Building Solutions and Automating Success Arnold Hsu on G Reminders, Fintech, and the Future of Productivity

Episode Overview

Arnold Hsu is a seasoned entrepreneur with over two decades of experience in the tech and fintech industries. Starting his academic journey with a degree in electrical engineering from the University of Southern California, Arnold developed a passion for technology early on, which led him to explore the intersection of business and innovation. His background in engineering gave him a deep understanding of how systems work, but it was his knack for problem-solving that guided him toward entrepreneurship. Over the years, Arnold has founded four companies, each focusing on leveraging technology to address real-world business challenges, the most recent of which is G Reminders, a scheduling and automation platform designed to improve workflow efficiency in the financial services sector.

G Reminders is Arnold’s latest venture, created to help financial advisors streamline their daily tasks by automating appointment scheduling, follow-ups, and CRM integration. His experience in fintech and business productivity has made him a thought leader in the automation space, helping companies save countless hours through smart, AI-driven solutions. Arnold’s focus has been to build tools that address the unique needs of financial professionals, enabling them to improve their customer relationships and increase operational efficiency without sacrificing personalization. His insights on the power of automation have made G Reminders a go-to solution for wealth managers and advisors.

Beyond his technical and business acumen, Arnold’s entrepreneurial spirit is rooted in his love for building. From his early days of working with computers to becoming a tech innovator, Arnold has always thrived in the startup environment. He believes that smaller companies offer greater opportunities to effect meaningful change. As a self-proclaimed “efficiency nut,” Arnold continues to push the boundaries of automation technology, ensuring that businesses not only run smoothly but also have more time to focus on growth and client satisfaction. His leadership at G Reminders reflects his commitment to solving problems and enhancing productivity through cutting-edge solutions.

Episode Transcript

Kevin Rosenquist: Hey there, welcome to Pay Pod, where we bring you conversations with the trailblazers shaping the future of payments in fintech. My name is Kevin Rosenquist, and thanks for listening. Arnold Hsu loves solving problems, especially when it comes to business. He’s founded four companies, the latest of which is G reminders, a scheduling and automation platform that integrates with your existing calendar to save financial teams countless hours of time spent scheduling appointments, following up, confirming meetings and things like that. It’s designed with financial advisors and fintech companies in mind, integrating everything together within the company’s current CRM. We talk a lot about productivity, how automation is poised to be a huge game changer in our business and personal lives. And of course, we chat. I. Joining me now from Los Angeles, Arnold Sue, you’re a self-proclaimed serial entrepreneur. What is it about starting a company from scratch that just gets you all jazzed up?

Arnold Hsu: You know, building. I love building things, right? Even when I was a little kid, building Lego sets, whatever. So I get interested in problems and how to solve those problems and having direct, meaningful impact on those solutions. And, you know, when you work for a large organization, large organizations are great. They have a great distribution channel. And, you know, you can sort of become an expert in, you know, very specific area of that business. And that’s great. It’s also safe. Right. But you as an individual don’t have the ability to move the needle as much, in my opinion, in a large corporate and in large organizations as you do in a small one. And so as a result, you know, I spend my time sort of, you know, starting companies, getting them to a certain scale and then eventually exiting them. And I’ve done that. You know, this is my fourth one. So I enjoy the process. I enjoy chaos to some degree. But I.

Arnold Hsu: Think.

Arnold Hsu: But it is difficult and it is not something I would recommend for. For most people, quite frankly, it is very difficult. You end up focusing, you know, a lot on problems, but it’s something that I enjoy doing. You know, even when things are going well, you’re still focusing on the areas that aren’t. Right. So 80% of the business could be doing great, but you’re focused on the 20% that isn’t. And then, you know, you start switching. But I enjoy that because I enjoy again I enjoy solving problems, be it, you know, in the business or be it for customers or clients, and then having and then seeing it sort of, you know, a relatively immediate result as, as a result of those actions.

Kevin Rosenquist: I saw that your education was in electrical engineering. How did you go from that field to leading B2B enterprise software companies? Were you a computer guy or were you a coder?

