[Music]
[Jared: 00:08.3]
Ed, great to have you on the podcast here today. How are you?
[Ed: 00:11.6]
Very good, thank you. I just got back from a London to New York to West Coast, back to New York trip. So, just happy to be in my own space!
[Jared: 00:20.6]
That's a lot of travel – racking up those miles though when you have to go that far. Yeah. Wow. Those are long trips. Long trips. Well, Ed, I'm really excited to chat with you here today. For folks that don't know Bud Financial yet, I would love to hear kind of just a quick overview before we get started and then I have some questions, but as I told you, like very much I like to keep these casual conversations. So, let's start there.
[Ed: 00:44.3]
Yeah. So, Bud Financial, we are a fintech B2B company. We have been around in the B2B guise for about seven years. Uh, before that, we did two years as a consumer app in the UK. We focus on helping banks and fintechs take their core data, so typically transaction data, turn it into a bunch of actionable insights, either for use internally in the bank to understand what their customers are doing or give the customer of the bank or the credit union members insights into their spending – so they can make better financial decisions.
[Jared: 01:18.4]
So what kind of problems are you helping these banks and financial institutions solve? What type of information are they looking for?
[Ed: 01:25.0]
So there's this idea I guess we all have of our bank which is: because they see our spending, they know everything about us. And they have a bunch of machines and algorithms processing all this data and they're able to accurately target us. I think we hold that in our head as a thought, but at the same time, we also get these mail shots from the bank that we've been with for 10 plus years, offering us products that are completely irrelevant to us. All of our mailboxes are full of that stuff.
[Ed 00:01:54]
So the reality is that at almost every single bank we've ever spoken with (which will be, you know, hundreds – maybe the next year it will be into the thousands) we've never come across a bank with a system that is able to process their own transaction data and leverage that across the bank and and show customers real insight. No one's built that. There's a couple of people that have built poor versions of it.
[Ed 02:14.8]
It's really in the kind of era of more advanced AI models that we're able to do that very accurately now. But yeah, the reality is banks don't have that and we bring that to them. So there are many pains and solutions that come from that. Some around just giving a better customer experience is a simple one. Another one is customers see transactions that don't have a merchant identified, a location or regularity of how many times you've been to that merchant.
[Ed 02:39.4]
Customers often will call the bank and say I don't recognize this transaction. And that actually costs depending on the scale. The banks [can spend] hundreds of thousands up to tens of millions a year just dealing with those. So that's a really simple use case we solve. But there are, in the world of AI, much more advanced use cases and problems we solve.
[Jared: 02:56.2]
Yeah, the not knowing about certain transactions is actually pretty frustrating. When you look back over the years to see how little information there is actually, as the consumer. And I always think when you, you know, when you have to even from a different side of things, right, from the business side of things… when you know, take a picture of your receipt so you've logged in your receipt. I always said: “Why? Like, why do we even need to?” Shouldn't we just know everything about the transaction so then our accountants know everything about it? It was always crazy to be like: “Take a picture of this receipt!” Anyway, side tangent, but I'm very bad at that.
[Ed: 03:37.1]
Also a side tangent. I'm very bad [at that]. Oh, yeah.
[Jared: 03:39.3]
The only reason I'm saying it is PTSD, because my accountant always chases me down for those items.
[Ed: 03:46.9]
Absolutely. Yeah.
[Jared: 03:50.0]
So we hear a lot about personalization in banking. But what does good personalization actually look like to a customer?
[Ed: 03:59.8]
So when a bank is doing personalization, they're doing it off of—I used to, before I started [at Bud], I worked at Salesforce—CRM tools and the personalization that they are doing like: “Where do you live, how much do we think you earn or how much did you earn when you opened the account or when you took out the last credit product?” You know? Your age. That's really it.
[Ed: 04:28.8]
In financial services, good personalization is basically knowing the customer almost as well as, or better, than themselves – and then finding them an opportunity to improve their finances in some way. Whether it's a product or just a helpful nudge. That's what good personalization is.
[Ed: 04:44.9]
The nudges build trust, and then that makes the financial offers tailored to you from a data perspective, or kind of like more readily taken up by the individual because they already have some trust in the bank or the credit union.
[Jared: 05:00.8]
Can you give… I always like a complex example and a simple example of how transaction data can lead to a better customer experience.
[Ed: 05:14.7]
A really simple one is you have a credit card bill that goes out on the 17th. We notice on the 15th or the 16th that you don't have the current funds available and we know when your payday is. So, there might be an immediate action. We could know a week out or whenever we decide. So, that's a very simple one.
[Ed: 05:37.2]
A more complex one is understanding your FICO score, understanding through looking at the transaction data, like, if we have like the primary account or even if we have aggregate accounts, we can see almost all the different financial products you have, because there's typically a flow of money at some point throughout the year. We can identify those and then, say, maybe you're paying off two loans and we actually think there's a consolidation effort that could be done because we know what the loan rate the bank is offering or the loan rate that’s in the market. That’s a slightly more complicated one. But, it's just bringing lots of data points together.
