Beyond the Hype: How AI Makes a Difference in Wealth Management with Rob Pettman

Speaker A: Foreign.

Speaker B: You are listening to Wealth Tech on Deck, a podcast about the future of wealth management technology, brought to you by sei. Here's your host, Jack Sherry.

Speaker A: Hello, everyone. Welcome to this week's edition of Wealth Tech on Deck, where we explore the trends, technologies and ideas shaping the future of wealth management. For our conversation today, we're going to talk about what everyone is talking about. Artificial intelligence, AI. And I can think of no one better than Rob Petman, President and Chief Revenue Officer at tiffin, to cut through the baloney and get to what really matters. Tiffin is one of the most active firms at the intersection of AI and wealth management, with a unique model spanning asset management, distribution and advisor technology. We're going to examine what is real versus the hype, what winners are doing differently. Rob has a front row seat to how AI is actually being deployed across our industry. What's working, what's not, and where we're headed. Rob has been on Wealth Deck on Deck before and it's great to have him back. Rob, welcome back.

Speaker C: Thanks, Jack. Pleasure to be here. And I gotta say, I had a hard time with AI because it used to stand for alternative investments. And uh, now what do we say? Just say alt. Don't know.

Speaker A: I've been of late, I found myself talking about alternatives a lot. And when I wrote down AI. Oh yeah, what does this stand for? I had to think for a minute because I, you know, it's just AI at this point. But I'm with you. So let's start at a high level. Let's. Let's get into this AI artificial intelligence version thing. There's a tremendous amount of conversation about AI and wealth management right now. Arguably more noise than clarity. I'd love to have you comment on that. From where you sit at tiffin, how would you characterize the current state of AI adoption in our industry? Sure.

Speaker C: You know, I think we've gone through this progression. There was initial curiosity. I think we're now moving from experimentation to production. And you're just seeing different shades of that production and what it looks like, Risk, advanced type spectrum. So you see a lot of major firms with the addition of Microsoft Copilot, and we'll put that in sort of low risk and some more basic implementations.

Speaker A: Sure.

Speaker C: And then towards the frontier, you'll see REAs using agents to rewire the workflows of their internal operations. And that's where a lot of the future is going for AI and there's a sort of big space in between.

Speaker A: Right. Actually, uh, as I mentioned before, we got on air here. I'm now using Copilot to help me construct the questions for the podcast. And I have to edit a fair amount because it doesn't fully get it, but it gets it enough to ask questions and it looks at what you've been talking about and revealing in the press and so on. So I actually found it Copilot to be my friend. But also it needs a little bit more than just regurgitating whatever might pick up online. But let's get practical. There's a big gap between AI as a concept and AI that actually drives measurable outcomes. That's a lot of what you just said. Where are you seeing AI work today? Where is it really delivering value?

Speaker C: Sure. And I think that there's three big themes here that you can look at. First is we'll just call it the theme of productivity. And a lot of firms are using AI right now, financial advisors, home offices, when it comes to note taking, meeting prep as an example, content creation, that is saving time and it is creating levels of productivity. Definitely harder to measure the commercial impact of what that productivity actually results in.

Speaker A: Yeah.

Speaker C: Right. But it is having an impact as it relates to productivity.

Speaker A: Yeah.

Speaker C: I do think though, as you start looking at the next phase of these things, when you have these meeting note takers that are getting more information and being able to put it into CRMs more effectively, and you're able to then connect in a much better way. Just given how the technology's advanced financial planning system, the portfolio management system, the CRM all together, you actually have the nucleus of a brain which fully understands all aspects of a client.

Speaker A: Yep.

