The recent movie "The Imitation Game" recalls how England recruited a team of code-cracking experts to break through Germany's enigma machine during World War II. The team went on to build a tool a computer that allowed them to intercept the enemy's secret messages.
Banks should take a cue from the Brits and put together a team of people who know and understand social media data and can play with it, manipulate it and influence it in subtle ways. As they refine these capabilities and build complementary tools, banks will be able to turn data into information they can trade on.
Social media data offers banks a vast, relatively untapped source of insights about everything from marketing to identifying new customers, talent and potential risk management issues. Warren Buffett called the stock market a weighing machine because it reflects individuals' opinions of the value of different companies every second of the day. Similarly, by putting customer relationships in the public eye, social media sites like Facebook and Twitter can now determine which companies will succeed or fail. The recent debate about the real color of "that dress" that set the Internet ablaze was a perfect illustration of the power of this new machine. Harnessing it is the next challenge for big data.
Developing the ability to tap into social media data, however, is far from easy. Twitter, for instance, estimates that over half a billion tweets are sent every day. This daily torrent of activity creates noise that overwhelms the analyst who lacks a clear and logical approach and who comes to the data flow without the right tools to navigate through it.
Come ready with such tools, however, and you can learn what people are saying about your company and its competitors.
Let's look at a few possible use cases. For example, imagine a sudden disruption takes place in the communications network enabling credit card payments. Signals indicating such a disruption may well appear on social media for instance, in customer tweets venting about the inability to make a purchase before they start appearing in call center traffic. Picking up those signals quickly and getting that data to people who can do something about it could be of great value.
Example two concerns a company's creditworthiness. Tweets or blog entries concerning a company's failure to make payments to key suppliers or debtors could be extremely useful data points to an analyst reviewing that company's probability of default.
Example three concerns product development. Tweets, blog posts and Facebook "likes" might help companies conclude, for example, that students are unlikely to take their business to banks that do not provides full mobile capabilities. Such insights could give additional impetus to new mobile initiatives at the bank.
Banks should model their attempts to mine social media for information after the approach of a trader looking to find an advantage over his or her peers. Traders do so by developing the ability to capture and analyze pertinent information from legitimate sources ahead of their competitors, and then by executing trades based on that information. Speed of both thought and execution is critical.
For companies trying to make use of unstructured data generated in social media channels, the ability to capture information, analyze it quickly and then make decisions based on what they have learned is critical to future profits and losses. That's why time is of the essence in breaking the social media code.
Andrew Waxman writes on risk and compliance issues in capital markets. He is a consultant in IBM Global Business Services' financial markets risk and compliance practice and can be reached at firstname.lastname@example.org or on Twitter @abwaxman. The views expressed here are his own.