Is artificial intelligence software mature enough for the investment industry?
Jeff McMillan, chief analytics and data officer at Morgan Stanley, has some doubts.
Wealth managers need to provide accurate, specific advice about clients' portfolios, he pointed out. And artificial intelligence isn’t reliable enough to provide consistent insights right now, he said at the InVest conference in New York last week.
"If you ask Alexa for a song and she gives you the wrong one, it's not a big deal,” McMillan said. “If you ask an AI engine a question about a customer holding and its answer is about the wrong asset class, it is a big deal. The level of accuracy is important."
The idea that artificial intelligence software could help financial advisers assist their clients more efficiently has been floated since 2013, when ANZ Bank in Australia became the first bank to announce it was working with IBM's Watson technology. At the time, the bank said it was planning to use Watson to assess new customers’ financial situations more quickly and comprehensively than a financial adviser could and help create financial plans. The bank spent more than a year feeding the system documents and questions and answers, and reportedly put it into production in one location last year.
A few other investment management companies have gone public with artificial intelligence for financial advisers. BlackRock has built an AI-based risk management platform called Aladdin that is used in-house and offered to institutional investors. It also offers Aladdin Risk for Wealth Management, a subset of the Aladdin platform, to wealth management clients. Goldman Sachs uses the AI-based financial research platform Kensho. UBS, Deutsche Bank and others are using an AI engine called Sqreem.
McMillan said that in a firm like Morgan Stanley, much of the detailed knowledge is in people’s heads. Chatbots are not equipped today to handle queries like "what the IRA policy is for a 65-year-old client who lives in the state of Utah," he said.
People with questions are more likely to chase down the experienced person who knows the answers.
"That's how human knowledge is largely transferred in an organization, even today," McMillan said. "Search really doesn't work. But that information exists in the four walls of our organization. Imagine a world in which all that knowledge could be transferred into a system and people could contribute that knowledge, and then using natural language processing you'd be able to access that instantly." (Morgan Stanley is building such a system; this will be covered in a future column.)
Getting it right"If you ask Alexa for a song and she gives you the wrong one, it's not a big deal,” says Jeff McMillan, chief analytics and data officer at Morgan Stanley. “If you ask an AI engine a question about a customer holding and its answer is about the wrong asset class, it is a big deal. The level of accuracy is important."The AI systems out there today can't really do this, he said. And AI might not even be the right idea.
"I'd rather have curated intelligence," McMillan said. "I'd rather not live in a world where I'm trying to get a neural net to figure out what you're trying to say to me. I'd rather have a world where I ask you what you're trying to say, I tell you to say it in a structured way and I enable my financial advisers to access that knowledge in a structured way."
McMillan acknowledged that natural language processing, a component of AI, has gotten good at understanding spoken questions and getting the intent.