Speaker C: I can ask a question and it can intersect all of my communications, all of the planning that we've done, and the current status of the portfolio, that's how you get the real outcome. Right. And there's the firms that are either there or progressing towards that end. So that would be sort of productivity. I think your other one. So the 2 and 3 growth and distribution, we sit on a ton of data. Firms are effectively leveraging that data just to get signals on how they grow. And whether you are a wealth management firm thinking about wallet share capture, or how you might think about new prospects differently, or an asset manager on which financial advisors you should choose to serve first. Those technologies are working well and actually generating real commercial outcomes that firms have results that they can reference in their efforts. And I think the last one is output into the line of, we'll call it workflow operations. I mentioned this earlier as this being the frontier and there are a host of firms that are actually really making progress here and demonstrating results. And think about it, if you're in uh, a wealth management firm, I mean we're helping firms right now as it relates to financial advisor transitions. There's a ton of inorganic growth. If there's M and A that's occurring or just regular recruiting that's happening and moving from one place to another has always been a struggle. So to be able to compress that timeline and also improve the level of accuracy and really challenge and tackle that data, uh, onboarding issue that exists is helping to create a better experience and also a better commercial outcome because firms sort of accelerate the time to billing and get the advisor in a better place to get on their platform. But the other areas of large opportunity are supervision operations In a wealth firm. As you can imagine, if you're an asset manager, growing area of opportunity is the OCIO function because it's huge demand for custom models from financial advisors. But there's a bottleneck in the number of the OCIO to financial advisor coverage ratio. And so there's really interesting solutions on how you expand that we've been helping firms with. And then on the insurance side, thematically reducing the cost to serve for these policies from service to operations to sort of the basic sort of course of business is a huge thing for them to solve as they try to make their products more relevant and competitive in the modern sort of wealth management platforms. And we're seeing a ton of efforts happening there as well.

Speaker A: So not sure how to ask this question. Maybe you can help me with your answer. So what I'm hearing is, and what I'm uh, personally experiencing is I use it on a daily basis. It's streamlining what I do. It frankly accelerates what I'm intending to do. And in my case, where I'm a lot about the narrative, the story about positioning, that kind of thing, I find it enormously effective because it can go out and find out what I've said before, what has been said before in the space that we occupy. It helps me tell a better story. Uh, as an example and what I'm hearing you say now applies in other realms within the wealth management sphere with streamlining the operations, streamlining the connection between clients and portfolios. Talk about that streamlining. And specifically how does Tiffin work with people on. I'm assuming this is a big part of yours, a lot of consulting and counseling around how do you help people be more effective and efficient?

Speaker C: Yeah, I mean I'm probably like a broken record of when it comes to just starting with the actual commercial outcome that you're intending to solve for first. There's a lot of places that want to start just thinking about a data problem without actually focusing on the real outcome that they want to achieve right out of the gate.

Speaker A: Expand on that, Rob, if you would. I know you've said it before, but I think my sense is people might step over that a little bit. I'm, um, sure you guys don't allow that too much. No.

Speaker C: Well, I mean, I think a frequent narrative across most enterprises is saying, hey, we'd love to do AI, but we're just not there with our data yet. We have this massive data initiative and we can't do anything until we've completed that. And modern technology has changed in how you actually solve for a host of these data issues. And again, generically solving for data doesn't. Still, without a commercial outcome with intent there, it's not going to help you progress. So that's why it really does pay to focus on specifically the problem that you're solving, the outcome that you want to see, and then be able to engineer around that and then you can build out from there. I think there's just a lot of perspectives of the past of how software and how data has been used before that are no longer relevant, but people are still carrying forward into their current practices.

Speaker A: Gotcha. So let's talk about the advisor level and how you support that. Ultimately, that's at least where you and I sit. That's a big part of what we're trying to do. So advisors are inundated with tools and now AI is being layered in on top of that, around it, through it. However you might characterize that, uh, what's actually resonating with advisors versus what's being ignored.