Arnold Hsu: Yeah, I was I mean, I enjoyed, you know, technology when I was, when I was a kid. I mean, computers were, were just really sort of, you know, coming on. There was no internet, you know. So I’m 50 years old, right. So you can kind of do the math. But I’ve always enjoyed working, working with computers and I’m half Chinese. And if you’re Asian, you have two options. One is be a doctor. The second one be an engineer. I mean, it’s,, sort of cliche, but that’s sort of the, the options that you have in that sort of family. So I didn’t want to go through, you know, 15 years or whatever of med school and all that. So I said, okay, fine, let’s go down the engineering track. I enjoy technology, but what I quickly realized is that hardware is actually more difficult right than software. Because if you make a if you make a mistake on hardware G, you got to rebuild the whole thing. And it’s very expensive. And and with software, you know, a bug is a bug and that can be patched. And when I was first getting started there, the internet was really just beginning. And, you know, this was like late 90s, right, 98 sort of time. And, you know, SAS wasn’t a thing. There was no such thing as software, as a service. You know, these sort of crappy, you know, websites, corporate websites. I think Amazon was maybe just coming online, stuff like that.

Kevin Rosenquist: But over time we were reminiscing about GeoCities. Do you remember GeoCities? Sure.

Arnold Hsu: Yeah, I remember I.

Kevin Rosenquist: Think that episode, uh, an interview I did last week, we were talking about that and it’s, it’s really funny to think about how horrible.

Arnold Hsu: You know, they’re pretty bad, but they were, you know, you thought they were state of the art. Oh my gosh.

Kevin Rosenquist: It was groundbreaking. Like it was mind blowing.

Arnold Hsu: So over time, you know, SaaS became a thing or the delivery of software became a thing and that was more commonly accepted. You know, I don’t know if you remember, you know, when Salesforce was coming online, people were deathly afraid of putting customer data on somebody else’s server. And, you know, their whole pitch was, you know, no software, which is ironic given their software company. But I thought it was a phenomenal marketing pitch because traditionally software was so difficult to install and maintain, and you had to have system administrators managing, you know, windows servers and all this sort of stuff.

Kevin Rosenquist: Oh, yeah, I remember I was in marketing, I remember Adobe before it went SaaS. You know, like we you’d have to, you know, constantly, like there’d be bugs and you’d have to download patches and you’d have to do all this stuff. And it was like it. I mean, when SaaS first came out with Adobe, it kind of ticked me off because I’m like, wait a minute, I got to pay a monthly fee now. Well, I just want to download this product and use it. And now I see the benefits obviously of of switching to that model.

Arnold Hsu: Yeah. And Adobe is also getting the benefits of that as well. Right.

Kevin Rosenquist: Yeah. Oh of course. Of course.

Arnold Hsu: So I used to buy Photoshop, you know, once every 2 or 3 years or five years. Now you’re buying it, you know, yearly, but you are getting the benefits, you know, of those enhancements. And it was.

Kevin Rosenquist: Expensive. So I don’t know if it’s really that different as far as from a cost perspective. I mean, I remember Photoshop being like $700 for one, you know, like so and that was just Photoshop. That wasn’t the full suite. So, you know, I never really sat down and done the numbers, but I don’t I’m sure it’s benefiting Adobe just fine.

Arnold Hsu: Yeah. Their stock price reflects it. 

Arnold Hsu: Yeah. All right.

Arnold Hsu: Um but but so you know the delivery of software is now online and you know has been for a while and we’re all sort of, you know, getting the benefits of that. But I you know, I understand I, I gravitate towards business problems, consumer problems I don’t really understand as well. So, I tend to understand business problems and I go and try to solve them.

Kevin Rosenquist: Yeah. I was gonna bring that up. Actually, the theme of your products seems to be like business productivity, workspaces, workflows, project management, task automation, data capture, very highly competitive space. But is there any particular reason you lean in that direction, or is it just because of what you said? You just understand the problems more?

Arnold Hsu: I tend to get those issues. A lot of them tend to be more back office driven.  and I’m like an efficiency nut, right? So like when I see stuff and, you know, people doing repeatable processes that I know systems can do better, you know, I tend to dig into kind of those areas so that that probably tends to be why, you know, you see what you see.

Kevin Rosenquist: So now you’re running G reminders. It’s a scheduling and automation platform that integrates with your existing calendar in Google Outlook etc.. So what does G reminders offer that you can’t already get with your existing Google calendar your existing outlook calendar.

