Asset management systems are advancing beyond their traditional boundaries of operations and portfolio management to encompass using predictive analytics and artificial intelligence.

Frank Fitzgerald, director of technology at O’Shaughnessy Asset Management, said at Thursday’s TSAM New York Conference that a point of “technological singularity,” where artificial intelligence will have progressed to the point of a greater-than-human intelligence, is only 15 years away.

“Artificial intelligence designers are talking about a point of singularity by 2030 when the equivalent of human intelligence will be housed in a computer,” he said. “We have to start thinking about how that will impact our business. As much as we need to take requirements from the business, in the future, business will be driven more by technology.”

At O’Shaughnessy Asset Management, a Stamford, Conn.-based quantitative money management firm that manages $6.8 billion, Fitzgerald is responsible for ensuring the operation of an extended IT infrastructure while working closely with all departments to improve decision making, automating manual processes and developing robust risk controls.

“We have had a focus over the past six years on portfolio management, research, and trading systems,” Fitzgerald said. “But we’ve now started focusing more on sales. We sat in on sales meetings and what’s come out of that has been a business intelligence module that does things like making sure that when we send out e-mail and someone clicks, it immediately notifies people. It’s driving our sales process. It’s a good example of a new approach to technology.”

Kai Saathoff, CEO and founder of Saathoff Capital, a small private equity company, said that the role of technology has shifted from operations to more strategic goals, like using predictive analytics to ferret out customer behavior.

“Technology in the asset management industry has been in mainly supporting straight-through processes, such as broker confirmations,” he said. “I can remember faxes going back and forth, whereas now we use FIX.”

Previously, Saathoff worked for Deutsche Bank where he was responsible for the strategic development, implementation and day-to-day management of all client services to institutional investors globally.

Later, at Credit Suisse, where he headed the business management office, Saathoff built a system called ClientAlytics. “It’s a Big Data driven solution to enable client management to be more data driven,” he said.

Although conventional wisdom claims that since 2008, clients have placed risk above performance in their measurement of satisfaction, this is incorrect, noted Saathoff. “If you look at studies, 40% of overall client satisfaction is related to service. But which services have which impact? We have used predictive analytics to identify 360 degrees of signals that we use to measure the effectiveness of sales and marketing. Then we can identify the real things that matter to each client. That results in an understanding of which products the client is interested in, which enables you to focus your IT investments and reallocate resources.”