Speaker C: Yeah, I think the baseline needs of financial advisors really haven't changed. They just want to do right by their clients. Forget the tools. That's the sort of end objective. So if there's a way in which they can do provide a better service for them, then they are interested. Not every advisor wants to grow. So if you give them the capacity to be able to serve a thousand clients and they have 300, they still may not want to get to a thousand, they may want to stay at 300. Right. The enterprises want them to grow. Right. And that's a different set of objectives. Depending upon the advisor, they're going to prioritize those features differently. I talked earlier about that unification aspect of being able to unify these systems together and Provide this sort of customer Service representative type view 360 degree way for an end investor. That really resonates because the amount of time that it takes for them to get this information from a CSR or even with an enterprise and how they allocate to the number of CSRs per financial advisor, that's needed. It is painstaking. And there are more efficient ways for advisors to get what they need to be able to deliver a better experience to their clients with that lens of more personalization.

Speaker A: So let me dig in on this one because I've been talking to a bunch of people around the industry on this very topic. Certainly firms want to grow, especially P backed firms. That's why they bought them to grow. And the this whole issue. So many of our podcasts are around organic growth, not just through acquisition or what have you, markets, et cetera. But if the intent of the firm is to grow, they would tell you they're struggling with that most if they're being honest. And one of the big issues is that advisors don't seem to want to grow. In other words, they got a nice gig going, they're making money. It's coming up on golf season, least up in the northeast, and they want to be playing golf now. They ostensibly through their clients and probably they do play golf off with a few, but that's really interesting. So how do you work that? Because I'm sure you're being brought into on organic growth opportunities and you have a reluctant, I'll call it reluctant audience in terms of that growth dynamic.

Speaker C: You do. But I think that there's a missing part in the equation. Uh, it's easy for somebody to say I don't really want to grow if you don't really know what growth looks and feels like with a different set of capabilities.

Speaker A: Mhm.

Speaker C: And this is why a lot of people miss the change management aspect of what's needed for AI in general. Because change management is massive within this. And we're called in on two different sides. We're called in for firms that are looking for a systematic process to grow and will help deliver intelligence. And if I give you a story on change management and the importance of it, we work with cetera and they're running a pilot and they happen to have a massive focus on change management and working through process with advisors.

Speaker A: Rob, if you would just define change management, what do you m mean when you say that or what does satera mean?

Speaker C: Yeah, in this case, we're delivering signals to financial advisors that uh, tell them that they may have A greater wallet share opportunity with existing clients or helping them understand that there's been shifts in life events within their client base and prompting them to ask a different question. And what happens typically is people may say, well, I know everything about my clients. There's no way that you're telling me something that's there. I don't believe it. It's not true. And part of the change management is to say, hey, look, this is just part of a process and it's a cue just to ask a different question. And if you ask a different question, you might be surprised in the results. And they have been really focused on this to the point where the advisors in their pilot grew three times more than advisors outside of the pilot.

Speaker A: Mhm.

Speaker C: So you take that case and then we work with a different firm with the same set of conditions, but without the focus on this change management. And the difference in results is reacts. They didn't get the same amount of pull through that they were searching for. Interesting, right? Because they needed that other component to play along with it and they're catching up and doing those things. But that's why the change management is really important versus just pushing a, uh, tool out there and expecting it to work instantaneously when we're asking people to change the way they've historically done things before.

Speaker A: Rob, you guys are working with a broad cross section of firms. Asset managers, distributors, wealth platforms. What are the most successful firms doing differently around AI?

Speaker C: Phil said, yeah, I think it's not an obvious one actually, but one of the things I see is that the firms that are most successful have a very strong initiative and leadership presence coming from the C suite. And it's not just about putting a flag in the ground and saying we are going to do AI. It's actually them leaning in and pushing through some of the structural issues within their organization that may prevent AI from actually being successful.

Speaker A: Talk about structural issues. Define that if you would.

Speaker C: So let's get a couple of examples, right? Because oftentimes the business side of firms has historically deferred technology decisions to technology.

Speaker A: Right.

