AI-Powered Meeting Management for Financial Advisors with Arnulf Hsu

Jack Sharry: Hello everyone, welcome. Thanks for joining us for this week’s edition of WealthTech on Deck. Today we’re going to speak with someone who has been a serial entrepreneur leading and running B2B enterprise software companies for the last 20 plus years. He’s been a CTO, he’s been a CEO, a product leader, and a board member along the way. And somehow he has landed in the WealthTech space. We’ll learn more about that in a moment. Arnulf Hsu is CEO and founder of GReminders, which is one of the leading scheduling and SMS reminder platforms for professionals in our world. It is ranked number 32 fastest growing software products by G2 in 2023. Arnulf, thanks for joining us on WealthTech on Deck today.

Arnulf Hsu: Thanks, Jack. Great to be here.

Jack Sharry: So, Arnulf, you’ve been a serial entrepreneur over the past two decades. GReminders is not your first rodeo. First, let’s talk about GReminders. What is it? What do you do? Who do you do it for?

Arnulf Hsu: Thanks. So GReminders is, I’ll give you the abstract versions first and I’ll get more concrete, is an AI powered end-to-end meeting management platform built for financial advisors. We’re exclusively focused on wealth managers and so we spend all our time in sort of this wealth tech space. So let me talk about what that means, what meeting management platform end-to-end means. We look at everything through the lens of sort of a meeting life cycle. And so when we look at how financial advisors interact with their clients, they meet with them once a year, twice a year, maybe four times a year for super high net worth or something to that effect. We are deeply integrated with the systems that they use. So we look into the CRM, for example, we understand the cadences that they have with their clients, we can automatically reach out to them to get them to book that performance review onto their calendar, for example. So we send out notifications. We would continue to send out those notifications until that action happens. So taking a lot of that sort of manual work to actually get something scheduled off of an administrator’s plate. Once they book, once they get a meeting on the calendar, we would kick off workflows, for example, inside of the CRMs, again, within their existing systems to get things done that might happen before the meeting to the client or to the end client. We essentially send out emails, SMSs to make sure they actually show up for the meeting. Before the meeting happens, for the advisor, we would send out a pre-meeting brief, very nice summary, using generative AI and so forth to basically summarize all of the things that have happened since the last time you met with them. So looking at notes, looking at previous discussions, looking at action items, tasks, activities that have happened since the last time they met with them to get them better prepared. We also have a AI assistant product. Think of it as ChatGPT on top of the client record. So if you want to ask additional questions to get you better prepared for the client meeting, they can ask any questions they want. And again, it’s pulling all the data from the systems that they use already. And then in meeting, once you’re in the meeting, we have a note taker product that automatically records, transcribes, and pulls summaries and action items from those calls. So neatly summarizes those for you, recommends tasks and action items that you talked about in the call, allows the advisor to push those back into their CRM, their system of record, effectively, making it super simple. We also recommend workflows that you might want to trigger after the call, as well as recommend opportunities that they might want to track for maybe certain types of things they talked about. If they talked about marriage or something like that, maybe you might recommend merging finances or things of that nature. And they could track those as opportunities within the CRM. And then we’d help them essentially with some follow-up emails as well. So again, this whole end-to-end meeting life cycle, we’re trying to automate as much of the administrative stuff as humanly possible using automations and AI. And then doing all that in a compliant friendly way.

Jack Sharry: I have a question for you on all that. So you seem to have a pretty good ability, as I reviewed your history, of evaluating business problems and customer pain and then figuring out solutions that customers like. I think on your website it says love, but you get the idea, right? And I guess the question is, how did you come up with this idea and why did you pick the wealth management space to do it?

Arnulf Hsu: Yeah, great question. So, I love generally solving business problems, right? So, at the core, that’s what I enjoy doing. Software is eating the world. I’m a technical founder. So, you know, I used to write a lot of code. I don’t write as much code anymore, but I still do some. The joke for engineering is like engineers work really hard to be lazy, like, so they try to automate as much as they can. And so, you know, I kind of follow that path. And so, you know, I’m very much focused on use cases and benefits, features obviously support those things, but, very much focused on use cases. I spend a lot of time talking to customers and so forth, trying to understand the problems that they have and deeply listening to those things. So, in general, we started the business about four years ago, but deeply focused really on wealth management in the last two and a half years. And that’s really all we’ve done.

