Innovators Fireside Chat

Financial Planning's Innovation Awards recognizes tech and wealth management firms that are making ground-breaking strides with fintech and AI. Join us as some of our award winners discuss their approaches to adopting advanced technology, the potential for changing the face of wealth management and what's to come.

Transcription:

Brian Wallheimer (00:11):

All right. I am going to get us started and maybe if the folks in the other room here are still, they'll head our way as well. Hi, I'm Brian Heimer. I'm Editor-in-Chief of Financial Planning. You've seen me up here bantering throughout the last couple of days. I'm excited about this panel especially. We did a new thing this year. We started the innovation awards at financial planning and we were looking for companies who are actually putting AI into the marketplace, who are implementing AI and trying to kind of get the ball rolling as this technology continues to grow and mature. So today we've got three people on stage with us who are doing that. They're companies of all won innovation awards. That's no secret because we announced that a few weeks ago, but later, after the close we're going to have an innovation award ceremony in which we will honor all of them and we will actually name live two innovators of the year that we have not made public yet. So right now I want to welcome to the stage Andrew Altfest.

Andrew Altfest (01:10):

Thank you.

Brian Wallheimer (01:11):

He's from FP Alpha. Yeah, Mike Wilson. Orion and I'm sorry, Brad DeLoatche

Brad DeLoatche (01:20):

Brad DeLoatche

Brian Wallheimer (01:21):

I knew I was going to say it wrong.

Brad DeLoatche (01:23):

The worst was Deli Roach. I had that happen one time. That was terrible. But you're way better than that.

Brian Wallheimer (01:28):

At least you got the mic right.

(01:29):

I got Mike Wilson.

Michael Wilson (01:31):

That's, that's a tough one. People mess up quite.

Brian Wallheimer (01:32):

Got a cousin named Mike Wilson works out for me.

Michael Wilson (01:35):

I tried to check in with Mike Wilson, my name here at the hotel and they were like, which of the Mike Wilsons are you?

Brian Wallheimer (01:40):

Oh man. Well, I want to start off, we're going to ask just a few questions and then we are going to open it up. I'd love for this to be a little bit more interactive than some of the other panels. A little bit more time on your questions than my questions, but I do want to kind of seat this and get us going a little bit. And my first question is, from your perspective, you're doing this, you are providing AI solutions, you're putting AI into practice. Where is success in AI today? What's driving success in AI?

Andrew Altfest (02:08):

Well, I think you have to look at where we are as an industry and for years and years there's been this investment in technology to automate the back office and that's where we've squeezed as much as we can out of the back office with tools rebalancing, with account filling, automated account filling forms, technology like that. But the work that the advisor is doing all day long, the work, if I were to go at, I'm also a financial advisor. I lead in addition to being founder of FP Alpha, I lead a larger RA firm. If I were to look at what people at my firm are doing right now, they would be doing one of a few things. Either they're communicating with clients, they're on the phone with a client, emailing a client on video call with a client, or they're doing some work behind the scenes for a client.

(02:58):

And that work has not been able to be automated previously. That's the promise of AI. Promise of AI is to take the work that we as advisors are doing all day long and automate it to free us up to do even more for our clients, spend more time with our clients, doing more to improve their wellbeing, broadening services to clients, working with them differently, changing how, how there are opportunities to work with more clients, bring in close clients faster, mean, so this is why it's taken off because the technology, there is this opportunity and now there's technology to do this that wasn't there before and the advancements that we've had in the last couple of years have really opened the door for a lot of huge opportunity development.

Brad DeLoatche (03:48):

Yeah, I would totally agree with that. I would say from my perspective, one thing that we see a lot of success with AI in is cyber Krakens helps with your marketing. And so generative AI is a big deal for us and we see advisors seeing a lot of success with it. I've heard I talked about quite a bit in this conference, and one is that blank page, right? What am I going to write about generative AI is so helpful to combat that or also even just give alternate versions of some of the content that we create. Give me a different version, a different voice, a different tone, and it can just generate it like that. Really, it takes a lot of time. It buys a lot of time back for the advisor that they would, and I think that's the point, right, is how do we empower advisors with this modern tool to become more effective and to do more in a more efficient way.