Speaker C: And when you view AI as a tool versus a change in your operating model, then you're going to go do this. And the issue that happens is that technology doesn't fully understand the business. If we're having a conversation about workflows and truly restructuring our operating model, where we're going to leverage agents inside of our ecosystem to do operational tasks and elevate the people that we have to work on more complex issues, technology doesn't really know all of those processes. And the business hasn't been accustomed to leaning in in that way to help actually drive that type of outcome with technology. So it really does have to be this sort of culture around business led technology enabled versus business deferred through technology. And that's what people are used to doing. That could be a part of an organizational shift that may have to occur within the firm. It all really depends upon the cultural aspect of things and how things interoperate together. But that has been getting in the way of a lot of the success of pilots that have just really never made it to production. And the firms that are winning have a C suite that are actually really m pushing through some of these structural barriers to make sure that both sides are collaborating in a way where they are focused on the end outcome that they're trying to achieve. And there is that collaboration with that focus to realize those results.

Speaker A: Yep. And maybe draw this distinction at a finer level. I keep hearing about AI at the operating level and then I hear about AI uh, as a tool. So maybe make that distinction because like we have Copilot at our shop. I use it all the time. It's a great tool. I use it in a way that I feel more productive and effective as a result of using it. So it helps in that regard. And I know the firm which is really at the C suite levels, the CEO in particular, they're really driving toward having it at the operating level. And how have it become part of our thinking? My observation as I try to understand this stuff and try to follow it, that seems to be the right course. That seems to be where one is effective. Break that down if you would sort of talk about that distinction or that difference.

Speaker C: Sure. Well, I mean I think the headline of this is the real power of the maximum commercial impact you get is when cost savings meets growth meets scale and you put all of those three together. But to give a real life practical example of how an operating model has changed just in, even in our experiences when we work with firms on financial advisor transitions, they'll have internal operations specialists that are working through moving a uh, financial advisor's assets from one place to another.

Speaker A: And all the data involved in that. Right.

Speaker C: Correct. And their day to day doesn't look the same anymore. Their day to day used to be doing all of that work. Today that is receiving, looking at a dashboard and seeing all of the more complex and exception type related activity that they need to work on. And instead of working on just one office at a time, they're parallel processing Offices, so increasing the overall capacity that's needed and, and they're really working on the high value problems that actually need to be solved. That's a fundamental shift in how that team actually operates today.

Speaker A: Interesting. So Tiffin has uh, built a reputation around AI driven personalization, particularly around um, distribution. Think about personalization in the context of wealth management these days.

Speaker C: Well, I think that's what AI is all about in what it's able to drive and it can do it in a host of different ways. I think in the context of wealth management you really have the ability to deliver personalized portfolios. How we're helping asset managers with OCIO models for financial advisors to deliver to end investors. Because AI is so powerful and allows you to wrap your arms around such a significant amount of complex information and distill it down also into what are the things I need to focus on, what do I need to change?

Speaker A: Mhm.

Speaker C: Normally just take an inordinate amount of time without it. Um, the possibilities now of how you are able to truly dig deeper with an individual client and service it effectively versus what you were able to do before is change. That's that level of personalization that's out there. But plus also it's one thing just to be able to implement it. That's not all servicing. The other component of servicing is to be able to get the information as to what's changed, what's happening, what's the narrative inside of this and what needs to be the message to the client, uh, sort of relative to their plan and what have you. All of these things intersect where you have these larger capabilities for portfolio construction, implementation. But then that also has to be connected to the intelligence and layers that help you with the narrative and help to connect that to the client's overall personal goals.

Speaker A: So one of the things I know you're, I'm sure you're watching closely, we're seeing an explosion of AI, uh, point solutions. At the same time firms are trying to rationalize their tech stacks. How do you see the balance between point solutions and the broader platforms? How are those coming together or are they coming together?

Speaker C: This has always been like an accordion in this industry. It's always like eras where it's all point solutions and everything platforms and it sort of breaks out the point solutions and then platforms again. At Tiffin, uh, we took all of our point solutions, not all of them, but a lot of them, and then pushed them together for a platform. Tiffany I. That's where the market was pushing us. They were saying hey, I like These three different point solutions, how do they work together? Because I'd like for them, they all do great things and I want to piece them together to achieve this outcome. So that just happened so often enough that we really had no choice but to just push it all together and have a platform type view because that's where the market was driving us. So from the feedback we're getting, there is a strong demand for platforms. Not saying that point solutions are irrelevant in this, but I do think over time it's going to be probably more challenging for point solutions until maybe the accordion changes again, who knows?

