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

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

Forcepoint

Technology Category	Analytics & Modeling - Big Data Analytics
Applicable Industries	Finance & Insurance
Applicable Functions	Business Operation
Use Cases	Fraud Detection Regulatory Compliance Monitoring
Services	Data Science Services
Challenge	The international banking group was facing challenges in meeting SEC compliance regulations due to the increasing use of personal messaging channels and web forums by traders. The bank's existing monitoring technology was outdated and required a high level of manual intervention to identify and investigate potential compliance issues. The system was not covering the full spectrum of modern communication channels and offered no systematic ways to flag potential indicators of fraudulent behavior. These time-consuming investigations, a vast majority of them false positives, were costing the bank millions of dollars. Read More
About 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 a 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 knew they needed a better way to stay close to trader conversations and safeguard the trading floor. Read More
Solution	The bank partnered with Forcepoint to build a program to modernize and optimize its monitoring technology. Forcepoint Behavioral Analytics was used to provide a robust picture of trader activity and communications, with deeper context into what was really happening on the trading floor. The solution ingested old email data as well as other electronic communications like Skype chats, Bloomberg terminals, and more, and analyzed them for potential indicators of insider trading activity. Natural language processing was used to analyze unstructured data, like the contents of email and chat messages. The bank also monitored all information that its traders send and receive. When all of these data sources were compiled and analyzed, a very clear picture of behavior and context began to emerge. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Applicable Industries

Finance & Insurance

Applicable Functions

Business Operation

Use Cases

Fraud Detection

Regulatory Compliance Monitoring

Services

Data Science Services

Challenge

The international banking group was facing challenges in meeting SEC compliance regulations due to the increasing use of personal messaging channels and web forums by traders. The bank's existing monitoring technology was outdated and required a high level of manual intervention to identify and investigate potential compliance issues. The system was not covering the full spectrum of modern communication channels and offered no systematic ways to flag potential indicators of fraudulent behavior. These time-consuming investigations, a vast majority of them false positives, were costing the bank millions of dollars.

About 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 a 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 knew they needed a better way to stay close to trader conversations and safeguard the trading floor.

Solution

The bank partnered with Forcepoint to build a program to modernize and optimize its monitoring technology. Forcepoint Behavioral Analytics was used to provide a robust picture of trader activity and communications, with deeper context into what was really happening on the trading floor. The solution ingested old email data as well as other electronic communications like Skype chats, Bloomberg terminals, and more, and analyzed them for potential indicators of insider trading activity. Natural language processing was used to analyze unstructured data, like the contents of email and chat messages. The bank also monitored all information that its traders send and receive. When all of these data sources were compiled and analyzed, a very clear picture of behavior and context began to emerge.

Impact #1	The bank successfully met its SEC deadline for demonstrating compliance.
Impact #2	It has bolstered its ability to recognize patterns of behavior and to identify situations of concern more quickly.
Impact #3	The bank is now much more attuned to its traders and their activity on the floor.

Impact #1

The bank successfully met its SEC deadline for demonstrating compliance.

Impact #2

It has bolstered its ability to recognize patterns of behavior and to identify situations of concern more quickly.

Impact #3

The bank is now much more attuned to its traders and their activity on the floor.

Benefit #1	66% reduction in false positives
Benefit #2	$7 million saved annually in investigation staffing cost

Benefit #1

66% reduction in false positives

Benefit #2

$7 million saved annually in investigation staffing cost

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Overview

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

Operational Impact

Quantitative Benefit