Alison Dooher: Why Data Is the Engine Behind RIAs That Scale

Building the technology backbone that powers thousands of advisory firms and helps them scale with confidence is one of the biggest undertakings in our industry. Today's guest sits right at the center of that transformation. Hi everybody, I'm business coach Steve Sandusky for Barron's Advisor, The Way Forward Podcast. My guest today is Allison Dewar. Allison is Managing Director of Digital Advisor Solutions at Charles Schwab. In today's conversation, Allison shares how advisor technology has evolved from the early days of trading automation to today's AI-powered platforms. We also talk about where firms get stuck in their technology journey, the risks of tech debt and data fragmentation, and how to think strategically about building a modern integrated tech stack. Allison also explains why thinking of data as the base layer of technology not software, is the true foundation of a scalable advisory business. And she offers a leadership perspective on managing constant change while drawing on her experience guiding Schwab through its massive TD Ameritrade integration. With that, here's my conversation with Allison Dewar. You have been with Schwab since 1999. You've been in the technology area, I think, for probably the bulk of that. So, I'd love to hear if there's a through line going back to 1999 to 2025 in terms of the evolution of the technology and how that has helped advisors and advisory firms deliver better service to clients, but also be more productive and effective in the back office. Is there anything consistent through that period of time?

Yeah, I would say, so when I started in '99, I actually started in trading. And so much, I feel like, of the investment in technology at the time in this industry was in the trading space. And that emerged very quickly. And what became clear is that standard operations really needed to catch up. And I would say around 10 years ago, the advancement in capabilities to automate back office transactions is really what unlocked an incredible amount of efficiency. It opens up the turnaround time for client activities or client events. So think about opening an account. Prior to that, where you were having a conversation with your client, they may open an account a week later, you'd tell them their account number. That now happens in the same conversation, and advisors can fast forward through some of the operational aspects of the conversation and directly into the value-add part of the conversation, which is where we know RIAs really shine. And it allows them to really focus on the wealth management aspects that they will bring to clients, help them deliver on their life goals.

So I started in this industry in 1993, so more than 30 years ago. And for the vast majority of that time, I hear people say, oh, this, the speed of change, it's faster today than it's ever been. And technology is moving so fast. And if you don't change, you're gonna fall behind. And I agree with all that stuff, but I'd love to get your perspective. And let's use robo-advisors as an example. Okay, so we go back to the mid-2010s, 15, 20 years ago, robo-advisors were the big thing. It's like we're really going to take advantage of the internet and, and digital onboarding, and this was going to be the next big thing. So do you think that the hype around robo-advisors and digital onboarding from back then— has the actual reality lived up to that hype?

Well, fun fact, I was part of the team that actually built Schwab Intelligent Portfolios at Schwab. Yeah.

So you'll have a good answer to this.

I do have some perspective on this. I, for the RIA industry, I think that original fear was thinking that internet technology, a robo-advisor, would replace potentially certain aspects of an RIA's business, or if not, compete for their client base. We never believed that would play out. We viewed that the technology wouldn't enable scale in an RIA's practice, which I actually believe is what played out, just not in the way that folks really thought. So while your traditional out-of-the-box robo-advisors serve a place in certain parts of the retail client base, for advisers, what really has paid off are the investments in technology to speed up things like onboarding, and then the investments on the wealth tech side to be able to create portfolios at scale. And marrying those two together has been a trend that I believe will increase in emphasis. And tying those two together, they're just not packaged as a robo. They are two kind of distinct parts of and potentially different parts of your tech.

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Stack, but they're there to create the same holistic experience.

Let's jump into AI. We had all the hype around robo-advisors. Now we've got all the hype around AI. Tell me how you're thinking about AI. Is this the next greatest thing since sliced bread? Is this going to be the biggest thing we've ever seen? Is this going to change everything? How is this going to impact the day-to-day life of an advisor and an advisory firm over, let's say, the next 3 years?