Arnold Hsu: Yeah. Good question. So let me start off by saying that we are a vertically focused business. And what I mean by that is we are focused not for the masses. We are focused predominantly in financial services, more specifically around sort of wealth management or wealth advisory. So we started the business several years ago being quite horizontal and focusing on notifications, pre meeting and post meeting. Right. And really kind of hence the name G reminders, which sort of stems from Google and then reminders and sort of that sort of combination. And it was a relatively simple product quite frankly.  and you know, we were doing text messages, voice. You would hook up your Google calendar, you would send notifications Pre-meeting Post-meeting. And we were selling to a lot of B2C type companies. So companies doing business with consumers were not very good about showing up to an appointment and things of that nature. And really over the last couple of years, you know, we started observing, we started observing certain verticals that had high concentration, right from a customer standpoint.  and we started digging into that and really found financial services that really sort of had a gap. And, you know, when you ask about what the differentiations are between us and what some of the other scheduling systems do, there are many, but they are tend to be very generic. And so we have spent probably the last two years building for financial services, wealth management specifically, and integrating with all of the systems that those organizations use today. Right. So specifically, it could be things like their CRM. Right? So like redtail, Wealthbox are dominant players in the CRM space.  We work with Salesforce, HubSpot, and other systems like that. We also work with compliance systems like Smarsh and Global Relay.

Arnold Hsu: We work with other types of client engagement platforms like precise FP. We work with VoIP providers like Intels. These are all like very focused on that industry. Right. And so, you know, I think in general when organizations buy products, they should really look at data interoperability, right. I think that’s super important. You know, working with systems that are siloed, don’t talk to each other is really bad and is bad for a variety of reasons. One is there’s probably manual work or, you know, there’s low code platforms that also sort of help with that, but they usually are not very good and are quite brittle. So, you know, think of like a Zapier or something, something to that extent. So in our opinion, data really has to flow across your tech stack. And if you know, we’ll get to this, but if you want to apply any kind of AI to anything, you better have clean and structured data. And if you don’t, it’s going to hallucinate, right? Like like you’ve seen a lot of this. So. So we are an end to end meeting platform if you want to, you know, just use certain bits and pieces of our system. You can do so. But we really cover the full meeting lifecycle right from scheduling a meeting to notifications, pre meeting workflows that kick off when a meeting is scheduled, the ability to ingest contact form data back into your CRM. Creating opportunities. We have a note taker product that we’re releasing here which is in meeting right. That captures notes summaries, action items, pushes those into the CRM, and then handles a bunch of stuff post meeting around follow ups and those types of things. So it’s really end to end product that is designed for financial services and that’s where we’ll focus.

Kevin Rosenquist: You mentioned the appointment scheduling. I saw that when I was digging into reminders. And so I use Calendly now for my meetings and bookings for this show. You know, you guys booked with me through, through calendly, uh, and, you know, I saw you guys are integrated with zoom the same way Calendly is g reminders a replacement for Calendly? Is it does it work similarly?

Arnold Hsu: Yes. There are certainly elements of what we do that are calendly like again, Calendly is a great product. They’ve been around for a while. They’re, you know, a large player in the space. They have a great product, but they’re horizontal, meaning they appeal to the masses and they don’t have the kind of integrations that, frankly, financial services needs. And so we are seeing a lot of customers move over from Calendly again, because of our, you know, financial services focus. And so a lot of our customers are able to replace Calendly with, you know, a couple other products essentially with our sort of end to end solution.

Kevin Rosenquist: Yeah. And I was just looking at I’m like, oh, it’s cheaper than Calendly.

Arnold Hsu: Yeah. There are elements. Price tends to be a factor. But you know, we tend to try to, you know, value, value price. Right. Yeah.

Kevin Rosenquist: There are a lot of tools here that the audience of financial professionals and fintech people would benefit from, as you said, that you’re you’re focused on the financial sector. I was particularly drawn to the automation piece. I think the automation has been something that, especially with generative AI, that a lot of stuff has been a lot of companies have been working to automate as much as they possibly can. Talk about what automation features G reminders are able to provide.

Arnold Hsu: Yeah. So there was a study put out by kids in 2022 and they surveyed like a thousand plus, uh, financial advisors of where they spend their time around clients. Right. And so I took some notes here. So there were four hours. This is per client per year okay. They spent four hours of meeting prep, three hours in meeting follow ups, seven hours in client correspondence. So you’re talking about, you know, 14 hours, right? Per client per year. So that’s a lot of time, you know, if you’ve got, you know, 100, you know, 100 customers or 100, 100 clients that a single advisor is working with, that’s 1400 hours. That’s probably 70% of your year right there. So when you use systems that create efficiencies in all of those areas that I just talked about when we ran our own surveys, we’re seeing 40 to 50% reduction or efficiency pickup by using systems like Arps. And so let me talk to those a bit more specifically. So when it comes to things like scheduling, right. So financial advisors spend a lot of time just getting meetings on the books or things like annual reviews or bi annual reviews. You want to talk to your customers. You want to explain to them what’s going on in the market, how their portfolios are doing, what their goals are. Et cetera. Et cetera. This is where the wealth management advisors spend most of the time, and should spend most of the time is working with clients. But there’s a lot of time spent just getting that done. And so we have basically systems automation effectively that will understand when the last time a review was had and automatically try to schedule meetings with their clients. And that’s all done 100% automated without you having to do anything. And we know when we send out a notification, for example, if they book, if they don’t, we’ll send another one and we’ll send another one and we’ll do that a few times essentially until something gets scheduled. So that’s just.

