Wealth's State of Readiness for AI Adoption in New Client Acquisition

Transcription:

Michael Moeser (00:10):

Kat, welcome Rachel.

Rachel Witkowski (00:12):

Thank you for having me.

Michael Moeser (00:14):

So Kat mentioned that we're going to be talking about a study and that's going to form the basis of our discussion today. This study we conducted earlier this year in Q3 of almost 300 different financial advisors and wealth management about their wealth management business. The purpose of this study, the goal ultimately is to understand usage and perceptions of generative AI in wealth management. In particular organizational preparedness for gen AI adoption and the use of gen AI specifically in marketing and client acquisition. So we did a little bit of learning in the unleashing AI earlier in the year. Could we start the time please?

(00:58):

And then this is a further refinement of that effort, as you can see in terms of who participated in the research, about 65% of the respondents were director level or higher. We had a very good mix of folks, independent brokers, hybrid RIAs, wirehouse brokers say that fast several times. And in terms of the mix of the firms, a number of small firms with less than half a billion in assets under management. And then a good balance of that half a billion to five and then 5 billion and over. So a good array of respondents. And I'd really like to start out here, Rachel, in terms of one of the things that Kat had mentioned, this is the second deep dive and it always feels like the financial planning team is always asking about ai. AI is in your title as one of the tech reporters. What is it about financial planning and its interest in learning more about the growing role of artificial intelligence?

Rachel Witkowski (02:06):

Sure. So I think as you all know, particularly in the last two years, there's been a lot of AI tools that have emerged in just our everyday household. I mean, you hear it on the news with big names like Nvidia, I'm seeing my kids starting to use ChatGPT, and just through that there's been a gradual adoption, I would say largely in the last year of the wealth management industry and wealth advisors starting to practice with it well or more so well largely in large language modeling. And you guys all know this as well, but most of the time I think with our study with Schwab, I've seen other reports with Orion. When we ask in any of those reports, when we ask them how many of you're using AI in certain aspects of your life, it's sort of that 30 to 40% adoption rate currently. But when we ask about what's the percentage of you they're going to use in the next year or two years, there's far greater adoption. So the hype is very present and that's kind of where we see the next year far more adoption than what we're currently seeing.

Michael Moeser (03:15):

Makes sense. Makes sense. So we're going to go through several slides here. We're going to try to break it up into two, three sections, three actually, and the slides are available for the audience to download. In this first section, we're going to really be talking about marketing being a challenge and the tech focus that's currently in play. We ask the question, what are your firm's biggest obstacles in marketing and prospecting for new clients? Finding the time to do was number one, followed very closely by finding the right tech tools to help. And then you see further down determining the right channel, personalizing that communication. So there are some key obstacles in terms of what advisors and their firms are seeing in terms of getting out there and marketing to potential clients. Prospecting for those new clients, finding the time to do it and finding the tech tools to do it are number one and two.

(04:10):

And then we ask the follow up questions. There's two questions we asked here. The first one was, how effective are you are in leveraging technology in your client marketing? And no surprise, I guess if you don't have the time to do it, you're not going to get familiar with the technology tools. And only about one in five said that they were very effective or extremely effective, half said they're somewhat effective. And then you've got a bunch of people who are not really effective at all in using technology. And the follow-up question, I mentioned that we talked about what have you been doing with tech? It's where has that success? Where have you seen the success in leveraging that tech? And if you see the stages here one through five, these are a funnel that we created with the financial planning people in terms of identifying those prospects, marketing, outreach, onboarding. Then when you've got them that account management and the account expansion and retention. And so really in the latter two phases is that they're feeling more successful, being able to leverage technology. And Rachel, I really want to ask you here in terms of I guess two things. One is do you think this lack of time and technology and focus on technology to prospect comes as the industries have the reliance on referrals? Does that have a factor that I can always fall back on my referrals instead of using tech?

Rachel Witkowski (05:40):

I guess I'm going to split up this question a little bit please. I think if anytime you talk to an advisor, there's no way you can minimize, referrals are so important unless you're just going to go out there and make acquisitions constantly, which isn't always going to be the best long-term strategy. I would say if you're not, and you guys know this more than I, if you're not in the business of referrals, this is the wrong business to be in because people have to trust you to handle their finances. I mean, I go on referrals for my finances, I go on referrals for my mechanic, A lot of those very personal aspects. So I don't think AI is not going to be, if you're bad at referrals, AI is not going to fix that. You have to be good at it in the first place.