Speaker A: Yeah, what's happening is, and I'm finding this personally, um, because we all put it in our own bailiwick, but I'm trying to have a conversation every day, multiple conversations around what this means, how this fits, where it goes and in the process of learning how it all works and comes together. The question I just asked you, I wouldn't have known to ask a month ago, but it's happening that quickly. But this whole idea of at the operating level versus at a point solution, both are going on. I think you're right. They will come together, are coming together and ultimately this is going to be an operating model, I would assume, but I'd love your thoughts.

Speaker C: I will say though that you can platform, but there's still going to have to be the need to be flexible. I think from our standpoint, if we are, ah, being in the market of delivering these workflow capabilities with agents, there are firms that have their own initiatives, their own tech teams and they may have their own agents doing things. And above that you have an orchestration layer, the command center of sending agents to collaborate and do different things. And so the question is, whose orchestration layer is it? Do you want us to be the orchestration layer? Are you the orchestration layer? And then as your role as a platform, you have to be flexible to say, hey, I can deliver this agency capability that can plug into your orchestration layer and be a complement to your business versus just trying to be an all or nothing type platform. I do think that you're going to have to be more flexible in this world and the technology allows you to do that. So there's really no rational reason why you wouldn't.

Speaker A: Yeah, I'm with you. Let's take a look forward. Over the next 12, 14, 24 months, what do you expect will change most meaningfully, um, in terms of how AI shows up in wealth management? I'd love to get your thoughts on that.

Speaker C: I think that a Lot of the drudgery in wealth management goes away. I mean, look, in my experience working at a large firm, the amount of manual processes that exist around administrating a very complex business, they're everywhere. And there's so much opportunity to go about streamlining those. And also in the spirit of just creating a better experience for everybody involved because it's just not adding a whole heck of a lot of value into the um. So I think that's one piece. I think overall, and this might be a little too sort of warm fuzzy if you will, but I do think that there's better wealth outcomes that come out of this. Individual investors, I think improving the ability for wealth firms to serve financial advisors, for financial advisors to serve end investors. There's a virtuous cycle there where I think that the end investor is better off with a stronger advice model that's leaning into them in a way that it never has before. That's the part that drives us. That's our mission in general. And that's a key part of the progression. I wouldn't say it's the change, I just think it's an evolution and progression of this business.

Speaker A: Love it. Quick lightning round to close out in a little bit. What's one AI use case every wealth firm should prioritize now?

Speaker C: Gosh, I don't know if I can give one, Jack. That's not fair.

Speaker A: Uh, well, yeah, I think, not to answer the question for you, but it does seem to me that it depends on the firm and what their strategy is.

Speaker C: It really does. I mean you've got to pick the commercial outcome that you're trying to solve for. Right. I mentioned that sort of trinity of things that you're looking for where growth meets cost, savings meet scale. If you can find one of those formulas, go for it. The low hanging fruit or theme that I see in wealth management is around operations, supervision and transitions. Yeah, those are the big three that people are targeting right now.

Speaker A: Very good. Biggest misconception about AI, uh, and wealth management.

Speaker C: I don't know if this is a misconception or not, Jack, but I might answer that a little bit differently.

Speaker A: Okay, go for it.

Speaker C: I think that the understanding of what is truly possible versus what a lot of people understand today. Right. So what's truly possible is here. I think that folks understand is here. And I think that actually impacts adoption more than anything else because you, uh, know, frankly, in talking to wealth executives and helping them understand what is truly achievable, once you understand those things, you actually think about it. In a very different way and your strategy differently. So the biggest misconception is actually around what's truly possible, if that makes sense.