Arnold Hsu: One.

Arnold Hsu: Piece.

Arnold Hsu: Of.

Arnold Hsu: Sort of the scheduling side of things, right? Then you have sort of notifications to make sure that, you know, people actually show up, things like that. We have when you are in meeting, we are we’re effectively, you know, taking notes,  summarizing those, creating action items out of these calls that that are being had automatically push those back to CRM,  create tasks in CRM again, making sure that everything is on track and people are manually journaling, logging all these different types of things. No, we’ve.

Kevin Rosenquist: Got your reminders. I note taker here in our meeting right now.

Arnold Hsu: There you go.

Arnold Hsu: You know, those are the types of things that are happening. And also, you know, when meetings get scheduled, for example, there’s certain tasks or workflows that might get kicked off as a result of scheduling annual review or a new introductory call with a client, things of that nature, things that need to happen. And so we’re doing a lot of things around data collection again, getting it into the systems that need that information. Again, from an automation standpoint, you know, if you’re using a calendly or something like that, you end up doing a bunch of stuff manually. Cally is great at getting the meeting, but then you got to take that data and push it into those other systems, right? And again, like those sorts of simple things and a lot of it, there’s a lot of nuance around field mapping and getting the right data types. And there’s a lot of brain damage there. But we handle sort of a lot of that, a lot of that for you. And then also follow ups. Right. Follow ups post meeting.  you know, here, here, here are the things that, you know, we asked you to do, you know, make sure those get done. So, you know, we’re really shaving 40, 50% of time that is spent, you know, doing these things that I talked about. And if you look at that, in aggregate, you’re talking about like 600 hours per advisor per year. That’s like three working months. I mean, if you really, you know, if you really take that to heart, like you could take those hours and days and months and apply this to revenue generating activities, which is like go get more clients, right, you can work more efficiently. And that’s a huge deal because you talk about, you know, AUM and and really, you know, what drives revenue. Grow the AUM and either grow it by spending more time with existing customers, getting their assets or go getting new customers. I think it’s a huge deal.

Kevin Rosenquist: Yeah. And one of the I would say one of the most exciting things I, you know, for me, as far as AI goes, is, is automation, you know, is just the, the, the addition of that in so many ways aside from like medical advancements and all the awesome stuff that we’re seeing. But, you know, for just me personally, you know, I’m eagerly awaiting that true AI assistant, you know, the Scarlett Johansson in my ear kind of thing. You know what I mean? Maybe not to that level, but you know what I mean. Like a real because. Because, you know. You know, I don’t want to say it, but, you know. Hey, Google. Yep. There it goes.  it’s not the best. You know, it’s fine, but it’s got a long way to go. You know, you guys are in that realm, you know, obviously. How close are we to having, like, a true AI assistant, do you think?

Arnold Hsu: I am blown away every day by its capabilities. And, you know, AI has been around for a long time. We’ve been, you know, more recently, just really over the last, I don’t know, two, two years, something like that. You know, Llms have essentially become, you know, somewhat mainstream, but not to the extent that you’re describing. Right. You still need to kind of go seek it out. I think the large players Google, Microsoft, Amazon will embed these into their assistants that they have today, right? Uh, Apple etc. like Siri, Google, Alexa, those types of things. I think part you know, one of the issues potentially, you know, maybe a cost factor, although that is, that is constantly being driven down. So I think you’ll start to see those things in a more mainstream capacity. But if you use, you know, some of these chat systems like GPT and you start asking your questions. I’m using it daily for things like brainstorming, you know, if you need some questions about code or anything like that. I mean, it is it is truly phenomenal. I mean, I’m really blown away every single day by.

Kevin Rosenquist: I’m worried I’m getting a little too reliant on it. Like, what was it last Friday when that big, big meltdown happened in the network? Chatgpt was down for me for like the entire morning or most of the day. And I was like.

Kevin Rosenquist: I gotta like Google stuff now. Like, what do I do?

Arnold Hsu: Yeah.

