DataSift Preps Financial Play for Social Data

San Francisco-based social media data aggregator DataSift has set up a group to focus on increasing demand from financial services clients, and has hired industry veterans Rob Passarella and Paul Balser to head the initiative.

Passarella joins from Dow Jones, where he was vice president of institutional markets, responsible for the agency's machine-readable news offerings, and has also held data and technology roles at Bear Stearns, Monitor 110, JP Morgan, Merrill Lynch and Morgan Stanley, while Balser was most recently vice president of business development and head of sales at social media-driven finance platform StockTwits, prior to which he held senior institutional sales roles at Cuttone Capital Markets, Cowen Group, Citigroup, Merrill Lynch and Lazard.

"If you use news in your models, this is a natural next step," Passarella says. Financial firms can harness DataSift's flow of social data either as a leading indicator of market activity -- such as for traders to predict price movements based on Tweets rather than news stories, since important events can sometimes break minutes or hours earlier on social media sources than on mainstream newswires, or to widen or tighten spreads based on events -- or as an indicator of "velocity" to show the level of interest in companies or topics, which can be further segmented geographically using location data integrated from a third party, which would allow analysts to look at consumer sentiment for a company's products in a specific country or region, for example, or to assign greater weight to sentiment from a certain geographical area, he says.

Rob Bailey, chief executive of DataSift, says the vendor originally focused on the social tech space, but was "amazed" by the range of companies in other fields that contacted it, especially from the financial industry. "Traders are increasingly viewing social data and what we do with real-time news as an important part of their trading process," he says. "For example, long investors are looking for sentiment around product launches and analysis of a company's competitors, while high-frequency traders are looking to analyze news sentiment. We're also seeing demand from broker networks where five years ago customers would call their broker to ask about something they had seen on the internet-now they are calling to ask about things they've seen on Twitter, and brokers have to be aware of that."

In addition, social media can provide a window into the opaque world of private company data, by allowing users to isolate what a specific company's employees are posting about. "Or if you see the executive team from a company all ‘checking in' at a restaurant in Redmond, WA [home of Microsoft], that could be a significant indicator," Bailey adds.

Passarella says the vendor will begin creating products tailored to the needs of financial firms, but which will be standardized in such a way that will be more akin to the standard datafeeds they are used to dealing with, before expanding to other markets, such as the UK, where the vendor already has a presence in Reading.