Yeah, I will say I do think the hype around AI is real. There seems to be no argument that the pace of change— I always point back to 12 months ago, this was new for advisors. It went from new to norm in an unbelievable fashion. The way that we have been thinking about AI at Schwab and how we can serve advisors better, first and foremost, we're really investing in how we can harness knowledge better. And deliver it back when questions are asked, be able to say something very relevant, nuanced to the specific situation, and provide information faster at the fingertips. But I think that's really scratching the surface. Advisors now are integrating tools into their practice very regularly. There's not many advisors I know today who aren't using AI in some fashion in order to enable and support their client engagements. Take the note-takers as an example, and they are exceptional tools for saving a tremendous amount of time in either preparing for a meeting or recapping a meeting, figuring out what the next steps are, and then acting on those next steps. Now, what we also believe at Schwab is that AI is there to augment advisors, not replace advisors. And so that human-in-the-loop aspect and some level of governance around how it's being used will be incredibly important in terms of how successful it becomes versus potentially damaging or risky.

Another thing we've talked a lot about in this industry is how do we scale our practice? And related to that, there had been talk for a long time about how, well, we think the average fee that advisors charge is going to go down because we got competition, we got technology, we got this, we got that. But the data doesn't really show that. It shows that the average fees that advisors charge have been fairly consistent for years. Now, maybe you're seeing something different. You're shaking your head.

No, I don't think we're seeing something different, but my observation is that advisors are charging the same fee and doing more.

Exactly, which was my point. And I wanted to relate that to technology in that, again, you started in '99, I started in '93. Think about the work that an advisor did for their clients back in those days is a fraction of what most of them do today. Back then it was like, in my day, it was more commission. I sell you a product and then I don't really talk to you again until I sell you another product kind of thing. And then it went to asset allocation, and then we're going to buy a slew of mutual funds, and then it went to financial planning, and now it's life planning, and then who knows what the next evolution is going to be. So yeah, to your point, we're doing more for the same amount. So my question is, as it relates to technology, is it going to be the same thing as it is with pricing in that, yes, we've got all this gee whiz technology and we can better serve our clients, but it's not necessarily enabling us to work with more clients because now we're doing more for each client, but we've got technology that's making it easier for us to do that. Because as I look at the data, I'm not sure that the constraint for an advisor to work with more clients— I don't think it's the technology, it's just their time. It's like, how many hours a day do I want to sit face to face with the client. It's like no technology is going to change that. So am I missing something there?

No, I think you're on to something there. I do think, though, that working in this field, I feel like the line that we're really trying to walk is actually hitting that sweet spot where we are driving so much efficiency into certain simple tasks that used to take time And at least by taking that out, there's a choice, right? You could keep your list of services the same and do more clients, or you could expand your service set with the same amount of clients potentially, or really expand the service set for even less clients. Right. But allowing that choice, I think, is what technology is enabling.

Yeah, I totally agree with that as well. And clearly there are areas where the technology is streamlining things. A simple thing like oftentimes an advisor will have a second person sit in on the meeting to take notes. And that's oftentimes a way to train someone new, sit in on the meeting, see how I do it, take notes. We'll talk about it afterwards. We'll write a summary email and send it out. Well, now, of course, we've got AI note-takers that can do that and we can have an AI that can read the transcript and spit out the action items and the to-dos and the summary email. And then I just have to look at it and improve it, tweak a couple of words and boom, send it off. So yeah, there's definitely efficiency in that. But another topic that might lead to a problem, how do we train new people if AI is doing some of the entry-level work that we used to have new people do?

My husband and I actually have this conversation all the time in that while the opportunity with the technology is there, I will be very honest, it is worrisome to me, or I spend some time worrying about it in terms of when we hear things like we don't need roles in junior positions. And I think back about how I matured as a professional and where I really honed critical thinking, where I learned what to worry about, what not to worry about. Some of that really happened in those early years. And what I think as a society in any industry we need to crack is how do you not lose those early years? And still create that level, because if we're not building critical thinkers, we won't have the next generation. A, we won't be able to pass on existing successful businesses and have them remain successful, but we also won't see the level of innovation emerge the way that we have in the last 20 years.