Michael Wilson (04:53):

I think those are great examples and I think there's definitely multiple ways that AI can improve the advisory practice. Two that come immediately to mind for me is one is just driving better outcomes for investors. Think about the way that I happen to not entirely agree with Michael Kisses earlier. I believe that the personalized experiences that we can help advisors have through ai, just really understanding the investor before you have a conversation with them, ultimately that's going to lead to them making better decisions, helping you to really engage with them and have much more just personal discussions, understanding their needs better and catering to them. So that's one. And then two, putting my entrepreneurial hat on for a second and maybe my CFO hat on for a second. It's all about driving operational efficiencies in the middle so that your bottom line will improve. I think the more that you're able to cut out some of the fat from your business and replace that with automation and AI, the better that all of you will achieve EBITDA.

Brian Wallheimer (06:10):

Yeah, so your firms have all had success obviously, but what are some of the huddles, what are some of the pain points for your firm still today or even more broadly for the industry in wider AI adoption?

Andrew Altfest (06:27):

I think the pain points for, we launched our FP alpha to all advisors in early 2020 and what we heard at the time, what we were telling people that you can upload an estate document and it'll be read using AI, natural language processing and understood, and people would fight us. You can't do that. We don't hear that anymore. So we were early and I still think we are. There's been a much bigger investment in the technology ChatGPT has really captured the imaginations of consumers and businesses alike, and we're all awake to the possibilities with AI now. I still think we are early still as an industry. I think that there are some tools now and there are many good tools that are here, any platforms that are here that are worth taking a look at, but still there are going to be more entrepreneurs who are going to come out and find ways, novel ways of using the technology to solve problems.

(07:42):

The technology is going to continue to increase in its capability. And so I think that that's, that's some of the challenges today. And even what we can do today is not as much as we can do tomorrow. We have to continue to reinvent ourselves. And so what we wanted to do four years ago, we couldn't, but now we can. And so some things we had on our roadmap four years ago, which were like blue sky type ideas, now we can actually go back and start to execute them. So that's what it's going to be like going forward as well. So I think these are all challenges, opportunities that we're seeing right now. All good stuff though.

Brad DeLoatche (08:33):

Yeah, I see. We have generative AI today in our platform, but what I'm really excited, that's just a beginning. What I'm really excited about is giving that so much more context and we're working in looking at that on three different fronts. First is at the contact or prospect level, second is the advisor level, and third is the enterprise or firm level. So at the contact level, if we could give the AI a little bit more context around what's this contact been interacting with, what's going on with their lives, what's their estimated net worth, either for the individual contact or a segment of contacts, if we could supply the AI with that when it's generating, it's going to get a little bit closer to the mark right off the bat. Then that second level is at the advisor level.

(09:27):

If I was using the system, me as an advisor, how do I communicate, how do I relate to my clients, things like that. If we could also give that context to the ai, it's going to be that much closer to the market right off the bat, buying that tie back. And then third, at the enterprise level, we want to pull data around what are the top advisors doing in the enterprise, that top 20% and how do I facilitate those kinds of ideas to the other 80% of the firm so I can improve the effectiveness and what kind of things are the enterprise trying to push as far as products or services? And if we can give all that context of the AI when it's generating, it's so much more exciting, so much closer to the mark and ready to go out the door and then beyond. That's take a step further, not just when I'm in there manually going to try to write this thing and it's taking all that context, but also in the background how I want. We're working towards the system, taking all that context, looking at the data and offering up those opportunities. Hey, we have this segment of clients, here's what they have in common. We've gone ahead and generated this content for you, you want to send it out. That's where I'm excited about going.

