicz, Caroline
AU - Kern, Daniel
AU - Sudjianto, Agus
PY - 2008/3
Y1 - 2008/3
N2 - 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.
AB - 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.
KW - Categorial and time-varying data
KW - Financial data visualization
KW - Fraud detection
KW - Visual analytics
UR - http://www.scopus.com/inward/record.url?scp=41549088767&partnerID=8YFLogxK
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U2 - 10.1057/palgrave.ivs.9500172
DO - 10.1057/palgrave.ivs.9500172
M3 - Article
AN - SCOPUS:41549088767
SN - 1473-8716
VL - 7
SP - 63
EP - 76
JO - Information Visualization
JF - Information Visualization
IS - 1
ER -