[Ed 06:18.0]
If you think about a bank, say, a big bank or even just a mid-market bank in the US, they've got a million customers. They’ve got no machines that are processing this, and there's no person going through individual transaction statements to do this.
[Jared 06:34.9]
Now, what kind of reaction do banks have when they start seeing the insights that Bud Financial can uncover? Are there any light bulb moments there?
[Ed 06:42.6]
Yeah. I mean, for many years, we were kind of saying: “Look we have this transaction intelligence and look at all the things you can get from it!” And banks were like: “Yeah, that's kind of cool.” But then about two years ago we started building this product we call ‘Drive’ which is a platform you can go in where you can have data visualization. We can segment customers based on really anything in that transaction data and so what we often do with a bank is like [say]: “Give us, you know, a small file of your customer data and we'll pull out a bunch of insights for you. We just give them a login to the dashboard and there you can see a whole bunch of things.
[Ed 07:21.5]
We can see the credit card usage, you know, what credit cards and what products the customers have. That then gives the bank the insight to say: “Oh actually I didn't realize [that about] my customer.” Most banks assume, in the US, that Amex is the biggest credit card but [the data could show that] in your customer cohort it's actually not, and you're working on a partnership with Amex, as an example or, you know buy-now-pay-later, it being a big thing: “What do they use, when are those used in the month?”.
[Ed 07:56.1]
Then [those types of insights] lead the bank to say: “Hey actually I could probably offer a product that's specifically tailored to my customer cohort that maybe is competitive with Capital One, rather than trying to think about being competitive with American Express."
[Jared 08:09.6]
When you think through personalization efforts, have you seen any of these efforts backfire or ever missed the mark? What makes the difference between helpful and creepy?
[Ed 08:25.8]
Yeah. I think the creepy thing was a concern, I guess, like five years ago. Uh, when everyone was kind of concerned about Facebook data and being over personal. I think in financial services, if you're offering something helpful you’re not creepy. If you start to say, like: “Hey you started shopping at these certain merchants therefore are you about to have a kid?” Or like: “Do you know your partner started, you know, doing this spending on your joint account?” Maybe that's a little bit too far, and there's no financial outcome or financially related outcome directly it kind of doesn't make sense.
[Ed 09:02.2]
Where we've seen it backfire is just core inaccuracy. We began building this language model around 2018 that understands bank data very well. It's very tailored to that. There's two things that can go wrong there. One is that your model's not accurate enough which is most of where we get brought in. Banks are using other suppliers or they built something themselves and maybe they've reached something which is pretty good in the industry. It's like 80% accurate. But, like, if I was going to know you as an individual, Jared, like your financial world is… I'm assuming, you know, you're making hundreds if not thousands of transactions a year. And so if you're 20% inaccurate, those errors add up. And actually, if I want to give you an insight, it's more likely to be wrong than right if I have a high degree of inaccuracy.
[Ed 09:56.0]
So we've really focused for many years (and spent a lot of money as our investors will relay) developing really accurate, granular customer enrichment. So up to like the mid-90s in the in the US. Our older models, or more advanced or mature models, in the UK are 97% accurate. And then we have to build customer specific context models that get you a little bit further.
[Ed 10:20.5]
[The sort of] things we can see that this transaction is regular, even though it doesn't seem like a subscription. It is something that you regularly spend on. Therefore we might know that when you get a receipt back from that merchant, it's a receipt and it's not income, as an example. That often gets done because like sometimes, you know, you have a return that's close to your income. Or [it’s] even small things like you go to a gas station and you spend $3.50. You probably didn't buy gas, it’s probably a convenience store purchase.
[Ed 10:51.2]
So all of those little things add up to being able to understand you much better. I guess a lot of people have promised personalization and the miss has been that they haven't focused on the core problem which is that accuracy of of understanding the transaction from a machine basis. They've gone to the cool ‘bells and whistles’ of pie charts and things like that before.
[Jared 11:15.9]
Yeah, I would say, you know, going back to the earlier part, right, of the ‘creepy’, I think you're totally right. I think that was more of a conversation five years ago. I think it's more creepy now if you're so wrong with what you're offering me.
[Jared: 11:32.6]
Yeah. Right. This information is not like information I would care [about], right? Even spending habits and stuff like that. So, if I could have that more personalized to have a better understanding of, you know, who I am and what I want, that's awesome.
[Jared: 11:48.5]
Would love to kind of shift the conversation to a newer segment that I'm trying out where it basically allows you to put your storytelling hat on, right? You've been building this company. Talk me through something that you can laugh about now, but probably when it happened, you wanted to cry a bit.
