Inside Morgan Stanley's AI strategy

Morgan Stanley is on a mission to combine the best of machine learning, predictive analytics and workflow technology with the human touch provided by its 16,000 financial advisers.

Despite the popularity of robo-advisers, clients still want a human being to help them navigate complex life questions, according to Naureen Hassan, chief digital officer for wealth management at Morgan Stanley.

And not just the older clients. Recent studies show that 22% of millennials who work with a financial adviser want more time with that adviser, not less, Hassan said.

At the same time, clients also want a simple mobile app to keep track of everything when these decisions have been made.

"I don't want to be forced into in-person meetings or shipping and signing a bunch of paperwork," Hassan said. "I do want to manage my finances the way I manage the rest of my life, which is on my phone, on my terms. I want to use it to check my balances, to track my progress against my goals, to transfer money back and forth. I want to be able to do that on my phone and reach out to my adviser when I have to have those more difficult conversations."

Naureen Hassan Morgan Stanley InVest 2017

Hassan rose through the ranks on the business side of digital at Charles Schwab. A year and a half ago Morgan Stanley hired her for a new position leading this effort to help its 3.5 million clients manage their finances when and where they want to. She shared some of the story of Morgan Stanley’s digital journey in a presentation at the InVest conference last week, and some in a follow-up interview this week.

“There are many digital products that can make human advisers more efficient, effective, productive and, in general, just better advice givers to their clients who trust them,” said April Rudin, founder and president of the Rudin Group, a wealth management consulting firm. “The key is in the proper balance of tools vs. human touch.”

NEXT BEST ACTION
To help advisers engage clients, Morgan Stanley is developing a “next best action” system that will present them with investment ideas they can share with clients. It will use predictive analytics and machine learning to comb through research reports, market data streams, and client databases to come up with insights about clients, market events and the impact of events on clients’ portfolios.

"Morgan Stanley alone produces approximately 55,000 research reports a year," Hassan said. "All of our clients' life events, birthdays, securities deadlines, elder care Issues, service alerts, margin calls, maturing bonds – it is a mountain of information they're trying to process.”

Rather than “replace our advisers with some cyborg bot,” predictive analytics and machine learning will “help them be faster and smarter in serving their clients' needs."

Once the system is complete, when a stock is downgraded or upgraded, an alert will be sent to the financial adviser, along with a list of clients who are most affected.

“They’re using AI to leverage the structured and unstructured data they have in house for improving service,” said Alois Pirker, research director for wealth management at Aite Group. Such projects are not easy or quick to carry out, he noted.

“It’s not going to be a one-and-done type of exercise,” Pirker said. “You put a prototype out, see what works, get the response in the field and you improve on that. It’s not like implementing a portfolio management system where you can know from the beginning where you want to get to. Here you’re feeling your way into it. They have done a lot in this area already, which some other firms can’t claim quite yet.”

MODERNIZING CLIENT COMMUNICATIONS
Morgan Stanley is also building a communication system that will take the next best action ideas and use them to pre-draft emails financial advisers can send to their clients.

"Imagine giving an adviser a team of smart research analysts and client service staff who can sort through advisers' paperwork, hand them the most relevant insights exactly when they need it, pre-draft personal responses for their approval and send it out," Hassan said. "That's the promise." The system will then track which alerts clients clicked on and what advice they acted on, so it will learn over time what works best.

Advisers will have control over what is sent. “We’re not sending it through a Morgan Stanley email bot,” Hassan noted. “At the end of the day, the financial adviser knows their client the best, and is in the best place to make that judgement as to whether or not we’ve gotten it right and that it’s relevant for that client.”

Eventually, the system will also draft text messages (using Twilio software) as well as Twitter, Facebook and LinkedIn posts (using Hearsay Systems software) for advisers’ potential use, to meet clients’ preferences.

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“The day of Brexit last year, my adviser helpfully sent me a long, thorough email about what was happening in the markets,” Hassan said. “He then followed up with a phone call, which is a best practice. But he couldn't get a hold of me because I was in a meeting, and what I really wanted was a text saying, ‘your portfolio is down but don't worry, your retirement date hasn't changed.’”

The social media posts will let advisers publish their views on Brexit to their entire social network with a click.

Rudin sees value in helping advisers think through events and removing their more mundane tasks. However, she also sees danger in becoming overly prescribed in automating tasks.

“In my opinion, pre-drafted emails are a good example of this,” she said. “No client wants to receive the same email from their adviser or worse, the same email from multiple advisers from within a firm.”

STEAMLINING PROCESSES
To help advisers and support staff time devote their time to building and strengthening client relationships rather than on paperwork, the bank has invested in a workflow backbone it’s using to convert more than 20 tasks to self-service online and through mobile apps by the end of the year. (Hassan declined to name the workflow vendor the bank is working with.) Where it can, it’s implementing straight-through processing behind the scenes.

An example is wire transfers.

To do a wire transfer today, the customer calls a client service associate who asks them to fill out and sign a form and letter of authorization and fax it back. The client rep enters the data into a system, it’s routed to various people for approval and verification, and another rep calls back to verify the caller’s identity. The form is scanned into the system and the wire sent.

The new process might still start with a wire request call. A client representative will enter the information once in the system, which will send an alert to the customer’s mobile phone. The customer will approve it with a fingerprint and the transaction will execute. In the background, a fraud and data analytics engine will examine the client’s geolocation and compare their actions against their typical behavior. Paper will be eliminated and a process that used to take 20 minutes will now take less than five.

Hassan said the new process is also more secure than the old one.

The biggest type of wire transfer fraud the bank sees today, she noted, is old-fashioned email spoofing, where a hacker impersonates a legitimate customer and convinces an employee through an email to execute a wire transfer. That’s one reason the bank wanted to get away from using email as a method of communication for vulnerable transactions like wire transfers.

“We’re doing security by design,” Hassan said. “It’s not about replicating our current design process in a digital world, it’s about designing a new digital process that’s got multifactor security checks built in.”

Over time, client tasks like changing an address or moving money will all be available online and on mobile apps.

Morgan Stanley’s efforts and similar programs at UBS and other banks are an attempt to accommodate clients who still want human help.

“The key to understanding this new paradigm in the marketplace is the client point of view: one size does not fit all,” Rudin said.

This article originally appeared in American Banker.
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Wealth management Bank technology Machine learning Broker dealers Asset managers Morgan Stanley Morgan Stanley Wealth Management
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