Jack Sharry: And why wealth management? What was the draw there?

Arnulf Hsu: Yeah, so when we started the business, we were selling to a variety of professional services organizations, right? Could be legal, accounting, financial services, health care, and so on and so forth. I’m a big believer in vertical markets, and it helps to focus all of the disciplines within your company, sales, marketing, right? You know what to say, who to market to, what your audience is, what product to build, what features to build and so on and so forth. So a big believer in vertical markets. And we looked at a couple, but wealth management quite frankly stood out the most. A, we had a decent amount of interest and it’s sort of an existing customer base that attracted what we had. So that sort of made sense. But also there was a gap quite frankly in this area where there were scheduling products that were installed in our customers that to some degree that they were using, but they weren’t very good. And what I mean by that is they were good products, but they were not deeply integrated to the systems that are used by financial advisors. And that’s kind of where we dug in. We’re a big believer in sort of interoperable systems, right? Like if you have a bunch of data islands everywhere, it’s not going to do anybody any good. If you ever want to use AI and analytics on top of this stuff, you better have systems that talk to each other and data must flow between them. And so we spent a tremendous amount of time over the last two and a half years integrating into systems that financial advisors use every day. It could be Redtail, Wealthbox, Salesforce, all the overlays, Smarsh, PreciseFP, know, on and on. again, being deeply integrated is really what sort of sets us apart from some of the other systems that are out there.

Jack Sharry: So what I’m hearing, this is kind of interesting. What ended up happening, it sounds like, with the wealth management space, there’s good data, but it’s not well connected. And so what you do is connect it from soup to nuts from, I’m assuming it’s once they’re a client or as they are onboarded, that you’re really tracking the information, the data and what have you, to really keep track of it in the life cycle of the appointment but then life cycle the relationship. Is that sort of your secret sauce? Is that depth of connection and interoperability?

Arnulf Hsu: Yeah, that’s right. So let’s just take a couple of concrete examples. So if you are collecting information either from a new prospect that wants to meet with you, you might be asking some questions from an initial intake form. Does that make it to your CRM on day one? Or are you getting an email and you’re manually keying that in? So we automate that fully connected, full field mapping into the system. So you’re collecting all of that data. If you’re asking for a performance review, for example, somebody is again scheduling with you. You might be asking some questions that update the client record. Is that stuff getting back into your system record? And if your systems aren’t connected, that stuff is sitting all over the place. We spend a lot of time in those areas. Also, when we do reach outs, when we send automatic notifications and so forth to end users, we are pulling data, again, from those systems of records to enhance and enrich what is being sent out. So again, deeply connected, both not just from a data perspective, but also from a workflow standpoint. So we spend a lot of time in those areas.

Jack Sharry: Tell me a little bit about the feedback you get from advisors and any that you hear about from clients. What’s their response to all this?

Arnulf Hsu: It’s been a really, really good reaction. I say we have definitely hit, in the software space, product market fit, you’re probably familiar with the term. But it sort of, you know, hits you in the face when you have a good amount of demand, you know, you have trouble hiring people and so forth just to meet that.

Jack Sharry: Good problems, right?

Arnulf Hsu: Yeah, good problems, high conversion rates from demo trial to buy, those types of things. So we’re very pleased with what we’re seeing. We definitely think that there has been a gap and we’re certainly filling that. And we also think wealth managers aren’t IT experts, right? And so like we believed pretty strongly on a smaller technology stack, right? That has less moving parts, is inherently a better system because you have less complexity. And so we take a variety of point solutions that are out in the market. Could be scheduling, could be SMS, could be workflow products, could be note taker products, and try to sort of bring as much as that, at least under one roof. Not the entire tech stock, obviously, but elements that make sense specifically around that meeting lifecycle I talked about.