No, I agree with that. And I think that's a huge issue, a huge challenge, and perhaps a huge opportunity as well. I've always said that I think the people who are going to be most effective with AI are the ones who are already experts in that area of their work. So if you're an outstanding financial advisor, if you understand the technicalities of sophisticated financial planning and wealth management and tax law and estate planning, if you know all that stuff, you're the one who's going to be able to take best advantage of AI because you'll know what prompts to ask AI. You'll know when AI is hallucinating back to you. You'll know when AI comes up with an idea that is a novel idea, like, wow, I'd never thought of that before. That's interesting. Let's explore that a little bit further. Maybe that's a strategy that we could work with this client that no one's ever done before.

So completely agree. And we can't lose the younger generation being given that opportunity to learn, to have those same advantages.

Right. And I think it is important that we still have deep training. And I know Schwab is very much into that. There's over 100 students here at IMPACT this year really training that next generation of advisors. So I don't think there's any, any shortcuts to do that training.

It's actually been one of the better use cases of AI, I feel like, in Schwab that we've been doing for the past couple of years is our ability to listen to client phone calls, aggregate that data, really identify trends of what client needs are in particular topics, and then we tailor our training for our service professionals around what we've learned from those calls. So it's actually allowing us to fine-tune specialties within our service professional base in a better way than we could before. So rather than focusing on generalities, we get to focus on specifics and make people experts.

Yeah, I love that. And one of the things I've suggested to advisors is when you're hiring people, record the conversation. So maybe the initial is a Zoom call or something, or you're in person, record the conversation, put it in AI, and then start prompting AI and say, I want you to play the role of an expert human resources professional. I want you to analyze this interview. And I want you to give me feedback on how effective was I as an interviewer. What could I have done better? What questions should I have asked? Were there one or more situations where they responded and I should have gone deeper with a follow-up question? You could even ask it things like, were there situations where when I asked a question, could you sense some apprehension on the part of the candidate? Was there an awkward pause? Is there anything that you can interpret from their feedback that is a red flag that I should further follow up on? To me, it's like, well, there's a great use case for AI, but it's also a great training tool to help me be a better interviewer.

I just got an early look at a new technology by a firm in this space who really started as one of the AI note-taker firms is really evolving how they can use that unstructured data and create insights from it. And one of the neatest things I saw was marrying critical thinking, an entrepreneur's vision for their business, what they feel like their value proposition is, and defining it for the model. And then live listen to client meetings and understand whether or not the advisor in the practice is actually hitting on those points that have shown the most success in terms of client relationships. And I think over time, it could be real time. You could prompt somebody in the moment and say, hey, they brought this up, remember to circle back on tax planning, whatever the item might be. But in totality, now RIAs have the ability to then look at their practice and understand how successful their client engagements are in aggregate based off of criteria they've defined.

Yeah. And to that point, I had a conversation recently with Matt Reiner and he was saying something very similar and he basically said, we'll probably get to the point where we're wearing glasses and in real time you've got the computer behind the glasses analyzing everything and it's whispering in your ear, Well, this is the next question you should ask or be aware of this thing. And of course that gets a little creepy, but I wouldn't be surprised if that's coming.

Matt's so great. He's been on the forefront of thinking about technology and how it can be best used in RA practices for a while.

So yeah, let's talk about bottlenecks. So again, you're at the forefront of all of this. You see a lot of advisor practices when it comes to technology. Where are the bottlenecks for them to be more effective? Effective in using technology to either A, deliver a better client experience, or B, more effective and productive and efficient in their back office?

Yeah, the truth is not everything is digital and not everything is automated yet. And that should it be though? That's still a journey.

Or should some stuff still be humanized?