Michael Wilson (10:45):

And I think AI is clearly moving at such a rapid pace that all of us are at risk for jumping the shark, right? By the time we roll something out, it's already yesterday's news. I've got a prime example of that. In fact, what we won the award for here at Advice AI is for our compare tool and what we call a smart summary and the first version of that before we rolled it out. Basically what it does is it takes in a workflow of information from trading to rebalancing and pulls in risk intelligence and a whole scenario, and it builds this really nice narrative for an advisor with which you can go back and talk to an investor. And by the time we got that into our lower development environments and started testing it, we're like, whoa, this isn't that great. It doesn't sound like it would've been crazy business to say your computer could give you this narrative a year ago, but in the time we're like, well, you could just put that and then maybe chat GBT and get the same thing and so on and so forth.

(11:48):

But what really set it off is when we embedded our behavioral finance persona into it and all of a sudden the language and the narrative went from being a very, I don't know, binary discussion between a computer telling you that you did these trades and so forth to made this very human connection in the natural language that would resonate with an investor whose persona might be a maximizer as opposed to a minimizer. If you haven't taken our B five 20 questionnaire, you got to check it out. I can give it to you later if you'd like to flip through it. But again, the key there, the message there is try to get ahead of it, right? This is moving at such a rapid pace that you can't slow down. We almost got to production before we iterated and made something a whole lot better.

Brian Wallheimer (12:39):

Sure, sure. The three of you have been here. I've seen you wandering, I've seen you on panels, I've seen you making connections here. Have you learned anything the last couple days? Is there anything when you get on the plane later, I assume none of you live in Vegas. I don't think you do, but when you get on the plane where something's going to click in your head from the last couple of days that you're excited that you picked up.

Brad DeLoatche (13:07):

I'd say one thing that I got out of when Michael Kites is up here speaking earlier today that really resonated with me was are we spending time on the right things on optimizing the right things with AI? I think if we continue to think of it through that lens, even as an individual when you're jumping into an AI tool and you're excited about using it, but not really sure, think about the tedium, think about those things that take a long time, that don't really give you joy, that aren't really the core of what you do best in building those client relationships. That really resonated with me a lot and I like that sentiment.

Michael Wilson (13:59):

Sure. I think it was, I hope I don't bot your name. I think it was Chrisy from LPL yesterday. Is that, do you recall?

Brian Wallheimer (14:07):

Yeah. I don't know who had bot your name?

Michael Wilson (14:12):

So she gave an analogy about radiology and so I learned a lot about radiology last night in my room. I was really interested to learn.

Brian Wallheimer (14:22):

Rabbit hole.

Michael Wilson (14:23):

Yes, yes. So I went down that because I think her analogy was something along the lines of radiology isn't going to get displaced because of ai, but rather it is just going to allow those people to be more inclined. Patient facing radiologist should be more patient facing. And I was like, well, shoot, I've never met a radiologist in my life. I tore my ACL, my doctor got the MRI, the radiologist read the MRI sent it back to my surgeon. The surgeon did the operation, all that. But then I googled radiology of course, and apparently maybe a lot of you or maybe a lot of you guys have met with your radiologist. I never have. And then I called my buddy this morning who's a radiologist in Manhattan Beach, and I was like, Ben, do you meet with patients? And he is like, well, I actually have very good bedside manner, but I don't get to do it as much as I can, as much as I want to because I'm constantly reading these images. So Christie was right is what I'm getting at. And the application back to advisors is I think comes full circle is that AI is going to give you these superhuman powers that you won't have to do all of this reading of images. You're going to be able to spend more time with your patients. And I think that was a big finding for me beyond the radiology front.

Brad DeLoatche (15:50):

Yeah, I like thinking of it as a colleague that you can pass off all the grunt work too to help you that much more.