Michael Moeser (06:23):

Makes sense.

Rachel Witkowski (06:24):

But you can use AI in ways. The ways that I've seen it are just communicating more effectively and more efficiently with more clients to gain referrals and meaning. As an example, I've seen some technologies where it is creating auto alerts to clients, identifying, and we can get more into this later too, but identifying the types of clients you should be immediately sending a message to if you're seeing some abnormal activities and market reactions and that sort of thing. But I think at the heart of it though, you still have to be really good with your existing clients for them to want to refer you to somebody.

Michael Moeser (07:04):

Well, now you wrote an article, if I focus on the backend here, the stages four and five where people feel like they're very successful in leveraging tech. You recently wrote an article about Schwab surveying advisors. They prefer that AI be part of that back office, and it sort of feels like account management transactions, account expansion, retention, feels that there's part of that back office. Is it a comfort factor?

Rachel Witkowski (07:30):

I think that's just the biggest, and this kind of goes back to the time save point. When I talk to advisors, they're spending most of their time onboarding a client on onboarding documents, closing contracts, clients. There's an increased demand for more emerging type products, ETFs, ETPs, all these systems that I'm starting to see AI as sort of the overlay to that to help streamline those systems to communicate. And I think those are the time sucks where you can really apply AI to reduce that time and being able to read estate planning and tax documents and those sorts of things to create summaries. And I think this goes to a lot of surveys I've seen throughout the year in terms of just being able to manage those accounts faster. And it's some incredible stuff out there.

Michael Moeser (08:19):

Now as we talk about managing accounts, I mean there's the great wealth transfer, I think 70 trillion or whatever, it's a huge number. And I guess that probably plays a factor in terms of you've got these clients, you want to manage that. And you recently wrote about pure facts using AI to help focus on revenue leakage. How does that play a role in terms of, you mentioned alerts as an example, but is there the sense of I'm getting paid doing this, I'm now using AI to find those where people are sneaking off to open new, I guess Robinhood accounts or whatever they may be, not to use them as an example.

Rachel Witkowski (09:05):

And I should have said, I do tech spotlight every week. I don't play favorites to any names that I'm going to claim in this. It's fair game. If you can explain well to me what you do, I can explain it well to the reader. So there's no favoritism here just to say, and my opinions are my own. So going back to pure facts, every certain tech providers offer a very specialized service. So when they talk about data leakage, they're talking about sort of finding data, IE the money. When a firm is getting paid out, they sort of handle the revenue management and they're using AI to detect when maybe those, what am I trying to say? The timelines for when you get paid are shortened within the fee-based platform. So that's the sort of data leakage they're looking at. I was thinking of another one, Merrill, I was speaking to them recently and we were talking about there was a market drop in August over the weekend, and then Tuesday it got better, but there was a momentary panic and they were using AI to alert the advisor of, Hey, a client opened our market insights report.

(10:11):

Maybe you should message them real quick, or let's draft a response that we can send out to those people who have opened that newsletter during that drop. And so those are sort of clever ways. It sounds so simple, but it just streamlines that process so much faster. And that way you don't have to, if you have hundreds or so clients, you can kind of figure out which ones you might need to respond to quicker. And AI's already helping that.

Michael Moeser (10:37):

Well, that's a great segue in terms of the role of AI. And in these next couple of slides we're going to talk about, we've asked advisors and their firms, how important of a role do you believe gen AI-based technologies will play in your firm's efforts to capture new clients and or retain children inheriting wealth from your existing clients? And what you'll find very interesting is in this slide, as you go from left to right, you see that the smaller firms feel that about a third feel it's extremely important or very important. And then as you get to the very large firms, 5 billion and up, we're at two thirds saying it's going to be very important. But then the next slide, when we ask the question of, okay, now I recognize you large firm say it's two to one going to be very important, where do you put your money, where your mouth is in terms of critical or high priority?

(11:33):

And we're relatively almost flat, 36% of small firms, 31 and 35% respectively of mid-size firms, 40% of larger firms. So there's a recognition in the larger organizations that it's going to be very important. However, in terms of as a priority today, not as high. And I think when you look at the next slide, you'll get a perspective in terms of how prepared are you to take advantage of gen AI based tools today? And we asked the question across four different factors from culture, 15% said they were very well prepared, 23% said they were well prepared. And then as you go down the list in terms of technology, infrastructure, process, workflows, et cetera, staffing talent, much, much, much less. And while culture is better prepared, it's not universal. Several obstacles remain from technology process workflows to having the right talent to leverage. And I want to talk about firm culture here. Rachel, you recently wrote an article about how AI is changing financial advisor jobs, and I don't know if there's a question here, ai, will people get fired because AI takes their job or will it repurpose them? So how is AI impacting financial advisor jobs?

