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Sal Cucchiara

Industry Spotlight > Wirehouse Firms

Inside Morgan Stanley's Big AI Test for Advisors

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“AI will disrupt a lot of industries, but the way we think about it is certainly as a productivity lift,” Sal Cucchiara, Morgan Stanley chief information officer of wealth management and investment management technology, tells ThinkAdvisor in an interview.

The firm, which kicked off a pilot test of OpenAI GPT-4 earlier this year with 1,000 of its financial advisors, will roll out the software to all its financial advisors [about 16,000 in 2021] by the end of the third quarter, Cucchiara, a managing director, says in the interview.

Even before the pilot, Morgan Stanley was an early artificial intelligence adopter, introducing it in 2020, for example, in its Next Best Action system for customized messages to clients.

The advisors have been using AI in recent years for product offerings as well, Cucchiara says.

“OpenAI and large language models are just the next generation of AI’s advancement,” he adds, noting that Morgan Stanley is “really aggressive in thinking about how we use AI but taking a really conservative approach to rolling it out.”

Cucchiara is responsible for the firm’s IT strategy and the development and delivery of all investment and wealth management business lines, including E-Trade.

The firm is making a strong effort to safeguard its artificial intelligence from generating inaccurate information by using Morgan Stanley’s internal research and the firm’s own content exclusively.

That is, it is “not commingling the internet or anything external to Morgan Stanley,” stresses Cucchiara, who before joining the firm in 2016, was with Bank of America Merrill Lynch for 20 years, serving as chief information officer and head of the wealth and banking solutions technology organization.

In Morgan Stanley’s pilot test, advisors essentially have a “virtual assistant” that can access hundreds of thousands of documents, including advice and forecasts published by the firm’s Global Investment Office, which provides portfolio guidance.

A key advantage is that advisors are able to access AI responses’ source material to validate the veracity of every answer the system churns out.

The software also synthesizes accessed information to “get to the heart” of advisors’ questions, eliminating the need to pore over long documents for a specific sought-after answer.

The wirehouse’s foray into the new generation of AI mainly focuses on advisors obtaining basic information for administrative tasks to save them time.

However, in the pilot, advisors have the capability to record phone discussions with clients — with their consent — a transcript of which AI synthesizes and summarizes. That document can then be sent to the client after the advisor approves it.”

For the near future, the firm is looking at offering investing opportunities using AI based on client behaviors, such as their actions when visiting the Morgan Stanley website.

ThinkAdvisor recently interviewed Cucchiara, who was speaking by phone from the firm’s downtown New York City office.

AI is “all about how to take ideas that advisors have and get them to clients in a digital way,” he says.

“Having the advisors at the center and making sure they own the content that’s generated really propels our confidence about the accuracy of responses,” Cucchiara maintains.

Here are highlights of our interview:

THINKADVISOR: Advisors worried when robo-advisors came along: They thought they’d take over their jobs. Are financial advisors feeling the same way now about AI?

SAL CUCCHIARA: I was surprised that advisors don’t see this as a disrupter to them. But they do see the power of how it can enable them. They’re eager to learn how it can certainly empower them.

AI will disrupt a lot of industries, but the way we think about it is certainly as a productivity lift.

What do you see in the future for AI as a tech business?

This is really exciting unchartered territory in technology. There’s going to be lots of advancement in this space. The number of companies that are coming up right now to support AI is significant.

A lot of tech companies have pivoted their business models to be in support of AI and how they can support its growth.

You’ve been running an AI pilot test with your advisors. When do you expect to make this technology available to all your advisors?

Right now, we’re in the middle of piloting. This first stage is in the hands of a thousand advisors.

[But] we’re going to start ramping up. In the second half of this year, AI will be rolled out to all advisors, and that could be as early as the third quarter.

Will you be rolling it out gradually?

We could go market by market, but regardless of how we roll it out, by the end of the third quarter, it should be in the hands of all our advisors [in the U.S.].

What’s the bottom line when it comes to benefits to the advisors? Does it mean that advisors will have more time or give clients better advice?

We think it’s going to really help their productivity to serve their clients. If there are things they’re doing of an administrative nature — like searching for information on how to — this will, hopefully, eliminate a lot of that.

We know that it’s going to continually improve how the advisors service their clients, and it also will improve their productivity to take on new clients. This will only get better.

Please discuss the sources of the information that your AI provides.

We have our own infrastructure with OpenAI. We aren’t training their models on any of our intellectual property or our information. They don’t retain any of that.

That’s how we can get really comfortable with the security aspects of OpenAI.

Financial advisors, for example, are able to search and get access to information published and stored by our Global Investment Office [analysts, strategists, economists giving advice to guide portfolios] around economic, company or industry outlooks.

