[00:00:01] Speaker A: Hello and welcome everyone. I'm Taylor Pankratz, and this is behind the breakaway. Together with my co host Jason Barber, this show takes you behind the scenes of leaving your captive broker dealer firm and explores the world of ria independence.
All opinions expressed on the podcast by the hosts and guests are solely their own opinions and do not reflect the opinion of uptick partners. This podcast is for educational purposes only and is not legal advice and should not be relied upon as a basis for any decisions.
All right, welcome back. Episode 17 of the behind the Breakaway podcast. We've got Taylor here, and Jason's joining us. And today we're going to talk about a recent news article talking about AI and kind of firms embracing AI and what that can mean and the pros and cons of that. And to start it off, I think I would just, I'll just start reading the article and we can talk about it.
[00:01:07] Speaker B: Absolutely.
[00:01:08] Speaker A: So we've got Edward Jones's AI play. This is from Financial Advisors, financialadvisoriq.com dot. So Edward Jones AI play data stockpile includes 500,000 weekly client interactions. Man, it's a ton.
[00:01:25] Speaker B: 500,000 a week, basically.
[00:01:28] Speaker A: I think, to be fair, a lot of brokerage firms and just tech companies advise on CRM systems in the rea space.
[00:01:39] Speaker B: Salesforce, right? This is Salesforce. I think I've seen a commercial on tv that had Matthew McConaughey and it was like, your data is gold, or something like that. It was cowboys and Indians.
[00:01:50] Speaker A: And we like Matthew McConaughey.
[00:01:51] Speaker B: Oh, yeah. Except for he's a t sip. But you know, that's okay.
[00:01:55] Speaker A: And there's nothing wrong with that. I mean, I think that's the future is anticipating client hesitations or nervousness in the market or things that AI can pick up on, whether it's either tracking how the frequency or maybe the changes of a client logging in multiple times, or it's a different cadence or schedule that maybe they're used to logging in. So maybe that might indicate that they're nervous about the market and just predictive things that help you pick it up.
[00:02:27] Speaker B: On, help you to identify if a client is at risk of leaving, maybe by analyzing certain trend patterns and things of that sort.
[00:02:35] Speaker A: So I think it could be a great thing. And so this is what we fully.
[00:02:39] Speaker B: Embrace, AI, and we're not opposed to that at all.
[00:02:42] Speaker A: The article goes on to say it's humans armed with AI that are going to be best enabled to grow their practice and help clients the right way. That's how we're thinking about AI, we see AI as an opportunity to make our financial advisors more productive, insightful, and able to bring information to their fingertips that's useful to them and their clients.
And so it goes on. Say Edward Jones's advisors interact with 500,000 clients per week, adding that the firm is gaining valuable insights into the wants, needs, and wishes and walks of life of millions of its customers.
She said the firm believes AI can harness those interactions to provide insights to advisors and their clients on topics such as why a model or analyst opinion has changed, tax loss, harvesting, and market volatility. It's being able to use the power of AI to compose that narrative and help with advisor interactions. So, I mean, they're definitely spinning this as, hey, this is a good thing, and probably it is a good thing for clients.
But what's funny is we take a cynical view of this being on the other side, being on the other side and having left Edward Jones and starting our own race.
[00:03:57] Speaker B: I'm sure the things that we're worried about would never happen.
[00:04:01] Speaker A: Right, right. But what would be the things to be worried about? Because what I read into this is they are now, if they weren't taking this to an extreme before, in terms of every keystroke and every mouse click on the computer, if they weren't tracking it before, they are most certainly now using AI algorithms to track it, to predict it.
[00:04:28] Speaker B: It's not, did you hit this key? It's that we know which key you're about to hit, almost. Right. I mean.
[00:04:35] Speaker A: Right. And that's. And that can be scary for the advisor that's looking to break away.
[00:04:41] Speaker B: Absolutely. I think we were talking a second ago, Taylor. It's like the movie minority report, where you get arrested for a crime before you've even committed it, because they can start to anticipate the reality before it's even happened. They are going to know that you're breaking away before you even know that you're breaking away.