Jack Sharry: So what I’m hearing is that you’re really able to just have a better… present and follow up on a better experience for the client. And that what I keep hearing as a complaint, I’d love to have you comment on this, among advisors is that they don’t want to be a CTO. They don’t want to have to figure all this stuff out. And it sounds like you’re connecting a lot of dots, leaving out the portfolio management aspect in terms of the client interface, follow-up operations, just staying on top of the client relationship. Is that what you’re hearing back from the advisors you’re working with?

Arnulf Hsu: Yes. There are, and you might be familiar with these systems, like there are middleware products out there like Zapier and things of that nature that are sort of these low code tools that allow you to sort of glue different systems together. They do require some technical skills and it’s on you to maintain those integrations. And I don’t think that’s why financial advisors got into this business is to sort of DIY a lot of these systems together on their own. And so if you can natively integrate deeply with the systems that they use today and minimize change management, like change management is hard, hard, hard. So for the most part, people aren’t spending that much time within our systems. Most of our stuff is generally a background service. And the most time they would spend perhaps is with the AI assistant where they’re asking some questions using just plain English and or interacting with say a meeting summary, you know, after the call, but looking at it, pushing it back into their system of record and then they move on.

Jack Sharry: So you’ve had some experience, you’ve started up other businesses. I have a few questions all around the same sort of topic, but I’d love to hear your thoughts on this. So you’ve started businesses in the past. I’m curious how this compares to those. How’s this different, easier, better, harder? Curious about that. I’m also curious about the reception. What’s the uptake? How’s that going? You mentioned it seems to be going well, but I’d like to hear a little bit more about that. And I’ll ask my next question around, where is it going from here? But let’s just stick with those two. How does this compare with other businesses? Your business is now two years old. How does it compare to the past businesses you’ve started up and how is it feeling in terms of the evolution of where you are now? And then in a little bit, we’ll talk about where it’s headed.

Arnulf Hsu: So I’ve run three previous sort of enterprise software companies, if you will. This one is really very much a product-led approach. In other words, sort of free trial, assisted sale, higher volume. Some of the previous ones were a bit more enterprise-y. In other words, higher price point product, mostly go to market through a sales force. And I think people are more comfortable these days in trying things, but you still need to couple that with humans, right? So you still need to couple that with customer success, onboarding, and those types of things. So I would say, we service a lot of, in many cases, smaller firms could be three, five, 10 person sort of advisory firms. And so it’s more of a volume sort of approach where some of the previous ones have been more enterprise-y, if you will. We are moving more up market, but I think a product led approach to sort of go to market has been good for us and sort of given us volume and those types of things. So I would say, those are probably kind of the biggest differences, but the other thing that we spend a lot of time on is we spend a lot of time listening, right? We spend a lot of time with customers listening to what they’re saying, what they like, what they don’t like, what they wish, and then asking a lot of questions like why, why, why, why, why, until we sort of get to the root cause. And then like we iterate that relatively quickly. And so if you look at our release cycles, you’ll see us put out new stuff every three or four days. And so when you talk to somebody and you hear this a few times, and then you turn it around in two weeks, they’re like, wow, you guys are actually really listening to us. And that sort of interaction with our clients, it goes a long way.

Jack Sharry: Talk a little bit about that and maybe in the context of you’ve learned, I’m sure with every company you’ve done, but also with every conversation, especially now, that you’re having. Talk about that experience. It seems so obvious, but I just wonder sometimes whether that’s done sufficiently in the marketplace. But talk a little bit about the learning process through listening.