I suppose I'm a little biased given where I spend my days. I tend to believe that the non-digital should remain the interpersonal interaction. But so much of what facilitates the relationship are putting pretty transactional things in place. So whether it's opening an account or updating an address or setting up for future distributions, right? Along those lines, at the core of that, they are transactions. I also actually believe that while at some point there is a segment of clients who might have enjoyed, for an address update, some physical piece of paper to be passed, or for an engagement that the future client base will not expect. That's how they're spending their time with their advisors.

Everything was digital for that generation.

Everybody who had the telephone on the wall in their kitchen with a really long curly cord Next generation. And the rotary dial doesn't even know what that is.

It's an antique at the vintage store. So as you look at the firms that are stuck with the bottleneck versus the firms that have broken through the bottleneck and have been effective at implementing their technology, what's the difference between those firms? Is it leadership? Is it mindset? Is it They just took the time to figure things out? Something else?

Yeah, it's a good question because there's actually, to circle back, there's a couple bottlenecks that I tend to see. And one is I actually think firms would do more digitally if it was available. So to some degree, that's on us as the providers in the space to at least make sure that option is available. The second bottleneck that I've seen is that, and I don't realistically envision for most firms that a kind of single tech stack is their long-term driver of success. And so the second bottleneck is what we're doing to help solve for the integration game. The promise of integration has been out there for 10 years.

20 or 30 years.

20 or 30 years, you're right. Yeah. And while I think it's gotten tremendously better. I think there's more to do. So the firms that I've found that are successful in this space, first back to the first bottleneck, I think they're really clear about where their value is with their client relationship and those transactional items. The culture is just built around the fact that that's not their value. So for their entire staff, your value's not filling out a form. Your value is creating a real bond with the client. For the integration piece, advisors who have solved that the best understand that at the base layer it is all data, and from the get-go they have embraced the need to have data. I think where AI comes into play really nicely for advisors that are just starting maybe down that path of organizing their own data, is it just solves for some of the, I think, resource challenges and effort it took to really structure data effectively so that it could actually be useful. And now AI operates much more efficiently or can solve for some efficiencies when looking at unstructured data. I think in the integration game, advisors who really understand that it's data at the core tend to solve that faster.

A phrase you said there I think is critically important. You said the base layer is data, which really leads into another question I want to ask you, which is this idea that one of the frustrations with technology is it's always evolving. I can never put a stake in the ground and say, boom, I've got it. I got my tech stack. This is good for the next 10 years. It's like, no, this is good till tomorrow. And then some other new shiny object's going to come along. I think about like CRM systems. Just since you started in 1999, like how CRM systems have evolved and we, we have to keep moving up and eventually we're on Salesforce or whatever. So how should firms think about evolving their tech stack over time? And I think this idea of data is the base layer, I'm thinking is a key. 'Cause that's the thing that if I have my data, if I have it structured as best I can, and if I have unstructured data that maybe AI can parse that, or maybe I can turn that into structured data, but if I always have the data, then whatever the new technology is, I can just have it pull from that database layer. But it starts with the data. So what advice do you have for firms when it comes to I can't get the shiniest new object every time it comes along. Strategically, how do I think about when is it time to evolve my tech stack because there is a much better technology, but I don't want to do it too fast because if I do it too fast, well, this company could be out of business next year, or I'm constantly changing because there's always something new coming along.

Yeah, I think, I think as I look back, one of the market drivers actually for advisors to really want to invest in their own data technology was the fact that technology was changing so fast and that without having technology in-house, so to speak, it was harder and harder to move from tech stack to tech stack. You had to rely on your previous provider to provide the data to your new provider. When you own it, you get to control that a little bit more, if not entirely. And that piece alone can actually ease any sort of technology tool transition immensely. In terms of kind of pace of change, it's funny, we talk about this a little bit differently within my team in that already this year we've done over 250 technology releases on our own platforms for RIAs. That's a lot of change.