How are they going to know that? Because imagine if, and again, I'm sure this would never happen, but imagine if it were you and you were running a firm like this and you had, let's say, I don't know, the last hundred, the next hundred people that leave, or they have 100 people that leave in a year, let's say, and, I don't know, 100 advisors. Excuse me, 100 advisors. I think they have attrition somewhere in the neighborhood of around 5%, if I remember correctly. I don't know. And again, I'm not trying to pick on just this one firm, but let's just say industry wide. Say you have. So if you had 20,000 advisors, you're probably having a thousand that either got fired or quit or some. So I don't know how many people are breaking away every year, but hundreds of people are breaking away every year and, and going independent. And so it's not going to take you that long before you're going to be able to analyze.
You're going to have more data, data than you know what to do with about the intricate details of exactly what happened with every single client interaction, every single keystroke, every single, how many seconds you spent on this screen or that screen. I I don't even know what else is possible. Okay. But I mean, it wouldn't surprise me if, I mean, what, who knows? It may not be that much longer before they have some kind of ability to detect where your eyeballs are looking on a screen or what you're doing. I don't know. But I, it's not unreasonable to think that's what the future is and that they're going to be able to know that and look at trend lines of, hey, the last hundred people that left in the month before, they looked at their top clients and they looked at required distributions, and they looked at whatever it is, they looked at the notes they spent on average. So typically, in a typical year, they spend 80% of their time, or 70% of their time is with the top 25% of their business. But in the six months prior, it's interesting. They spent 95% of their time on the top 20% of their clients. That's interesting. And so then imagine you have that kind of data, and then you're able to take this trend line of 100 people and overlay that on your top advisors in the firm and start to be like, that's interesting. These fault, these people are matching up almost perfectly with this trendline. What are you going to do about that information? If you're the person who has that.
[00:07:33] Speaker A: Data, you're probably going to be start to really hone in on those particular advisors and make sure that they're nothing leaving and they're doing what's really interesting. As you were talking, I was thinking, wonder if there's any ability for them to, like you were saying they, they have this trove of data over the next few years, let's just say. And maybe by that point, it's thousands of data points. And they create these trends and they say, oh, yeah, million. But they say they have these trends of saying, all right, this is what's happened for every single one of our breakaway advisors. This is what's happened leading up to that. And then you end up breaking away, and they use this data, and they lay your data over top of these trends and use that as a case against some kind of tro.
[00:08:23] Speaker B: Oh, absolutely.
[00:08:24] Speaker A: Because it's. Hey, we have precedent. We have. We have not. Because proof is. How do you prove that somebody took data or didn't take data?
[00:08:32] Speaker B: Yeah.
[00:08:33] Speaker A: You would go, I didn't take. I mean, we didn't take data. You would say, we promised we didn't take data. And then all of a sudden, I. Jones or any of these people, Raymond James, any of these people are going to go, actually, we can actually prove that you did.
[00:08:46] Speaker B: Yeah, yeah, exactly. At least prove it enough to where a judge would agree with us.
[00:08:51] Speaker A: Right. I mean, it's like it. Yeah, it truly is a.
It truly is a. Is it. Does that give them enough evidence to tro you? Because they have these previous cases and they're gonna go, these people left. But I guess it doesn't prove that you. That they took and that they took that either, though.
[00:09:09] Speaker B: Yeah, either that, or, like we talked about, it becomes, like, the minority report, and they either outright just fire you, because they just get to a point where they're like, we know the trend line and the numbers don't lie type of a thing, and so then they just outright fire you. Or maybe they don't fire you because maybe there's some legal concerns there, but maybe they try to smoke you out, and so they come, they say, hey, we're, like, 99.9% sure that you're about to break away. Is that true? And why would they do that? They would do that because they want to try. Even if you resign at that moment, they've now thrown you off your game. Right. It is now no longer your decision of when you resign. It's now their decision. They also, by the way, probably have already lined up who's going to be the babysitting advisors at this point. They already know because they already were able to anticipate. The AI computer literally has already anticipated that this person over here is a 90% chance of leaving. And let's already get the babysitting advisors picked out. We already know who's going to. Like, we know the clients, and these clients know these clients.