Rachel Witkowski (12:57):

Yeah, I love to ask this question because people get very opinionated about it. And then I've had people say, well, there's the Texas instrument and we're still here using our phones to do calculations or what have you.

(13:13):

It is interesting. I think about this a lot too, even from a journalism perspective and coming from big organizations like the Wall Street Journal that had a ton of layoffs earlier this year and we wanted to blame it on AI then too. It has a role, but I don't think it has a role that would take away a job. I think if you're good at what you do as an advisor and you're already a trusted advisor, AI will help you be better. But if you're already not a good advisor and you're not applying ai, you're probably not going to succeed anyways. I do think AI won't necessarily take a bunch of jobs, but I think it will change the daily role of an IT acts as an assistant. So now ideally you should have more time to invest in your customers. It's going to change what we do.

(13:58):

It changes what I do as a journalist. So I spend less time writing an explanation of what an ETF is, plug it into a certain application that I use, writes it up better than I probably could have thought about it in five minutes, but I'm monitoring it and I'm putting those compliance measures. And I think that's what a lot of advisors are going to end up having to do is be sort of that last checkoff. You're going to have to be your own compliance officer in that sense and your own monitor, your own editor. And that's kind of how I think the role might shift a little bit.

Michael Moeser (14:32):

No, we talked earlier in the last few slides here in terms of recognizing AI is going to be impactful. The larger organizations were clearly two to one versus the smaller organizations saying AI will probably have a bigger impact. But in terms of priority, not difference in a priority. And I wonder if there's a case where larger firms, because even though they have larger budgets and more people in their IT tech stack, they probably have a lot more legacy technology. Are they at a disadvantage because of all that existing infrastructure? Because to use AI more effectively, you've got to eliminate those data silos modernize the tech stack. So is there a challenge or is there an opportunity for smaller firms here?

Rachel Witkowski (15:21):

Interesting. I'm going to say it's a mixed bag. I only say that because obviously the big firms, they have a bigger tech budget and yes, we all have legacy systems. They might be able to adapt faster just because they have the budget and more a greater resource. I do think the smaller firms might be able to test out more products in ways that they're not as bound to these mega firms testing it out more so in the back office because you do have to be careful about consumer facing technology and compliance. And I should preface everything. I covered the federal regulators for 15 years, so I'm going to always talk from a very regular story.

Michael Moeser (16:08):

Well, no, I think you raised a great point about compliance of regulatory because clearly that has an impact. And I guess as you've been talking with firms, is there an overhang of that regulatory compliance? How do I make sure AI that I employ doesn't go awry?

Rachel Witkowski (16:27):

Yeah, and that's a scary thing when we're talking about the Schwab survey. I think 80% of them said they weren't ready to adopt it, and it was largely one large language modeling hallucinates, we, there's a huge, and we can get into this more, but a huge concern about data flows.

(16:46):

If you have a vendor third party, are they sharing some of that information with another third party? Yeah, so I should say, I was at a FINRA conference recently and it was a very interesting discussion about large language modeling and say, use dictation services. Well, even at our company, we'll either ai it and share it with a team who might've missed it. But how do you know that information is just being housed within the certain select people? Are you aware of the toggles of whether or not it's being public or private and that sort of thing? And this is very even more sensitive when you're dealing with clients who are giving personal information and that they're aware of, Hey, AI is being used to record this conversation. Are you okay with it giving out permissions upfront and FINRA, SEC, all those guys are looking at it, not just, at least from the outside. My interpretation is they're not anti AI, but they're very use case watching it.

Michael Moeser (17:48):

And that's not restricted to the wealth management industry. I think as we've researched other industries and banking mortgages, et cetera, there's a big concern around compliance issues, regulatory, do I trust AI to create the filing? And there's this common human in the loop, you can create the filing, but I want to have Michael or Rachel read the filing to make sure there's no misleading or incorrect information or hallucinations. We do see that quite a bit and that definitely is, perhaps that sort of feeds into maybe why people aren't so well prepared. And I guess could it also be we don't know the full potential of gen AI?