Andrew Altfest (15:59):

Yeah. I think for me, just seeing how much AI is on the minds of everyone from individual advisors to large enterprises, everyone's investing in these tools and I think that as much as we as advisors are going to be better as a result of having these tools, we're going to be able to offer more to our existing clients. We're going to be able to do this, take what the wealthiest have had in a manual form and bring it down to everyone, including the mass affluent. We will be able to as much as we'll be able to do all of this, what I also am taking away from the broad interest is that we can't be too complacent. We can't, because a lot of advisors are making their money on a transparent fee for service, but then there are others that are going direct to consumer or making their money on everything from bank deposits to investment product sales and doing and are able to, they're also investing in these same tools and as a result there's going to be more competition. Now how fast that comes, regulators, all that stuff, who's going to get comfortable with compliance? We can't be too complacent because people big and small are making these investments. There's movement away from different traditional channels like banking and into more broad forms of wealth management. So I think our industry needs to do invest in these tools and provide more service to our clients, focus more on the personal side. I think there's going to be increased competition. It's a big opportunity, but we can't just do business as usual.

Brian Wallheimer (17:56):

I'd love to open it up now. We've got a nice crowd here. Any questions from you for these folks? Don't be shy please.

Brad DeLoatche (18:10):

Looks like over here, we got one.

Brian Wallheimer (18:11):

Got one over here.

Audience Member 1 (18:20):

Do you see any areas that AI shouldn't be implemented either because of the complications it would cause or there's maybe a minimal or negative ROI?

Michael Wilson (18:39):

Yeah, I mean, listen, I've fallen the trap myself a lot of times I think to look to AI first to answer things. But one thing that I'm trying to challenge myself with is asking if I could use an algorithm as opposed to an LLM to solve certain things, right? Because the compute is obviously far less. If I can you run an algorithm on something as opposed to trying to pass it through in natural language. So that's something that's worth considering in my opinion is do you actually have to go that route? Do you really want to use an LLM? Do you want to use a vector database as opposed to a relationship, a relational database to solve some of these questions?

Andrew Altfest (19:33):

I think the answer is yes, you want to be able to use AI very broadly. The thing that I think we're going to be dealing with as an industry, it's funny, we deal with this now to some extent. So on the wealth management side, when we hire a new advisor, we give the advisor, the prospective advisor a case study. We say it's basically like here, should someone take a lump sum versus annuity? Let's see if they can answer this question or how would you build an investment portfolio? And it's very interesting because today if you do that, you see practicing advisors who don't understand the assumptions of the tools that they use. And we've had people do projections to average life expectancy and it's like, well, what happens if they live longer than average life expectancy and just other areas? And it's because we rely on the tools that we have.

(20:36):

And I think having powerful tools, AI that tell us what is the optimal outcome, but really these are tools that we should be thinking about the outputs and overseeing the outputs. And these tools are going to take an advisor, all of us, from 50% to 90%, that's great, but there's going to be, I think we need to invest even more in these different domains and having great understanding of what is coming out from the AI. And so us as technology providers, we have to do a great job at doing this. It has to be accurate, it has to be explainable. You have to understand why it's coming to the conclusion. But the industry itself, we all have to be able to dig deeper and understand and grow our technical acumen and understand because we're going to be advising people in more areas. So I don't think there's anything wrong with giving it to ai.

(21:40):

Everything should be given to AI, even the relationship side of it. If I'm speaking to one client segment, someone who wants to take a lot of risk, and I have one client I work with who says, go big or go home. She's program. So you need to speak to her in a certain way versus someone else. And it's fine to have a tool that helps you with that, but the advisor, we still have to use our judgment. We still have to be able to understand what's there. And I'm fearful that having a genius assistant, we're going to stop short of doing that. We're going to be too much too reliant on the technology itself. And I think that that is something that's probably inevitable, but still creates an opportunity for those of us who really still understand how to go from 90% to a hundred percent and can differentiate our advice and service.

