Profile Behavior

Concentrate on good behavior rather than bad activity with Adaptive Behavioral Analytics

Prioritize Alerts

Make investigators’ work more rewarding by focusing on automatically prioritized suspicious alerts

Predict Future Threats

Improve future transaction monitoring by predicting and adapting to new threats
 

Work fewer alerts and uncover more suspicious activity with ARIC

Key Benefits

• Predict and prevent more money laundering
• Reduce cost of investigations
• Increase productivity
• Fight financial crime more effectively with explainable analytics

Predict and prevent money laundering with ARIC

ARIC is fuelled by industry-leading technology. It understands normal, ‘good’ behavior to discover anomalies that may indicate money laundering.

Harnessing machine learning and Adaptive Behavioral Analytics, ARIC assesses complex data sets to control and understand risk exposure. At the same time, ARIC minimizes false positives, enabling investigators to focus on the alerts that need the most urgent attention.

Unlike traditional AML solutions, ARIC combines rules, adaptive rules and adaptive models. It is intelligence-led and automatically adapts and updates as behavior changes are identified - improving future transaction monitoring and providing greater control of risk exposure.

Featurespace ARIC named "best in class" among the new generation of AML solutions in the 2019 AITE report "AIM Evaluation: Fraud and AML Machine Learning Platform Vendors."
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“Featurespace not only delivers cutting-edge ability better and faster than anyone, it also shares our spirit of revolutionizing financial services. That’s an intangible quality that cannot be overstated and is exceptionally rare today.”

ClearBank CEO, Charles McManus

Case Study: Tier 1 Global Bank

In search of the best AML solution, this Tier 1 global bank selected Featurespace following a head-to-head challenge to demonstrate the benefits of machine learning coupled with automation.

The Challenge

The bank used a rule-based AML transaction monitoring solution. They had a complex data set where it was difficult to spot suspicious activity with rules alone.

The bank’s existing solution generated a monthly batch of alerts with a high volume of false positives. Which required manual consolidation and time-consuming investigation, resulting in operational fatigue.

The Solution

We tested ARIC on this complex data set, comparing the results against the existing solution.

We found that ARIC generated less alerts and uncovered a lot more SARs.

One third of SARs were spotted one month earlier.

12%

reduction in overall alerts

5%

only work top 5% of alerts

1 month

1/3 SARs spotted 1 month earlier than existing system

Why Featurespace?

Born out of 30 years of research at Cambridge University
 

Trusted by the most respected banks and payments companies in the world

World leaders in machine learning for solving risk challenges
 

Unique real-time machine learning methodology

 

Multi-award winning platform and best machine learning models
 

Inventors of Adaptive Behavioral Analytics

 

Our Customers

Multi-Award Winning Fraud & Risk Management Solution