Financial services firms face some of the most complex information challenges in business today.
The amount of information available to support decision-making is staggering. Reuters publishes 9,000 pages of financial news every day. Wall Street analysts produce five research documents every minute. Financial services professionals receive hundreds of e-mails a day. And these firms have access to data about millions of transactions.
An advisor wants to be able to confidently recommend retirement planning strategies, investments and portfolio changes. Evaluating an investment target requires looking at a wide range of data and interrelated factors. Financial services professionals need all the help they can get in consuming and analyzing available data to improve decision making.
Help may be on the way from a 2011 Jeopardy champion – but not your average game show champion. Watson, the super computer named after IBM’s first CEO and industrialist Thomas J. Watson, was originally developed specifically to answer questions on the quiz show, and in 2011 famously beat noted Jeopardy champions Ken Jennings and Brad Rutter to win a $1 million prize.
Now, IBM’s Watson technology will be featured in a demonstration of financial decision making at the 2016 LIMRA Big Data Analytics Conference, set for June 21-22 in Boston.
Sridhar Iyengar, distinguished engineer, cognitive computing research at IBM TJ Watson Research Center, will discuss the future of financial decision making, using cognitive computing. This is a self-learning system that uses data mining, natural language processing and pattern recognition to provide insights from large amounts of unstructured data. Iyengar will show how Watson can combine traditional portfolio information with a stream of unstructured data such as social media, news, investment reports, etc. to provide relevant guidance for a financial advisor.
Dr. Jennifer Golbek, director of the Human-Computer Interaction Lab at the University of Maryland will provide the opening keynote speech at the conference and look at how scientists and companies leverage social data to develop a deeper understanding of consumers’ preferences and behavior.
“A real strength of this conference is the way it brings together professionals from both the business and technology sides of the industry,” said Eric Sondergeld, corporate vice president and director of strategic and technology research at LIMRA. “By having both disciplines in one place we can examine effective ways to use big data to make better decisions and solve real business challenges.”
Sondergeld will moderate a discussion on analytics featuring Louis DiModugno, chief data and analytics officer for AXA Equitable Life, and Victor S.Y. Lo, vice president of data science and workplace investing at Fidelity Investments.
The conference program — with the theme Illuminating Data — also includes interactive demonstrations, problem-solving exercises, and microsummits, and takes full advantage of being in Boston – often called the big data capital of the world.
The conference is being held at The Revere Hotel. For more information or to register online, visit: 2016 LIMRA Big Data Analytics Conference.
Watson learns banking
IBM is now partnering with financial institutions to teach Watson the business of retail and institutional banking. The ability to consume vast amounts of information to identify patterns and make informed hypotheses naturally make Watson an excellent solution to help make informed decisions about investment choices, trading patterns and risk management.
Watson is being designed as the ultimate financial services assistant, capable of performing deep content analysis and evidence-based reasoning to accelerate and improve decisions, reduce operational costs, and optimize outcomes.
In a bank, an advisor can use Watson to make better recommendations for financial products to customers based on comprehensive analysis of market conditions, the client’s past decisions, recent life events, and available offerings.
The ability to take context into account during the hypothesis generation and scoring phases of the processing pipeline allows Watson to address these complex financial services problems and assist financial services professionals in making better decisions.
Citigroup announced this March that it has entered into an agreement with IBM to explore possible uses for IBM Watson. Under the agreement, Citi will examine the use of deep content analysis and evidence based learning capabilities found in IBM Watson to help advance customer interactions, and improve and simplify the banking experience.
