Challenges

Intuit’s search for a robust transaction monitoring and case management solution wasn’t easy. With the constantly changing landscape of the vectors of attack involved in money laundering, Intuit needed a highly flexible and intelligent system to monitor transactions. However, just a blackbox score wouldn’t cut it. Intuit’s business isn’t that of a generic payments company, and complex patterns that are more specific to Intuit and its business needed to be captured.
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Moreover, the system needed to have a high degree of automation and configurability so that Intuit’s investigations team would spend less time on manual tasks such as data aggregation and report generation, and more time on the actual investigation.
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The issue with most vendors that Intuit considered was the lack of flexibility to capture vectors of attack that were very specific to Intuit. Ultimately, for any kind of customization, Intuit would need to require professional services hours or have to build its own internal software, both of which are very expensive operations.

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Results

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Tackling Financial Crimes with a Highly Customizable Modeling Engine

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One of the key factors involved in deciding to select Unit21 was the flexibility that the Unit21 platform offered.

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Unlike most transaction monitoring companies that provide blackbox machine learning scores, Unit21’s transaction monitoring modeling engine enabled Intuit to combine machine intelligence with the explainability that is needed for compliance purposes. The platform enables a perfect hybrid between intelligence in detection and explainability for reporting.
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Intuit can easily create, test, and deploy complex logic for identifying suspicious activity, without having to write any additional code. The modeling engine is also very intuitive, such that even someone from Intuit who doesn’t have a Computer Science education can easily operate on the platform.