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Scalable and interactive visual analysis of financial wire transactions for fraud detection

机译：金融电汇交易的可扩展和交互式可视化分析，可用于欺诈检测

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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.
机译：美国银行等大型金融机构每天处理数十万笔电汇交易。尽管大多数交易都是合法的，但这些机构有法律和财务义务来发现可疑交易。随着欺诈活动的方法不断变化，对预定义模式的搜索通常不足以检测以前未发现的方法。在本文中，我们基于识别电汇交易中的特定关键字，提供了一组协调的可视化。我们系统中使用的不同视图描述了关键字和帐户之间的关系。此外，我们引入了“按示例搜索”技术，该技术可提取显示类似交易模式的帐户。我们的系统可以连接到数据库以处理数百万笔交易，并且仍然保持高交互性。与美国银行的反洗钱部门合作，我们证明了调查人员能够使用我们的工具来检测具有可疑行为的帐户和交易。

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