[00:10:19] Speaker A: And so there's exactly. That's a really interesting point. Like, how can we get the highest client retention?
[00:10:25] Speaker B: Yeah.
[00:10:25] Speaker A: By marrying up who these advisors are and who they might know. And who they might be more comfortable with as a baby sitting advisor.
[00:10:33] Speaker B: You bet.
[00:10:34] Speaker A: And because if you're listening to this and you work at one of these big box broker dealers, and you think that's not what they at least want to be able to do, they might not be able to do that. We might be thinking and giving AI too much credit, or these kind of the data that they're going to be gathering too much credit, but that's certainly what they would want to do, because that's saving them hundreds of millions of dollars.
[00:10:56] Speaker B: If they could increase by 10%, if they could just be like. We would have gotten 80 or 90%, but instead we were able. The advisor only brought 70% or 60%. Because why? We knew that this client goes to the same church as this advisor because we use AI, and we just know. We know that's happening. We know that there's a increased probability because they go to church together. So we're gonna. The thing is already. It's already planned out ahead of time.
[00:11:22] Speaker A: Yeah.
[00:11:23] Speaker B: I mean, it's not crazy, and it's what I would do. It's what I would do.
[00:11:31] Speaker A: This whole thing of matching up people that are even related to other.
When we broke away, we had people that were family with other, like, people that had family relationships of the clients that were family with each other. In our book of business, they got split up to different advisors.
[00:11:50] Speaker B: Exactly. So dumb because they didn't know, because it's not the same last name, or.
[00:11:54] Speaker A: They had no idea. And that was dumb, because wouldn't it make sense that you're at least putting this family unit at least to the same person? Yeah, but so just something as simple as that, or.
[00:12:06] Speaker B: Well, shoot, let's think about even this new tool that we're testing out called Finney and how they can now start to understand which clients might be more inclined to a particular advisor based on a person's values, maybe. Right? Is it not crazy? Or is it not possible to think that's even doable? Okay. That it's. We're gonna line up.
Maybe it's political beliefs, maybe it's religious beliefs. Maybe it's. We have kids that are the same age. Maybe it's that our kids play baseball. Maybe it's.
[00:12:40] Speaker A: Yeah, well, maybe you can spend a little. Maybe you can spend a second on talking about what Finney is, because what's what. Maybe people that are listening don't understand is that. And they probably do, but if you don't, the amount of information that AI can scrape from just the Internet about you and put together what they would like, this picture of you or this idea of who they think you are in your values and your relationships. And it's fascinating.
[00:13:11] Speaker B: Yeah. Yeah. So Finney, is Aihdenkhdev data. I don't know what the right word, but, you know, it's a data mining software company, a startup company that we're maybe in the pilot program maybe would be the right way to describe it. And essentially what they claim to be able to do, and we don't have enough experience to have fully vetted it yet, but they claim to be able to be able to prospect better by understanding what, let's just take me, for example, like what my values are. I have three kids underneath the age of x, and I go to church. Here's the people that I vote for. Here's the value system, the fact that maybe I live on land or whatever the thing may be, and then they are able to take these things and then say, okay, let's go across the entire country and let's find people that we think would get along with Jason.
Okay. And then what they're going to do is they're going to, and this is their, I'm probably stealing their thunder a little bit, but in essence, they're going to reach out to these people on my behalf and essentially try to set up a discussion. And they just think that the probability of success there is higher. And I'm sure it is.
[00:14:27] Speaker A: It's no different than when we're advertising on Facebook or LinkedIn, where you can create a lookalike audience, say, here's my clients and I want you, Facebook or LinkedIn, I want you to go out and go put ads in front of people that are just like these people over here. And I mean, that's currently possible. And we're at the beginning stages of this AI thing. And so just think about if you had, and that's what Facebook knows about you, which is probably a lot, but it's significantly less than what your big box broker dealer is going to know about you because they know everything about, they know your income, your network. They know everything about you.
