Greater Visibility into Trading Floor Communications Saves This Bank $7 Million in Projected Investigation Costs
Customer Company Size
Large Corporate
Region
- Europe
Country
- France
Product
- Forcepoint Behavioral Analytics
Tech Stack
- Natural Language Processing
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
Technology Category
- Analytics & Modeling - Big Data Analytics
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
Use Cases
- Regulatory Compliance Monitoring
- Fraud Detection
Services
- Data Science Services
About The Customer
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.
The Challenge
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.
The Solution
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.
Operational Impact
Quantitative Benefit
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