Brad DeLoatche (22:35):

Yeah, I would say another challenge too is, I mean there's going to be a lot of regulatory challenges as we explore this new territory. Absolutely. But to piggyback on what you just said too, we don't want to be too dependent on it all the way to the point that when you go and meet with this client that there's a disconnect between we have all this knowledge, we know who you are using that information, and then you go meet with the person and you forget to add that piece in there about you and who you are and why you relate to this person and why you're a good fit for your client. And having that and building that relationship is a super important part. So even though the way in which you're using AI is, I mean it's important.

Brian Wallheimer (23:28):

We've got one here.

Audience Member 2 (23:30):

So as technology plays a bigger role in the advice process, do you guys think at all about what the implications could be for the business model of the industry, the value sharing between how advisors are paid versus how platform firms like yourselves are paid? I mean, you're investing a lot in figuring out how to bring this AI capability to your clients. It's going to save them time once we sort out the kinks, right? There's no question that's going to add value. So how does that get shared the different stakeholders in the value chain?

Brad DeLoatche (24:11):

Yeah, it's definitely another interesting piece that we're going to continue to be working on together. Even in this conference, there's a lot of different service providers here that are using AI in all different interesting ways. And now we're at this point where we don't have that all figured out yet, and that's something that we're going to be navigating together. How do we share this kind of information back and forth in the right way that benefit us because we're businesses, but also benefit the client? What's the outcome? So it's definitely an interesting challenge that we have ahead of us.

Andrew Altfest (24:52):

Yeah, I think it depends where we all fit in use cases and the value that we're driving for advisors. So if we're helping with sales and we're helping to close business, that value is very high, right? I think that our industry is willing to pay for tools that will help bring in more business. If our value proposition is efficiency, it's another value, it's another type of cost. If the value proposition is connecting with the next gen or the value proposition is automation of communication. I think these types of, all these use cases have different value to the advisor and it's not hard to, I think if we're doing our jobs correctly as technology providers, then we are helping everyone understand that the value we provide. And so for example, at FP Alpha, we've had customers of ours bring in, we have one customer who at a very, very large firm, who brought in a hundred million client using our tool. So we have these new use cases that I think our industry don't just look at this as efficiency by the way. We have technology that we're just figuring out how it can help us drive more results in our business. It changes how you can price your services, forget fee compression. I think fees can actually go up. More value is being provided. I think 1% is just for investment management. Now we can do much more.

(26:33):

We can work with different types of clients if we as technology providers make it clear how we are delivering value and advisors are capturing that value. Then for those use cases, those use cases all have dollars attached to them. And the technology providers should be taking some percentage of that value, leaving a lot to the advisor.

Michael Wilson (26:56):

I think from an ROI perspective, the biggest thing that advisors that you bring to the table, of course is your human interaction with your clients. And the more that we can through AI and through our technology, improve your efficiency and open up opportunities for you to have more discussions with more people, whether they're clients or prospects, the better. Going back to the personalization at scale comment, that to me is what a key driver, whether you're using AI for prospecting or you're using it for ongoing client communications, the more conversations you can have with more clients, more prospects, the more you're going to grow organically. Think about that efficiency phase in the middle of your practice. Maybe you've got paraplanners and other folks in your office who are doing tasks like cleaning up NIGOs and moving data from one system to another over time as AI eliminates those jobs. Ideally you can take those people and put them more towards the front of the house, right? Maybe they're going to be become advisors themselves and your practice will grow again organically. So that's really where I see the ROI coming from. This is operational efficiency leading to top line revenue growth.

Brian Wallheimer (28:29):

Great. Is there one more? We have one minute left. I don't know if we've got time for another question or not. If not, I'm not seeing anything, so I'm not going to press it. Thank you all so much. Congratulations on the awards that we'll be handing out later. Everyone, please stick around. We've got one more session and then we're going to close up our conference and get to the innovation awards and then another cocktail hour. So thank you so much.