Use Case: Intelligent Money Laundering Detection

Keep up with ‘innovative’ financial criminals to reduce risk of non-compliance and increase operational efficiency

The problem for banks

Money laundering is a significant global problem, with $36b in fines imposed for regulatory non-compliance since 2008, and banks are at risk because they can’t keep up with ‘innovative’ fraudsters: “We published the rule on Friday, the fraudsters knew it by Monday!” — Head of Risk at Top 10 global bank

Our solution

Inspirient’s automated analytics platform combines fraud-specific reasoning, general anomaly detection, and Machine Learning to detect known and previously unknown fraud patterns.

Why Inspirient?

Reduce money at risk from regulatory fines, which can be in the billions of dollars, and increase operational efficiency through alert prioritization and intelligent automation.

Typical Efficiency Gain

Efficiency gain is modeled via the FTE resources currently performing the process that is to be automated.

FTE days gained / year
Savings / year

Would you like to achieve superior efficiency through automation?

The Inspirient Automated Analytics Engine automates the entire data analytics process end-to-end: From the assignment of input data, pattern and outlier detection, automated visualization of patterns, weak points and opportunities to automatic generation of textual explanations and recognition of the underlying relationships and rules. Most other analytics solutions rarely include these textual explanations and observations regarding the underlying data relations, which are both critical to provide a deeper level of analysis and more actionable conclusions.

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