“AI is specifically useful where there is a significant amount of data,” says the firm’s CEO, Chida Khatua, a former director of engineering at Intel. “And there is a way we can find or train the systems to understand the correlations.” That means evaluating both Excel spreadsheets and newspaper stories.

The $167 million fund’s AI model is based on how investors do due diligence on a company. They look at management, financials and how insight from news will influence companies’ profitability or equity prices. The idea is that the market trains the system to work better.

The fund charges a 0.75% expense ratio. The firm launched an international fund in June (AIIQ).

Robots Hunting Clients

Advisors are also using AI for marketing. Shirl Penney, CEO of RIA services firm Dynasty Financial Partners, recently told attendees at a Pershing Advisor Solutions’ RIA Symposium in New York that one of his firms on the West Coast did an entire marketing campaign based around artificial intelligence to bring in some $21 million in new client money.

“We wrote some simple white papers, very short and easy on ISOs, stock options, for Snapchat employees,” Penney said. The firm then used LinkedIn to target executives at the company. “The strategy was very simple: To position this group of advisors as experts in stock option cash-flow analysis, diversification, etc., running a concentrated position, in this case for Snap. And then we had a very simplistic AI tool that interacts with the client.” The advisors set the software and then let it do its work, Penney said. If a client clicked through (“raises a hand”) the software sent more educational materials on options. Ultimately, a meeting could be inked in.

“In the last campaign that we ran, [we got] 16,000 impressions. Nine hundred times the employees clicked through. It automatically, through the system, set up 15 meetings. Of the 15 meetings, the advisors closed seven of them. It was $21 million in new assets. Let me show you how much that campaign cost: $600.”

Ram Nagappan, chief information officer at Pershing, says machine learning can show patterns with clients and help predict when they might defect for another firm.

“We are using machine learning to give some kind of head’s up that this client could potentially leave,” Nagappan says. “We take data on who is the client, what gender, what status, tendency, tenure, all types of information that you have on the book of the business, then we use the previous history of why a client left and recreate a pattern. … This is a learning technique. You want to learn whether it is right or wrong and then you can correct the algorithm.”

Nagappan says the machines look at the assets a client has, the assets she’s transferring over a period of time, what similar clients did during book transfers and what transactions they pursued—as well as the clients’ ages, genders and employment statuses, dependency and how much online interaction they have had. The algorithm then shows patterns in a book of business similar to the patterns of clients who left in the past, Nagappan says. If someone is doing money transfers, or logging in and checking more frequently than ever, those are warning signs.

He mentions the big improvements in AI tools by Microsoft, Google and Amazon. Pershing offers these through its own portal and offers tools through its advisors’ own portals.