Well, how many of those changes are visible to the end user, the advisory firm user, that they're like, oh, we got to change a procedure because Schwab just updated this thing?

The vast majority have some visible component to them. Much fewer have a big impact and a real kind of process change versus minor tweaks and improvements. But either which way, it is change, and we tend to be really mindful about how much change we're introducing into the ecosystem at any given time. So we talk about balancing. Do we want to introduce a lot of change, for example, in our onboarding workflows at the same time we're making absolute massive change in our cashiering workflows? That tends to hit the same the same employees within an RIA firm. So now you're really overwhelming a client support group with a lot of change at once, and they feel the pain. They feel that they're not serving their clients well. So we tend to be a little bit mindful around how do we stagger and cadence that. So while doing a wholesale tech stack at once probably used to be the norm, because again You were giving up your data at one place and you were moving it to another place, and it didn't make a lot of sense to keep them both around. Now today, when you own the data in-house, you actually get the choice to do discrete changes within the tech stack that allows you to reduce that change friction.

So when we talk about data as the base layer, so you're a custodian, you have all this data, so From your standpoint, do you own that data of the client? Does the advisor own the data? Is it joint ownership? If the advisor says, I want to download every piece of data about my clients that resides on Schwab's platform and give it to me in a file because I'm going to create my own data lake or whatever you want to call it, do you say, absolutely, we'll do that?

Yeah, so client's permission sharing of their data with advisors upon account open and upon their relationship establishment. So to be clear, it's the client's data. Okay. Okay. And they permission either Schwab by nature of us being their custodian or their advisor by nature of their relationship with their advisor to have said data. We distribute over 2 million files a day of data to advisors or other third-party vendors that advisors are using to ingest that data and be able to pipe them into the systems that are then allowing them to serve their clients more effectively. So think portfolio rebalancing tools and of that nature. But at the end of the day, it's the client's data. It's the client's data. It's, it's all about having the right permissions.

Right. Okay. I want to go back to change management for a moment because I think that's such a big thing. You talked a little bit about how you think about how much change you want the advisory firm to incur, so you're thoughtful of, okay, we got to be mindful of that. Tell me a little bit more about how you as a leader think about change within your department. Again, you've been here since '99, you're executive here at the firm, you've gone through a lot of change. So how do you think about that? How do you ensure that your team can deal with the change over time? Because I think what you do is certainly going to apply to what advisory firms do as they think about dealing with change.

Yeah, we like to joke, wait 6 months, there'll be another org change. Yeah. But I think in terms of preparing folks, one of the key aspects— so nobody asks me why I joined Schwab. 26 years ago.

Why did you join Schwab 26 years ago?

People ask me why I've stayed because it's part of the answer relative to change management is that the culture of Schwab. First of all, I get to work with really fabulous people at this company, some of the smartest and maybe while not important to many people, some of the funniest people also in this industry, which just makes going going to work a little bit easier. But because of that relationship culture within Schwab, because of our commitment to clients in that I have never been challenged or felt like I was sitting on the opposite side of a decision from the company. Things go wrong sometimes. Every time I've been part of something like that at Schwab, we've always done the right thing. And that holds true actually with employees too. That's, that's my lived experience at the company. And I think when you have that type of base layer, then any sort of change becomes easier to deal with because you're still all rallied around the same goal.

So take the TD Ameritrade acquisition, merger, integration. Obviously, that was a huge deal. Think back at that point in time, what did you learn through that about change management and how to deal with such a big project like that?

Yeah, first of all, it's so fun to look back at because while I have colleagues now that I met 6 years ago, I feel like I've known them for 20-plus years. That's how much I feel like we've grown together in those 6 years. I think given an event like that integration, largest historical of the nature, you have to make decisions with twofold, the clients in mind, and by clients in this case we're talking advisors in mind and employees in mind. And some of that was around trying to trying to reduce collective churn across the entire client base. We, we needed to start looking at the client bases in totality and try to chart a path forward that mitigated some churn, but also put us on a path that we really felt like would actually springboard growth once we landed the ship. And it was amazing to see how teams could really rally around that. On the employee side, I suppose like any two companies coming together, there were differences in culture, but there were a lot of similarities in culture too. And I think we embraced both and learned a lot from each other. And that part of that 4-year journey before really landing the ship was also some of the most fun years I've had. And I think if you had asked me during the time, would I have used the word fun?

