Questionable behavior and employee misconduct have cost financial institutions more than $200 billion in fines and settlements since 2009. The extreme cost of this misconduct is proving to be a daunting challenge for financial services institutions. Although surveillance offers a means of protecting investors, consumers and firms from fraud and misconduct, current surveillance methods are falling short. Accordingly, financial institutions are searching for new ways of addressing this ever-present problem.
Moving surveillance out of the silo
Traditional surveillance systems are not working, in part because market manipulation techniques are constantly changing. Even with hundreds of scenarios identified for use in surveillance, misconduct continues to grow in complexity and can extend across a variety of assets and venues.
In addition, modern approaches to combating fraud exist in siloes. Organizations monitor trading activities so they can use trading analytics to identify suspicious trading, but then they use completely different systems to monitor communications. When they record voice and audio, they use yet another set of systems for monitoring. This approach leads to two major problems: false positives become a common occurrence; identified incidents are not correlated or not substantiated, and other incidents are missed, not having been monitored in the necessary channels.
Taking a cognitive approach to surveillance
The IBM Surveillance Insight for Financial Services solution, a surveillance system powered by IBM Watson, can go beyond current surveillance approaches such as rules-based systems or lexicon-based systems by using a cognitive approach to identify patterns not previously considered. Indeed, cognitive computing can look at actual behaviors, then use machine learning to go beyond predefined rules.
Using the IBM Surveillance Insight for Financial Services solution, organizations can set a baseline for how traders act in their normal trading behavior, taking into account types of trades, assets traded, trade volume and dollar amounts traded as well as communication style. This latter approach uses Watson’s varied cognitive capabilities, including its personality insights and tone analyzer features, to identify the tone used in communications, whether they are angry, excited, disgruntled or pushy—even overly excited or overly pushy. Changes in a trader’s communication style can be identified as indications of possible wrongdoing.
Building a framework of learning
A truly cognitive system such as IBM Watson is about more than just understanding and reasoning; it’s about learning over time. As Watson identifies patterns, these patterns become part of its collective knowledge. Accordingly, the planned acquisition of Promontory by IBM offers a means by which to heighten the level of expertise that goes into training Watson. This technique is expected to allow Watson to learn by continuously ingesting regulatory information as that information is created, as well as through interaction in real-world applications. Infusing the system with the learning that results enables a capability that IBM is calling proactive compliance—identification of potential patterns of misconduct before that misconduct affects an organization, market or customer.
IBM Watson is extending surveillance capabilities far beyond areas having to do with trading activity, reaching throughout the organization to help identify potential instances of sales malpractice. These surveillance capabilities are expanding to wealth management to ensure adherence to Department of Labor stipulations that wealth managers act in the best interests of their clients. Accordingly, IBM Surveillance Insight for Financial Services takes a holistic approach that looks across trading activity, specific actions and communications of the trader and even client recruitment to help identify questionable behavior and misconduct that might expose the company to risk.
Marc Andrews is vice president, Watson Financial Services solutions, at IBM and is responsible for industry-specific IBM analytics solutions. Andrews manages a group of industry-aligned teams that are driving the design, development and delivery of solutions to help organizations extract insights from the modern data explosion in support of their key business objectives. He meets with business and technology leaders from clients in multiple industries across the globe to share best practices and identify ways that they can take advantage of emerging big data and analytics capabilities to drive the creation of business value.
April Rudin is founder of the Rudin Group and is an acclaimed financial services and wealth management marketing strategist. A digital and traditional media expert, Rudin is noted for her ability to forecast, analyze and illuminate critical trends in the industry, which allows her to create campaigns that enhance brand and professional visibility. The Rudin Group, founded in 2008, designs bespoke marketing campaigns for some of the world’s most important wealth management and family office firms, focusing on digital strategy and multigenerational marketing.
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