Arnold Hsu: It’s really it’s it’s really phenomenal. It’s really phenomenal. And just the, the, the change between, you know, GPT 3.5 and four was massive. I mean, really, really astonishing and was really, really surprised. And I think you’re gonna see, you know, two, three, four more iterations of that really from a scale standpoint. And then, you know, probably the algorithm, you know, needs to needs to morph a bit, but it’s really astonishing. And it’s on, you know, sort of last mile delivery folks, right. Like ourselves to sort of find the use cases that are most applicable,  you know, beyond sort of, you know, the general system stuff that you’re talking about, but just find those use cases that are most applicable to, to, you know, the LMS or, you know, other AI, things like machine learning and other things like that, that been around for a while.

Kevin Rosenquist: You know, you’re a tech guy, you’re a business guy. Like, is there any AI aspect that you are particularly excited about that maybe we don’t hear about as much. That’s not as in the mainstream media.

Arnold Hsu: I don’t know, you know, I think the,  I mean, it’s not as applicable to, to what we’re doing necessarily, but I think, you know, some of the image and video things that are going on are, are.

Arnold Hsu: Just.

Arnold Hsu: Really. I mean, they’re really mind blowing. Yeah, they’re like ability to edit a video or edit an image, you know, by just just speaking to it. You know, you don’t have to learn Adobe Lightroom or whatever. I mean, it’s really staggering. We tend to work in a more tech based world, at least from our standpoint. So, you know, we’re leveraging AI, you know, for summaries and action items and, you know, pulling salient information out of sort of composite data. And it works quite well for those things. And it continues to get better. I will say that like prompt engineering is a real thing. Like you really need to think about and sort of, you know, engineer how you ask it questions,  to get better answers. So, measuring the output and the quality of that is sometimes a bit challenging. But I mean, really it is a transformational thing.

Kevin Rosenquist: And you can, I mean you can talk to it like a buddy. You just might not get exactly what you’re looking for. I mean, if you just need something simple, like, yeah, you can just be like, hey, what’s up? How’s it going? Can you do this for me? And it’ll do it. But yeah, for true, like, if you really know the prompt engineering stuff that it does change some things as far as what kind of outputs you get. Yeah.

Arnold Hsu: Yeah. And so giving it context. Right. Giving a context understanding, you know what kind of conversations being had is this. Is this a sales call versus is this a client meeting or you know, those types of things or what type of industry is it? You know, those types of things do help a lot. Again, context, just like, you know, just like if you kind of go back to, you know, first principles thing, you know, you want to understand who the audience is, what what am I having? Why am I even having this discussion? And so, you know, you know, sort of level setting your, your, your mind from a contextual standpoint, I think it’s important for computers or humans.

Kevin Rosenquist: You’ve got a countdown teaser on your website that says something big is coming, I think nine days. Yeah. This episode won’t air until after that, but just for my benefit, can you give me a hint? What?  Anything.

Arnold Hsu: Anything. So.

Arnold Hsu: So we’re really launching. So what we’ve done and I kind of talked about this already,  in here, but,  you know, we’re essentially launching sort of this, this end to end meeting platform. Right. And so note taker is a new product for us.  it is officially launching on the first. And so bringing that into the fold is really sort of, you know, what we’re announcing. So rather than just talking about scheduling and automation, we’re really talking about the sort of end to end platform. And that’s ultimately what, we’re launching.

Kevin Rosenquist: Wow. That’s exciting.

Arnold Hsu: It is.

Arnold Hsu: It really is. I think it’s, you know, we have a bunch of customers sort of in, in beta test right now. It’s going extremely well. Very solid feedback. We’re launching with five platform support.  zoom,  Microsoft Teams, Google Meet, go to meeting WebEx and um also in uh, in person um recorded. And you know.

Arnold Hsu: There’s a.

Arnold Hsu: Lot of.

Arnold Hsu: Exciting things.

Arnold Hsu: There, just and there’s a lot of nuance there too. But just, you know, if you take a single audio stream and then being able to understand, you know, different speakers not understanding their names, but then inferring names from what is being said and then applying names to those speakers, it’s very complicated, actually. It’s a very interesting problem. We love it. You know, we like solving problems and we think it fits super neatly into our story.

Kevin Rosenquist: That’s awesome. Well, Arnold, thank you for joining me. The company is G reminders. The website is G reminders.com a lot of information on the website and different pricing tiers and all that. So if anyone’s interested check that out. Arnold thanks so much for being here.

Arnold Hsu: Thank you Kevin.

Arnold Hsu: Thanks for having me. Thank you.