Maybe not. It's type 2 fun. But in hindsight, it was really hard while it was happening. But as I look back on it, it's like, oh my goodness, that was just epic.

Yes, epic's a great word for it.

Yeah. Yeah, and this could be a whole nother podcast, but since you touched on it, I think I'll bring it up. This idea of melding cultures. So a lot of folks listening to this are acquiring other firms that have cultures. Now, of course, there's a self-selection there. Like if I'm going to acquire this firm, we want to make sure there's a meeting of the minds and we want to make sure that there's a cultural fit. But I think I heard you say that TD Ameritrade, they had a culture. Schwab, of course, has a culture. Some of those pieces were similar, some of them were different. And I think I heard you say that you didn't force TD to embrace the complete Schwab culture. It's like, let's take some of the best of the TD culture with the best of the Schwab culture and let's come up with something that's really a melding of the two as opposed to one gets subsumed by the other. Is that fair to say, or?

And thankfully that applied across just, I think, how we emerged as a team. And as well, it was really a driving factor in our decisions around technology. And we, the phrase at the time was best of both. We want the best of both to survive. And I absolutely think that that has made Schwab collectively a stronger company into the future because it wasn't a scenario where we used to refer to blue and green for obvious reasons, that it was just blue. I think at some point we like to refer to ourselves as teal because we really meant that it was a merging of the teams together to become one team.

Excellent. Okay. So I'm going to anoint you with magical powers. I'm giving you a wand, a magic wand. And you're going to wave that magic wand, and with that wave, you're going to be able to make one major technological change, enhancement, improvement, implementation, execution. It could be within Schwab, it could be in advisory firms' practices. What is the thing that you're going to do when you wave that magic wand?

This is ostensibly the hardest question I think I've been asked. I think in this moment in time, if I were able to solve for all standard operational friction, if we were able to implement automation, some machine learning at mass scale and within a really short period of time, I think the future of what we then get to look at becomes incredibly exciting and the opportunities that we could materialize by nature of that become much faster to fruition. So I feel like I didn't say anything innovative there, but it's really based around I feel like there's a, there's a gap that we're still striving to close and there is a long tail of operational tasks that could use some level of digitization or, or automation. And I think solving for that would just open up the pathway to really be thinking and pushing the envelope in other places.

And have you asked AI what its advice is in trying to solve that?

I have not, but I will be.

You should be.

This afternoon.

There you go. All right. Okay, so final thing here. I'm going to start a sentence and I want you to finish it. So the beginning of the sentence is, the future of advice will belong to firms that blank.

Continue to put the client at the center of the relationship.

Excellent. All right, Allison, appreciate you being on the show. If folks want to stay in touch with you or learn more about what you and your team are doing, what's the best way?

Oh, best way is to check out advisorservices.schwab.com, and there's plenty of information around how our platform's progressing. And for, for clients of Schwab, we publish our roadmaps internally on our website as well. And there's plenty of other education resources available on our Schwab Advisor Center website as well.

All right. That's all for today. Make sure you like and share this podcast through your favorite social platforms. And for more great podcasts, visit us at barons.com/podcast. Take care and be safe.

This podcast was brought to you by Wells Fargo Advisors. Looking for a firm your clients can't outgrow? Wells Fargo Advisors offers financial advisors full balance sheet solutions with wealth planning, investment products, banking, and lending that meet the needs of affluent to ultra-high net worth clients. Build your practice your way and on your schedule with independent and employee model options designed to meet your needs today and tomorrow. Learn more at joinwfadvisors.com.