AI Meets AML: How Smart Analytics Fight Money Laundering

In the last six months alone, I think I’ve read at least 1,000 Wall Street Journal articles on artificial intelligence (AI) and its technologic cousins: robots, drones and self-driving cars. Between those three things, I’m pretty sure most of the jobs humans have today will change. Some will even disappear.

There is so much noise about AI and its ilk that, in my opinion, it’s important for us in the worlds of fraud and compliance to take a step back and focus on how we can implement this incredibly advanced technology in the context of our current technology and regulatory environment. For example, while it’s pretty cool how AI is now being leveraged to play poker and beat professionals in real games, it’s a distraction from the discussion of ways that AI can help right now, today, for real business challenges.

One of the places where AI can make a huge difference today is in anti-money laundering (AML). FICO has incorporated AI technology in our FICO® TONBELLER® AML solutions; FICO’s Chief Analytics Officer, Dr. Scott Zoldi, recently articulated a number of AI’s important benefits to customers attending the FICO TONBELLER User Group. These benefits include:

• More effective than rules-based systems: AML systems are overwhelmingly rules-based. As regulations become ever more demanding, the rules-based systems grow more and more complex with hundreds of rules driving know your customer (KYC) activity and Suspicious Activity Report (SAR) filing. As more rules get added, more and more cases get flagged for investigation while false positive rates keep increasing. Sophisticated criminals learn how to work around the transaction monitoring rules, avoiding known suspicious patterns of behavior. Both of these trends put undue pressure on financial institutions with a workload that only increases, to be handled by compliance teams that typically don’t.We have built FICO’s mature, market proven and patented advanced artificial intelligence and machine learning algorithms, used today in FICO® Falcon® Fraud Manager, into FICO® TONBELLER® Siron® AML. Our new machine learning techniques are directed specifically toward real-time transaction-based KYC anomaly detection, and highly refined self-learning models focused on anti-money laundering SAR detection.
• Powerful customer segmentation: Traditional AML solutions resort to hard segmentation of customers based on the KYC data or sequence of behavior patterns. FICO’s approach recognizes that customers are too complex to be assigned to hard-and-fast segments, and need to be monitored continuously for anomalous behavior. Using Bayesian learning, we take customers’ banking transactions in aggregate and generate “archetypes” of customer behavior. Each customer is a “mixture” of these archetypes and in real-time, these archetypes are adjusted with financial and non-financial activity of customers.Using clustering techniques based on the customer’s archetypes allows customer clusters to be formed within their KYC hard segmentation. Different clusters have different risk, and customers that are not within any cluster are suspicious.
• Rank-ordering of AML alarms: Using machine learning technology, FICO has also created an AML Threat Score that prioritizes investigation queues for SARs, leveraging behavioral analytics capability from Falcon Fraud Manager. This is a significant improvement, since finding true money-laundering behavior among tens of thousands of SARs is a true needle-in-the-haystack analogy. FICO uses transaction profiling technology, customer behavior sorted lists, and self-calibrating models that adapt to changing dynamics in the banking environment.

Check out this infographic to learn more about transaction profiling technology, customer behavior sorted lists, and self-calibrating models.

Tune in tomorrow for the second post in this series, when my colleague Frank Holzenthal will explore what these technologies add to AML.

Follow me on Twitter @FraudBird

To find out more about how FICO is putting AI to work in AML, register for our February 23 webinar, co-presented with CEB TowerGroup, “Hiding in Plain Sight: Is Your KYC Process a Spotlight or a Blindfold? Operational Benefits of New Analytic Technologies.”

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While you’re here, why not check out our other financial crime blogs

• Asian Money Laundering Scandals: Banks Fear A Large Breach
• Financial Crime Compliance Predictions 2019: Stop the Scandals!
• AI Meets AML: How the Analytics Work
• How APC Will Fight Financial Crime in Panama
• 5 Reasons Why AML is More Important Than Ever in 2019
• Latest Reports Name FICO TONBELLER a Leader in AML, KYC
• Tax Evasion: Have We Learned the Panama Papers Lesson?
• Two Ways to Prevent Money Laundering Scandals
• Cognitive Analytics for AML – Making SARs Count