Forcepoint Case Studies Greater Visibility into Trading Floor Communications Saves This Bank $7 Million in Projected Investigation Costs
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Greater Visibility into Trading Floor Communications Saves This Bank $7 Million in Projected Investigation Costs

Forcepoint
Analytics & Modeling - Big Data Analytics
Finance & Insurance
Business Operation
Fraud Detection
Regulatory Compliance Monitoring
Data Science Services
In the highly regulated world of investment banking, new communication channels like Skype and WhatsApp, and web forums like Investopedia, are raising the risk of widespread abuse, whether through insider trading, fraud, or leaks of sensitive company information. This bank’s operations and compliance leadership knew they needed a better way to stay close to trader conversations and safeguard the trading floor. The bank’s monitoring technology was obsolete and required a high level of manual intervention to identify and investigate potential compliance issues. With essentially just an email archiving system, investigators had to build lists of words indicative of insider trading activity and conduct manual searches within the archives to build cases.
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The customer is an international banking group with a presence in more than 70 countries. In addition to retail activities, it is also a leading global investment bank. The bank operates in the highly regulated world of investment banking, where new communication channels like Skype and WhatsApp, and web forums like Investopedia, are raising the risk of widespread abuse, whether through insider trading, fraud, or leaks of sensitive company information. The bank's operations and compliance leadership recognized the need for a better way to stay close to trader conversations and safeguard the trading floor.
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The bank’s leadership invited Forcepoint to join them in a collaborative effort to build a stronger, more effective compliance program. Forcepoint Behavioral Analytics was implemented, which ingests old email data as well as other electronic communications like Skype chats, Bloomberg terminals, and more, those data sources can be analyzed for potential indicators of insider trading activity. And with natural language processing to analyze unstructured data, like the contents of email and chat messages, the bank can monitor all information that its traders send and receive. When all of these data sources are compiled and analyzed, a very clear picture of behavior and context begins to emerge.
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The bank successfully met its SEC deadline for demonstrating compliance.
It has bolstered its ability to recognize patterns of behavior and to identify situations of concern more quickly—making it much more attuned to its traders and their activity on the floor.
False positives have been reduced by 66%, leading to significant optimization in the investigation process.
$7 million saved annually in investigation staffing
66% reduction in false positives
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