Arnulf Hsu: So most people, if you have a product, they’ll ask for a feature enhancement of some kind. And I’ve seen a lot of people just deliver on that and that may actually solve the problem or may not. You really need to understand the use case and you need to understand the why. And if you don’t understand the why, you literally have to ask why, like in many conversations, literally asking why like four or five times. And it sounds almost silly, but finally, if you ask enough times, you will actually understand what they’re actually trying to do. And customers will give you a solution based on the knowledge, the scope that they have, but they don’t know all this other stuff over here. And so if you can come up with a real, a better solution. They’re like, oh yeah, I never even thought about that. That’s great. And so it’s really about listening and then knowing all the tools that are available to you and also the systems and the data, it helps. I’m an engineer by education. So I spent a lot of time in software engineering teams. And so I have a pretty good purview about what is possible and what the t-shirt size is on all these things. So there’s a lot that goes into that.

Jack Sharry: This is a comment to my listening audience who might be in sales or marketing or product development, something we found, LifeYield being a software company, something we found, a couple things are not clear. Often they have a rough idea where they want to get, but they have a predisposition as to how they might get there and what they need to have. And I’m sure you’re finding this and I want to have you comment on that in a moment. The idea is that they’re trying to figure it out and they may guess wrong or they may guess off a little bit. And a lot of times we’re just trying to figure out what is it you’re trying to do. And we’ll talk about it. It sounds exactly like what you’re doing, which is really refining the understanding of what the problem is so then you can develop the solution. But fill us in, I think this sounds like exactly what you do.

Arnulf Hsu: Yeah, 100%. And there are many ways to solve a problem. A, are you even the right product to do that? Maybe there’s another mechanism for that. Maybe it’s a partner approach. Maybe there’s an integration. If it’s within the wheelhouse, see where that fits into your roadmap. And if you’re hearing the same problem multiple times, maybe that’s an area to invest in. But of course, you need to look at the market and see what other folks are doing and so forth, but you’re constantly playing jujitsu with your roadmap, and that’s where the art comes in. There’s always the things that you know you need to do, but once you get through that, then you need to figure out this kind of fuzzy middle where you need a decent nose. And over the years, my nose has gotten a lot better.

Jack Sharry: Yeah, I presume AI enables and accelerates that, true?

Arnulf Hsu: So, AI has been around for a long time. When we talk about AI these days, we’re probably talking more about generative AI. It’s enabled a whole bunch of things on our roadmap in the last year. Pre-meeting briefs and post-meeting summaries and pulling out salient opportunities and tasks and different things from conversations. I don’t know if it’s helped so much necessarily like refine a roadmap. I use it personally as a way to collaborate with somebody. So I asked all kinds of questions and it might take me down certain tracks and I find it very useful sort of from that perspective.

Jack Sharry: Yeah, I’m not sure we’re far off from one another. I find the more questions I ask, the more I discover I didn’t even know to ask. And that informs my later questions or my further reach down the road. In fact, I’ve talked a good bit about this, I teach a class on the topic. And I’ve been urging students, just get in conversation. Don’t worry about the answer. Just worry about the question. Just follow wherever you’re going and just refine your understanding and you’re going to get to an answer one way or another. But I just try to learn with every conversation and when I do that, there’s so much I discover that I just didn’t know I was going to find out. But it was so useful just by being open to trying to solve the problem as opposed to have the right answer. Does that resonate with you?

Arnulf Hsu: 100%. So you don’t know what you don’t know, right? And I think what AI has, generative AI has done for us in general, I think it will make us better in asking questions. And I think asking the right questions is probably more important than even the answers in many cases. So I think being able to formulate questions that have context and so on and so forth, I think will make us better as a society in general. Prompt engineering is a real thing. We spend a lot of time doing it. As an engineer, we tend to be binary about stuff. But I think in general, I think asking questions, asking the right questions is really important.

Jack Sharry: So in this journey, in this process of learning all that you’re learning, what’s next for GReminders and what’s next for the industry? I don’t know what you’d call it, AI or SMS optimization. Tell me what’s next, what’s coming.