[00:15:10] Speaker B: Yeah.
[00:15:11] Speaker A: And they have all the notes of everything you've ever said to your financial advisor. He's that they've either recorded or typed into this computer the amount of information that that they have on their clients and can use data to try to make it when you break away, to get you to not take as many of those client relationships as you as they can, the amount of money that's at stake for these people. They have the. I mean, it would be in their best interest to throw millions and maybe hundreds of millions of dollars at this idea, because they're saving that in reoccurring revenue by getting a handful of clients.
[00:15:51] Speaker B: 10% of them, to not let.
[00:15:52] Speaker A: To not go with you.
[00:15:53] Speaker B: If you think about what is $30 million of clients or 40 or $50 million of clients, if they had a $500 million person wanted to leave, they could maybe even improve it by $50 million by implementing some of these. It's worth a lot of money. It's worth a lot of money.
[00:16:09] Speaker A: And there's billions of dollars that come in and billions of dollars that leave every year from breakaway advisors. So I think that it's.
[00:16:18] Speaker B: Yeah, you would be. I think it's fair to say that you would be foolish if you did not anticipate that this is for sure what the future holds.
[00:16:28] Speaker A: Even. We've heard a story recently where you had an advisor that was an employee advisor at a firm, and they sent an email from their personal email account, personal device, personal email through the.
Through their workplace Wifi. And that email got sniffed out because it went through some, like, barracuda thing, some kind of email filter, something, and they basically got found out that they were gonna leave by sending an email from their iPhone, from their Gmail account, to the recruiter. And it just so happened that they had connected to the company's Wi Fi to do that. And that's. That.
[00:17:14] Speaker B: Yeah, that is obvious. That's happened.
[00:17:16] Speaker A: But you'd be like, that's obvious. Of course, they probably are looking at any email traffic or Internet traffic that goes over their wifi. But, so, if you're an advisor listening to this, you need to be extremely careful, because you can be so careless, and you get fired. Yeah, you get fired from your job because you're just not thinking. So. And now they're going to take the offensive, and they're going to go. They're going to go on the offensive and say, now we are going to predict before you send that email, we're going to predict that you're about to send that email, because we have all this data of hundreds of people that are left before, and this is the screens that they went to, and this is where they spent the most time. And this. And guess what? We see that you're starting to do that. You're going to get found out. So, anyways, the key is, don't do that. Don't take the data, don't go do that. Trust in your relationships. But unfortunately, as much as you preach that, people don't do that.
[00:18:15] Speaker B: Yeah, I remember when we were in the days leading up, it was just very much business as usual. And that's the way it has to be. And you just have to show up one day. And hate to use the analogy, but it's just like, you just have to show up one day, and it's like, I got raptured. I'm just gone. Like, I didn't take any information with me. I'm just. I just vanished. And it's.
I do think that ultimately, at the end of the day, it is going. It is undeniable that the future is going to be more difficult on breakaway advisors. So I think it goes back to what we've oftentimes said, maybe on this podcast, but certainly privately, Taylor, is that you just. Folks have got to make a decision of, do I want to be an employee advisor? And if I do, then I want to be the best dad gum employee advisor that ever lived. And I'm going to drink the Kool aid, and I'm going to not even come anywhere close to the line. Okay. And I'm going to play by the rules. Because if you don't, if you even think about it, if you get. I mean, it can really come back to bite you. And if you want to be a business owner and you think you're a business owner already, then you would be very wise to think about doing that sooner than later. That's what I think about that. I think you would be very wise to get out while you can. Right. Because it is. The future is for sure going to be more difficult to do this. It just is. It's undeniable. And short of literally blowing up your business almost, it's going to follow.