Rachel Witkowski (18:32):

Yeah, we don't. When you talk about that now you're getting into the real scary stuff, the deep fakes. I was thinking the other day, I was talking to someone at the SEC and we were talking about one of my institutions just last year implemented technology where I have to say a sentence to get into my account, and now that's a complete wash ai. I was at ACC conference and they're like, we need to think about this now. And I'm like, well definitely impact, just go back to password logins. But it is an interesting time, and I understand the hesitancy, especially within the financial services space to adopt AI because we just came out of, what was it, 2022 where everybody was really getting into chat GPT. Now there's already four versions and it's moving so much faster than us. And it's very, I am fascinated by the Microsoft discussion this morning about sort of having that verbal conversation with ai. And obviously you guys can probably tell I'm coming from a very regulatory conservative mindset, but I'm not sure I'm ready to debate AI verbally yet. I'm okay with writing and we'll write back, but that's just a personal opinion.

(19:46):

But you think about, if I can go off on my regulatory tangent here too, we have to have record keeping. And so how do you record keeping a conversation like that? And when you're talking about summaries, I am hearing these discussions with the regulators too. When you're talking about summaries, what if you adjust, you had an otter or fireflies AI and a conversation with a client and you just sort of adjust the summary to send to them, but you hold that as a record in your CRM, what if you tampered with it and the SEC comes in and says, Hey, this was adjusted, or maybe they won't. I mean, there's so many different areas that I understand the hesitancy. I'm not saying don't use it because it's helpful, but these are things to keep in the back of your mind as AI evolves,

Michael Moeser (20:28):

I guess we're still in early days on that.

Rachel Witkowski (20:30):

Yeah.

Michael Moeser (20:30):

So I think a lot of times as new technology comes in, often the regulators are little late to the game or they look at where it may have been used incorrectly to set as a precedence. So that is the challenge. Well, in this next section, we're going to talk about steps firms have taken. And so we asked the question, to what extent has your firm and its employees taken in terms of adoption of gen AI based tools and the larger firms have taken more steps, and that could be a case in terms of having larger budgets, more people. The challenge of that legacy technology infrastructure that more needs to be done in terms of being able to prepare your firm and its employees for adoption in terms of the steps taken themselves, we ask. So okay, which if any of the following actions has your firm taken or to encourage its employees to prepare for the adoption of gen AI?

(21:33):

No surprise. Number one is modernizing the tech stack. gen AI requires large data sets, needs to be able to access those readily very quickly. And so there's a big focus on data itself, data management, data governance. And then the next set of sections really is around how do you create those policies? And we'll come back to this particular point, creating the policies of on when and how AI can be used at work, encouraging the use of AI-based tools. I know when ChatGPT first came out, we all jumped on and we started using it and then it just didn't seem to work for a while. And now it's, I guess in the four versions that are available, we're testing it more. But really people are learning from industry publications that talk about AI and then creating that sandbox or testing environment for AI tools. And so we'll come back to this slide for a question on creating the policies.

(22:31):

But this last slide here in terms of focusing, where are they focusing the AI efforts? And if you look at this chart, the stage four and five at the very top, successfully using tech at each stage, this is where companies have been very successful and they're still aggressively pursuing gen ai. But as you can see at the very bottom in the blue section, stage one, stage two, identifying prospects, data mining, marketing outreach, that's where a big focus, they haven't hit that success yet, but this is where firms are really spending a lot of time to focus on the application of AI reaching out. So Rachel, let me go back to the previous slide because you and I chatted and you recently wrote something. How do you get AI approved at your firm? And this is something that we at our work have been thinking about quite a bit. And so you recently wrote about this, so maybe could you talk about how do you get AI approved at your firm?

Rachel Witkowski (23:40):

Be best friends with your compliance officers? No, I've seen

Michael Moeser (23:44):

Spoken from a,

Rachel Witkowski (23:47):

I've seen different methods, and we can talk about culture too, but everybody has a different method. So I've seen some that require that upper executive leadership to work with compliance to test it out. I've seen it where they started with middle management and somebody has to be willing to go through these demos, first of all. And so I've seen it where you have your team that's willing to go through the demos and then they report back to senior leadership and the compliance and figure out whether or not it's worth it or can we get it past compliance. But I guess at the forefront though, there needs to be an openness to trying things in a safe space. I would definitely put somebody in compliance at the front of that. But then also a level of, and maybe this does come from the compliance team, but a level of, hey, it's okay to test out AI in these specific ways.

