Rise of the Machine

Are human advisors at risk of obsolescence as advances in artificial intelligence accelerate? By Timothy Inklebarger | Winter 2017



The age of the robo-advisor is among us. Over the last few years, industry leaders like Vanguard, Morgan Stanley, H&R Block, EY, and others, have made their first ventures into the world of artificial intelligence (AI) and machine learning—and that’s going to mean big changes throughout the financial services industry.

The question many ask, however, is whether customers and clients will simply trust emotionless, lightning-fast computers and their complex algorithms to help them make their most important business and financial decisions. The answer: They already are— many without even realizing it.

And therein lies the threat. To what extent will human advisors— particularly those resistant to change—be replaced by the rise of machines?

ARMING AI

“It’s impossible to know what the job losses will look like because of AI, and rapid advances have made that uncertainty greater,” says Brian Uzzi, a thought leader on social networks and big data, professor of Leadership and Organizational Change at the Kellogg School of Management, and co-director of the Northwestern Institute on Complex Systems (NICO).

What’s more, companies that embrace AI are using it to expand their businesses and relationships with clients, which also impacts labor needs. “The world of AI is creating efficiencies in industries where the bottom line is the top priority,” Uzzi says, pointing to Morgan Stanley’s move earlier this year to arm 16,000 financial advisors with algorithms that recommend trades and take responsibilities for more mundane tasks as proof of concept.

And for those who are reluctant to adopt such technology? Well, they’ll get left behind. “I think in some industries, particularly the financial services industry, job loss is not necessarily seen as a problem, but deeply embraced,” Uzzi says.

Indeed, many firms will likely be eager to phase out and automate some human jobs in pursuit of profits. “AI will eliminate people who are doing the routine stuff, so you have to move them over to the predictive stuff,” suggests Willard Zangwill, professor emeritus at the University of Chicago Booth School of Business. “CPAs, accountants, and finance professionals are in a fantastic position because they understand data, particularly financial data, that is important to business—they will be tasked with understanding how data is going to help the different aspects of a company.”

IN DIGITS WE TRUST

In fact, we’re already seeing the merging of man and machine, accountant and AI, in the tax space.

In February 2017, H&R Block, perhaps the most widely recognized tax preparation company in the industry, announced an alliance with IBM’s Watson, an AI system that originally gained fame by competing, and winning, as a contestant on the television quiz show “Jeopardy!” in 2011.

“We are introducing something this tax season that is totally new, and is in fact, a first in the tax preparation category,” H&R Block President and CEO Bill Cobb wrote at the time of the rollout. He went on to claim the combination of “the human expertise, knowledge, and judgment of our tax professionals with the cutting-edge cognitive computing power of Watson” will benefit both tax professionals and clients.

Cobb noted in Watson’s introduction that customers and tax professionals are faced with “a federal tax code with more than 74,000 pages and thousands of yearly tax law changes.” And that’s where Watson comes in. With its extreme computing power, Watson can parse and present the subtlest changes in the tax code, alerting tax preparers to discrepancies in filings and arcane rules that, when accounted for, can equal big savings for clients. The beauty of Watson is the more data it is fed, the smarter it gets, making the tasks of tax preparers and accounting professionals easier as they go.

“This technology allows for the best of man and machine,” says Meg Sutton, H&R Block’s director of retail client experience. She explains that the company views Watson as “augmented intelligence” rather than “artificial,” because in an AI platform the computer is making the decisions for the user. With Watson, the tax pros still make the final decisions. It’s a refrain commonly heard among the companies arming themselves with AI that still want to ensure their clients that their money is safe in the hands of a human being—but even this is changing.

MONEY MACHINES

The upstart firm Dream Forward, a technology-based provider of modern 401(k), 403(b), and 457 plans for businesses and nonprofits, has built its business around an AI platform designed to lower costs, simplify retirement investing, help employees feel emotionally confident in planning and saving for retirement, and help advisors understand what their clients are thinking—i.e. worrying about college savings, how matching works, or asset allocations.

Actions like early withdrawals, major shifts in investment strategy, or simply taking too long to make a decision can trigger Dream Forward’s always-on AI chatbot to ask questions and issue warnings to users in easy-to-understand English as they navigate their accounts.

Grant Easterbrook, the former robo-advisor analyst and consultant turned Dream Forward co-founder, describes the Emotional Advisor technology they developed as “conversational AI used to talk to clients and keep them on track.” For example, if the client lowers their savings amount, the AI, which looks like an online chat, will pop up and ask why the client did that in an attempt to talk through the concerns and reasoning.

“The goal of the technology is to keep users from taking negative actions,” says Easterbrook, who believes that mission is best accomplished with technology that's designed to work with human financial advisors rather than replace them. Dream Forward’s AI shares what it has learned from clients so the human financial advisors working with the clients can custom tailor their outreach based on specific needs or concerns.

Here again, we see the merging of man and machine rather than replacement—for now. Uzzi says he believes smaller companies, particularly those operating in the retail space of financial management and traditional brokerage services are susceptible to an Uber-like disruption; however, the high net-worth clientele segment is more likely to be protected due to the importance of personal relationships.

“These clients often make financial decisions based on emotion and want the sense that the human they’re talking to is watching their backs,” Uzzi elaborates. But that could change as time goes on and the more tech-savvy generations begin saving more. “If I create a machine that provides the same sense of emotional security, and it makes a better decision than a human being, I think people will be happy to work with a machine,” he says.

REGULATIONS RISING

The machine learning used by Watson, for instance, is the same kind of technology being used in developing self-driving cars. If consumers are willing to put their immediate lives in the care of a machine, will they do the same for their financial lives? Uzzi thinks so, but as more firms and consumers turn to AI and other technologies, it’s only a matter of time before safeguards will have to be put in place.

Easterbrook says this has been a topic of great interest to his company, and Dream Forward has been careful to build its AI platform in a way that does not create a liability. “Our technology will not tell you to buy this or sell that. Our investment lineup is picked by an investment fiduciary and uses low-cost institutional funds; there’s no proprietary AI-driven active management strategy,” Easterbrook explains. “There’s no case law on using AI for financial advice yet. But Dream Forward isn’t taking any chances; this is a whole new area that hasn’t been dealt with before.”

What hasn’t been dealt with yet surely will be, and Uzzi believes that it will be AI technologies at the forefront. “As technology advances, consumers will become increasingly comfortable using AI to help make important life decisions,” he says. “In the future, the most important contact in your social network might not be a human being but a machine.”