Speaker A: Totally. I mean, my own personal experience around AI, which I also use in my outside of work, just on volunteer stuff I'm involved with boards and what have you is it just helps clarify my thinking in terms of organizing what's possible or the articulation of the issue at hand and what might be done about helps me think better, if that makes sense. Now, anytime I have any kind of issue I'm trying to grapple with, I, uh, use AI to help me think it through. I inevitably change whatever they tell me, but they raise things I wouldn't have thought of or I would have forgotten about or wouldn't have. Especially on complex issues where there's lots of different elements that need to be considered. But love your thoughts on that.

Speaker C: I think that's always going to be valuable. Right. And what's also interesting, by the way too, is the challenger model, uh, the multiple models challenge each other and you actually get a better outcome. So even you challenging the AI or challenging you on thinking other models can challenge each other to actually get a better outcome as well.

Speaker A: Yeah.

Speaker C: So I think of it that way too. But beyond the sort of supplement to how you think, just even how work is actually performed and created, the whole notion of computer use models, I don't think people have fully wrapped their head around. But once that understanding is there, I think people are going to get a lot more creative on how they're going to change that operating structure of their business.

Speaker A: So, Rob, uh, this has been a great conversation as always. You've been on a few times before. Always learned something in our conversations. So let's shift gears and talk about stuff that's not AI. As you know, we always like to wrap up with a more personal question and what our guests do outside of work for fun or relaxation. And I know you spend your days thinking about AI and wealth, operating systems and transitions and all the rest. Tell me a little bit about how you spend your time away from work and how you recharge. Yes.

Speaker C: Well, I will tell you just a funny story on recharging or just the at work part, because I'm in a different location now. Right. I've been in Wealth Management 20 plus years.

Speaker A: Yeah.

Speaker C: Now I'm in a tech company and I'm not used to the practice of meditation. It's just not something you see in a Fortune 500 company with a room before.

Speaker A: Who has time for that?

Speaker C: I just Remember in my first couple of weeks, sitting there, just totally uncomfortable with what was happening in the room. So that is not one of the things that I do. I still haven't got accustomed to that yet. But I do go for long runs and long bike rides. That's actually my form of meditation is probably through long pain and suffering. That sort of forces my mind to escape somewhere, then my breath.

Speaker A: That's great. Yeah. I think I've seen you online in biking, uh, regalia. Are, uh, you an ardent biker or cyclist?

Speaker C: Yeah, I love it. I think one of the great things about cycling is the aspect of community, because you just get to sort of ride with friends, have a ride for a couple of hours, have a long conversation. It's like doing that in golf, except you're getting a lot more exercise.

Speaker A: Yeah, we'll have to come back to this at some point. I've been thinking an awful lot lately about just how technologically immersed, enmeshed we all are. And I'm thinking that more and I'm reading more and more about how important it is to have that softer side of life. And in the event, for another time, we'll maybe have a conversation about how you strike that balance. I haven't figured that out yet, but I keep threatening.

Speaker C: So.

Speaker A: Rob, thanks. This is a, uh, great conversation. As always. Appreciate your thoughtfulness, your clarity. I also appreciate the good work you're doing around advancing the cause around productivity and effectiveness in our world and industry in particular for our audience. Thank you for tuning in today. If you've enjoyed our podcast, please rate reviews, subscribe and share what we're doing here at Wealth Tech on Deck. We're available wherever you get your podcast. You should also check us out on our dedicated website, wealthtech on deck.com. all our episodes are there. Rob, thanks again. Uh, this has really been fun. I really enjoyed it.

Speaker C: Great. Thanks, Jack. Appreciate it.

Speaker B: Thanks for listening to this episode of Wealth Tech on Deck, our ongoing conversation about improving financial outcomes for all. This podcast is brought to you by SEI and ah, produced by Turncast. Subscribe to future episodes in Apple Podcasts, Spotify or wherever you listen to podcasts. You can connect with our host, Jack Sherry on LinkedIn. For more information about our perspective on the future of financial advice, visit our website@, uh, wealthtechondeck.com.