Capital markets may lead other sectors in low-latency network messaging, but they are laggards in leveraging ‘big data’ analysis.

“Retailers are light years ahead of Wall Street in analyzing their data to find out what their customers want,” said to Peter Giordano, managing director at Oppenheimer & Co. “Instead of analyzing customer data, the industry still relies on salespeople, relationships and actual trades to tell us what clients want.”

“It would be nice if we could recommend a product to a client after identifying a pattern over the past 18 months from client-data analysis,” he said. “I haven’t see it on The Street yet, but I think people are playing around with it.”

Giordano sees the problem not as a lack of data, but rather the lack of easy access to the data that resides in firms’ trading and Customer Relationship Management platforms, and the difficulty of analyzing it and turn it into actionable business decisions quickly.

Oppenheimer has used application programming interfaces, which enable one application interact with another, to access the data on the firm’s various platforms.

“I can tap an API against my trading system to pull out data and analyze it next to my CRM data, and come out with some very interesting information for my business folks and regulatory folks,” explained Giordano.

The firm also uses its data analysis capability to provide different data products for its customers as well as to improve revenue and cut costs, he added.

However, simply accessing more data is just the first step, according to Andy Brown, CEO of Sand Hill East Ventures.

“You can bring six data sets to bear and all of a sudden the set of questions you can as are completely different,” he noted. “When people discus analytics, what they are talking about is coming up with questions that no one else has ever thought of then you get the answer: It’s much better to route orders to this market on close than that one.”

Brown warns that generating those new set of questions will not be easy, especially for business analysis who think hierarchically using if/then or else statement.

“It’s very hard for people who haven’t been trained to think that way,” he explained. “This is why data science in financial services is such an important aspect of the future.”

Giordano and Brown spoke Oct. 21 at the MarketTech 2015 conference hosted by Tabb Forum.

Featured image via Dollar Photo Club