What specifically can the advisors do having AI other than access info?

We not only allow advisors to get access to information, but we can synthesize it in a way that gets to the heart of the question they’re asking to give them a thesis or bullet points or more detailed answers.

What else do advisors gain?

Advisors have been operating in a structured world. With AI, we can have unstructured data: We can use all the documents — whether procedural or product information or [as noted] information that comes out of our Global Investment Office.

We have hundreds of thousands of these documents. Advisors have to go and surf [the web] to get answers sometimes. Now we’re going to make it much easier to get access and synthesize the information so that they can enhance how they’re servicing the client.

We’re not only giving them the answer but mapping it back to the actual [original] document that was spun out: We’re giving them the answer but also going back to the part of the document from which we derived the answer.

This synthesized [approach] is almost like having a conversation with someone.

Instead of just reading the document, you’re also getting the specific answer [to your question].

How do you think AI will reshape wealth management?

We began our digital journey seven years ago. We wanted to make it easier for our advisors to service clients. Initially, we focused on automation for specific problems.

Then we rolled out a number of innovations, such as Next Best Action [AI-based engine delivering customized messages to clients guided by advisors].

This is all about how to take ideas that advisors have and get them to clients in a digital way by using some form of machine learning and AI.

We’re going to continue on that journey to enable advisors to service their clients with scale.

What sorts of safeguards do you have to prevent AI from generating inaccurate information?

We’re working only with our own content, not the information AI may have gained from reading the internet. We’re not commingling the internet or anything external to Morgan Stanley.

We’re just using the large language models on our own content.

That minimizes a lot of things, like [AI] hallucinations, which are really misguided.

Having the advisor at the center of this and making sure they own the content that’s generated really propels our confidence about the accuracy of the responses.

Our safeguards are that we can map it and test it against the curated answers.

Being able to go back to the sources of the document to make sure it’s valid helps us improve productivity. And this will only get better.

How else are you making sure that AI doesn’t give advisors false information?

We’re really aggressive in thinking about how to use AI, but we’re taking a really conservative approach to rolling it out.

By using AI to leverage the power of large language models to synthesize documents, the advisors can then go back to the answer key to validate [the information].

Please elaborate.

We’ve curated the 7,000 most frequently asked questions that a service agent will get.

If you ask the question the way we’re expecting, we’ll give you a curated, approved answer.

This gives us confidence that we’ll get the right answer and allow the financial advisor to not only have the answer but go back to the source of the document to make sure they can validate it.

Will your AI be capable of doing more complex things for advisors down the road?

We’re piloting a few things now.

If, say, I’m on a call with a client, I can record it with the client’s permission and afterward be able to synthesize the transcript and summarize the whole call, telling the client in an email exactly what we talked about and agreed on.

That not only would take a long time to do without AI, but AI simplifies the output, which the advisor can see before sending.

Does the advisor just click a button to make that happen?

Exactly. The advisor will be able to guide AI to determine how they want to synthesize the information from the meeting. Some might say, “I want a bullet format.” Others could say, “I want this in an email.”

We want to take these large language models and map them back to how we’re giving advice.

But the financial advisor is certainly going to be at the center of everything we’re doing in terms of driving advice.

What’s the game plan?

We’re going to start with the simple tasks.

Will the client be aware of the things for which AI is responsible?

Right now, everything is with the [advisor]. Our advisors have been using AI for the last number of years in our product offerings, [for example].

OpenAI and large language models are just the next generation in AI’s advancement.

Is using AI for sales opportunities on the horizon?

We’re going to be looking at opportunities through information we have about clients: As we [study] some of the behaviors they have, is there any opportunity for a product, and are we offering all the relevant products to them?

Machine learning will be at the center of those products.

We learn what’s working for clients, how we can understand their behavior — like what they’re doing when they visit our website.

All that information is going to help serve the client, and AI is at the center of that.

“The work we’re doing with [OpenAI] will allow us to bring our expansive intellectual capital into the hands of our financial advisors in seconds: It will be like having our chief investment strategist, chief global economic and global equities strategists on call for every financial advisor 24/7,” Jeff McMillan, head of analytics, data & innovation, Morgan Stanley Wealth Management, said in a statement this past March.

To what extent is your AI capable of strategizing like a human advisor?

It’s really access to the information that we have now, and how we understand it better, and how we don’t have to read a 20-page document to get the answer or a summary of it.

It’s about the simple basic administrative tasks: How to do something? What’s the policy? What’s the procedure?

Our goal is to reduce the time from hours to minutes that it takes to do things that you don’t do on a day-to-day basis.

Pictured: Sal Cucchiara


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