[00:20:02] Speaker A: It's going to follow the same progression that any. That, as technology develops, it gets harder and harder to do a lot of the things. I mean, it may. It gets easier to do the simple things, but it gets a lot harder. Fix your car. It's really hard to just fix your car now because it's got all this thing, whereas it used to be relatively simple. So technology makes it easier to do a lot of things, but it makes. When they don't want you to do it, when they don't want you to leave, it makes it incredibly hard. Right. They're going to make it extremely easy to service your clients and to do a great job. That's the goal. Right. But if they. If you try to do something that they don't want you to do. They're going to, they're going to make it incredibly hard to do that because there's millions of dollars on the line and this is a, an invet. Think of how, think of the return on investment that this AI is for all these firms. It's tremendous.
[00:20:58] Speaker B: Yeah.
[00:20:59] Speaker A: And so, yeah, they're going to spend the money because they can make that money back hand over fist by preventing you from leaving or finding out, you squashing your plans, making you leave early. If you leave early, you're not taking 90% of your book. So that's if they can just do that.
[00:21:13] Speaker B: Yeah.
[00:21:14] Speaker A: They're saving money.
[00:21:15] Speaker B: Yeah. Much less smoke you out.
[00:21:16] Speaker A: Yeah. If they can just get you to leave a week early.
[00:21:19] Speaker B: Yeah.
[00:21:20] Speaker A: You're not going to take 90%.
[00:21:23] Speaker B: And again, I think the big thing is not only that, but if they, imagine if you were, had to leave a week early and the day that you left, somebody else was already calling your clients and they go to church with them, or they know their kids or whatever, like, they know. And that advisor knows ahead of time that this person voted for Donald Trump. So they pick up the phone and they call them and they already know because why they have access to voting records, whatever it may be, they already know. So imagine, I don't want to say the name, but, you know, one of the people that was our, one of our babysitting advisors, the dude that likes to stomp his feet and stuff, and you imagine he picks up the phone and he's, oh, man, are you voting for Donald Trump? Oh, man. All of a sudden it's, oh, man, this guy, he's, he's like me.
[00:22:09] Speaker A: He gets me. He knows me already.
[00:22:11] Speaker B: He already knows me. Okay. Imagine that. And imagine how much more. And again, you don't have their contact information, you don't have their phone number.
It is for sure going to be more difficult. It is. So I think that, again, if you're.
[00:22:28] Speaker A: Listening, so the way to do it is you got to be smart about it. Let us, if you want us to help you, we would love to help you. Right. Uptake partners would love to help you break out of jail. Right.
[00:22:41] Speaker B: We've got a book.
[00:22:42] Speaker A: We've got a book that you can go download. You go to our website, check out our podcasts. We'll send you a free book. Just go to our website and request one. I mean, we want to be a resource for anybody listening of how to do this the right way, the smart way to do it, the most effective way to get the most client retention and make. Make this be a good experience for you. So uptick partners would love to come alongside you and Sherpa you up this proverbial Mount Everest. So if that's you, if you're listening to this, I've been kicking the tires about doing this, and. And just at least start the conversation with us, because we'll be very candid. It might not be a good fit. It might be. Hey, you should wait a little bit. But odds are we talked to you. We talked to. I won't say. I mean, tens of advice, not hundreds. I don't want to be. I don't want to be exaggerating, but we talk to tens of advisors every month that are thinking about breaking away, and a lot of them say the same thing, which is, I would love to. I just don't know if I can. And I don't know if it's the right time or the time is I'll do it next year. And the reality is, there's never a good time to do this. Yeah, there's never a good time to do this. You're always going to be busy. The kids are always going to be busy. The kid, there's never a good time to do it. But every single person, if you ask them, they'll go, I wish I would have done it earlier. I wish I would have done it sooner, because it's not fun. But it doesn't get any easier. The longer you wait, it just gets harder, and this whole AI thing is going to make it even that much harder. So, anyways, if that's you, if you're listening to this and you've been kicking the tires on it and kicking the can down the road a little bit, reach out to us and at least see what uptick partners is all about and how we might be able to help you. Because we built this thing to help advisors like you break away. That's the entire purpose. That's why we do the podcast. All right, that's a wrap. Thank you for listening. We hope you enjoyed the podcast. Please subscribe to our channel. You can find more of our episodes on YouTube, Spotify, and Apple podcasts, and check us
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