(24:44):

And definitely in some of the slides we've seen too, I wouldn't do it consumer facing initially, but more internally, but creating that environment where you have a team, and even with us, we have sort of a core tech team that'll test it out and they might pull me in to test one particular product or a video product or that sort of thing. And just sort of creating these teams. I've seen Raymond James has tech ambassadors that go to the offices and different offices and sort of teach the folks how to do that tech luncheons or what have you. It is sort of hard to get people to show up at luncheons. I've seen people do a day event where you interact with different tech providers and do sort of that human, it is kind of funny to teach tech. You have to have a human interaction.

(25:35):

I feel like it goes a lot better when somebody's actually showing you how something works and we can't lose sight of that. I think the worst thing and doesn't, I've never seen it adapt very adaptable in my own space to just say, Hey, we launched this new layout system, figure it out. Here's a PowerPoint slideshow presentation on it, and go, I really needed somebody to sort of walk me through how I can actually use it at my own company. So you really almost need a team, an ambassador team, and then obviously compliance either right at the forefront or somewhere in the middle of it.

Michael Moeser (26:13):

Well, one thing we've noticed from the research that we've done in the interviews that we've done, there's a great fear of, people often feel, I've got to boil the ocean, set up this big thing around AI being used in every individual aspect of our company's business. And from some of the best practices that we've learned is to take a particular element doing maybe on an application and matching names, verification of names. So basically taking one piece and one effort, applying AI to that and having a human review that information, review that application, and then all of a sudden you find out, well, we're doing that income or name verification and 30 other places, how do we go about and then do that same thing in those 30 other places. So oftentimes picking something small as an example and then having a success and moving that forward.

(27:13):

We've heard that a lot of companies feel that that's a great way to start with ai. And so I guess that's one of the ways to manage. But definitely having the compliance team onboard from the get go certainly sounds like a good success factor. Let's talk about in terms of the application of AI, particularly generative AI, and in that stage one, stage two, the identifying prospects marketing outreach, the folks at financial planning recently had innovation awards. You announced finalists, and I think one of the finalists that you folks had mentioned was creating emails for advisors as they reach out to prospective clients. Could you talk about that and what was going on with that technology?

Rachel Witkowski (28:01):

Yeah, we had a lot of great innovators and applicants, one of the finalists, RBC wealth management, which actually got double recognitions for their marketing and client growth, but they have, one of them is the RBCs campaign central. That's like a self-service portal where advisors can sort of craft personalized messages and then send them out in automation and with reminders. So like a birthday or a holiday or a market event can sort of be sent out automatically written through some large language modeling in there. And then I was going to mention too, Orion compare that. A lot of people know Orion too, but they were also recognized as one of our finalists for having sort of a comparison, a portfolio comparison function that partly uses ai. And so there's a lot of, even with the vendors that we're talking about, like Orion, there's a lot of new creative development, so you might not have to have this fat tech stack of different tools going back to the tech stack pain point.

Michael Moeser (29:08):

Definitely, definitely. Well, I guess as we close up, any final thoughts for the audience in terms of generative ai, what you may be covering, what you're looking for?

Rachel Witkowski (29:18):

I did, and I've said this too in a podcast once, but when you're talking about the great wealth transfer, everybody wants to bring it up. And then I always think about a year ago, I was just sitting at a Marriott restaurant at a conference, and

(29:35):

I saw, and I'll be really quick, I have one minute. So I saw the bartender was making bets on an app for the horse race on tv. He wasn't serving anymore. He's distracted. And so I was like, what's going on? And he's like, oh, I've got this horse I'm betting on. And then somehow in that conversation I started talking about crypto and these other investments, and I kid you not every server, every bartender, every person behind that bar opened their phones and they were on some kind of investment app and none of them had an advisor. And so I just feel like they are out there and they're in applications and they know how to invest very fast, and it might not be the best investment, but there has to be a better way that advisors can reach that market. They know how to get things fast, but they don't know if it's right or the best choice for their life. So whatever it takes to build that trust, I think is so critical in this next generation. You could probably walk to a restaurant and ask people, they're out there and they're investing. And so part of that too is going past the high net worth, desired target.

Michael Moeser (30:40):

Yeah, the larger masses.

Rachel Witkowski (30:43):

Yeah.

Michael Moeser (30:44):

Super. Well, thank you Rachel. Thank you everyone for your attention today. And again, this presentation is going to be available to you through the conference team, so thank you.