Arnulf Hsu: So, variety of things, we continue down the sort of AI assistant path for certain, getting access to more data, you know, data normalization is always challenging, connecting to many systems. So, we spend a tremendous amount of time connecting to API’s and getting access to data, normalizing data. So we’re going to continue to go down that track, continue to integrate with systems that advisors use every day. We probably have like 35 plus integrations today under our belts. Second, would say AI is very good at personalization. So around recommending next best actions around client engagements, things like that, based on previous discussions, conversations and those types of things, sort of personalizing that outreach more. And then thirdly, if you think about all of the interactions that you have with your end clients and the systems that you have, historically, it’s mostly been manually updated, right? CRM is great, but really required somebody to put all that stuff in there. And so I really think, and we’re not there, but I think that having access to all this unstructured data gives you, and AI is going to be very, and is, and will continue to improve significantly over the near and midterm, would allow you to actually keep all those systems up to date without you doing anything whatsoever. And so this idea of like this organic CRM with almost zero administrative work, that’s a goal that I think maybe we’ll get to, know, over the midterm, but I think that’s a very interesting area. And nobody got into the space to do a bunch of admin work.

Jack Sharry: Yep. So, any key takeaways you want to leave with our audience before we look to wrap up?

Arnulf Hsu: Yeah, so look, I think, AI is obviously, AI is a big thing. I think to stay competitive and to continue to sort of enhance the client experience, I think financial advisors should spend time looking at tooling and those things. Think about use cases, right? Like don’t think about, I want to install AI, but think about use cases where that could be helpful. We’re seeing large benefits, again, in things like pre-meeting briefs, note-taking summaries, call summaries, action items, those types of things. I talked about tracking opportunities better. Opportunities historically have been underutilized within your systems. And so if you have a system that can basically surface those for you and what I mean by, you know, if somebody talked about selling a business, okay, let’s create an opportunity to look at liquidity planning, or if you had a new child, let’s set up a 529 plan, you know, think things like that, like AI is very good at that kind of stuff. Let it do that and make you better, right. So I would encourage folks to start exploring these areas because you do get a heck of a lot of efficiency out of these systems.

Jack Sharry: That’s great. Great conversation. Really have enjoyed it and look forward to having many more. We’re doing a lot of work on the podcast, not work so much as a lot of listening on the podcast around AI, where it is, where it’s going. And our focus, frankly, right now is to be practical and what you just described as practical. In other words, this is stuff you can use every day, roots out the inherent inefficiency in an overly administrative process, especially one that’s as regulated as ours. So, appreciate the work you’re doing. Thanks for doing all that. Thanks for this conversation. One last question before we close out, always my favorite. What do you do outside of work that you’re excited or passionate about that people might find interesting or surprising?

Arnulf Hsu: Very limited time outside of work, Jack, okay? I love building things. So honestly, I spend way too much time working and so forth. But I do mentorship for other entrepreneurs or founders. So again, related to work, I suppose. Also doing some mentorship for like a local foundation that helps high school kids with charitable projects and stuff like that. And I’ve got two kids and a wife. And so that’s really where the rest of the time goes. But we do try to take some extended trips from time to time, Europe, go for a month or something like that, kind of work part-time. I think three years ago, I think I logged about 30 ski days. So that was pretty good, but that hasn’t happened in a while. So, try to get out and do stuff, I work remote so it kind of you know sort of works out, time zone is less of an issue. But yeah, those are those are the few things that I guess I do outside of work.

Jack Sharry: I hear you, you actually just inspired me. It’s been on our bucket list, my wife and I, to spend a month in Paris. Why not just work from Paris for a month? It’s doable. It’s probably a little bit of an effort, but not really. Anyway, thank you for that little bit of inspiration, but I get it. So thanks for this conversation. I’ve enjoyed it very much. Learned a bunch, which I always appreciate. For our audience, thanks for tuning in. If you’ve enjoyed our podcast, please rate, review, subscribe, and share what we’re doing here at WealthTech on Deck. We’re available wherever you get your podcasts. Also, please check us out at our dedicated website, wealthtechondeck.com. All of our episodes are there along with blogs and curated content from many folks around the industry. Arnulf, thanks so much. This was really enjoyable. Thank you. I appreciate it.

Arnulf Hsu: Jack, thanks for having me.