[Ed: 12:06.2]
I still cry a little bit about some of these things. I mean, there's many things we've got wrong. You see all these things on LinkedIn and stuff of like: “Look how fast, you know, Cursor AI scaled to $100 million in revenue in less than a year!” And then look how long it took this one company to get product-market fit and we're on that curve. We're at 10 years now and getting product-market fit is just happening now, and it's like you can feel this pull in and so you kind of cry or laugh.
[Ed: 12:39.36]
Some of the missteps in 2017 to 2019 in the UK… We were helping three big banks build challenger apps. We were running the go to market, we're doing customer communication for them, we ran the whole thing and some of those banks actually invested in us at the time. So it was very much, from the top of the bank, this is something we really want to do. And then within the space of six months, all of those customers just decided: “Hey, we're not going to let a third party run an app for us!” So, we got unceremoniously dropped by pretty much all of our customers at once. And the not funny bit is having to let go of a large amount of the team. You get a headline of, like, you're basically a big failure and you have to, you know, sit face-to-face and let go of a bunch of people. But, looking back, it feels obvious that that model would have never worked. But, you know, in the unknowing world of doing that, we thought it would work.
[Ed: 13:39.1]
Another one is like 2017/2018 we made this big announcement that we've flattened the hierarchy of the company and everyone's going to have autonomy. And the reality is [that] a lot of even great employees don't want the level of autonomy that we were giving them. It just seemed like a good idea as young founders. We were working at big corporates before. We didn't get much autonomy, and we just gave people too much and it was very inefficient and actually a very difficult place to work because of that. So yeah, there's a few things we've tried.
[Ed: 13:39.1]
I think don't try and innovate on those core business models that are tried and tested as much as they seem like a nice, utopian idea. Yeah, even employees – they'll talk about full autonomy and then when they finally get that autonomy, they realize that it's almost like they're running the business. And the reason, right, that some people don't start these businesses is [that it’s] very, very difficult. There's a lot of work involved in the whole process.
[Jared 14:38.9]
Interesting with what happened, you know, you talk about some of those platforms, right, that you always see every single day on social media. They hit this with this amount of employees and, I think it's… what's his name? Greg Isenberg? Do you ever see him post? I think that's his name. He always calls out these companies and not, like, I'm always positive and congratulations to all these companies for what they're doing. But a lot of that is vibe.
[Jared: 15:08.0]
Anyone that's tried a lot of those products, it's cheap. You can immediately, you know, put your credit card information in and it's kind of like painting a picture for the people that are building companies over years. It's not painting a complete picture. No. Um, I always look back to the really exciting example of UiPath and how they scaled from essentially just doing consulting and not making that much in revenue for a long time. And then it just seemed like over a 10-year period, it was like they flipped the switch after all these years of learning and just created this massive company. I think that should be more of the norm that we point to than these vibe, you know, revenue success stories. I don't know. That's just my two cents.
[Ed: 15:52.3]
No, definitely. Me and my co-founder have a couple of posts that we will probably make at the end of the year that shows this. It also shows the difference between regions and we had some really great products in the UK, but the way the market works in the UK is very hard to scale. We have, you know, a handful of customers here now that have completely outscaled the entire UK business in the last three months. It’s great in one way but also a little bit painful and so that's the other thing you know being a UK-based company for many years (with with some customers in Australia as well but so a similar market to the UK) and then coming to the US, we would always see these SaaS businesses hit this crazy scale in a short amount of time and I just sat there thinking: “We're terrible at business and we're idiots!” And both of those may be true, but not to the extent that we believed it to be true.
[Ed: 16:47.8]
Yeah. And then you go to pitch a US investor and they point to that as the example. Yeah. And it's like: “I don't know what we're doing here.”
[Jared: 17:00.0]
Have you tried it? You know, I have tried all of these vibe revenue platforms, by the way, and they're good.
[Ed: 17:03.8]
Yeah. But they are not worth $100 million. It doesn't even make sense. Well, you can switch them out tomorrow. Or something else better comes along, it's kind of very easy to switch out. Now, some of these I've used. Cursor and Replit – we use both of them in the company, and we love them just for the record. But, you know, who knows?
[Jared: 17:30.5]
By the way, I am a big fan of Cursor and Replit out of all of the ones out there, and I think they'll start to create more models some of these companies. Yeah. Which will be interesting.
[Jared: 17:40.7]
As we wrap up here, Ed, what's next for Bud Financial that you want to share with us here today?
[Ed: 17:46.4]
Yeah, for us, I guess we're in full execution mode right now. We’re tracking to our profitability point at the end of this year, and we want to scale off of our own backs for a little while. Margins are moving in the right direction. So, that's great.
[Ed: 18:01.3]
And then the next thing we're thinking about is that we're implementing a bunch of AI products into banks. Obviously, banks and financial services are a little bit more risk averse with technology than than other industries. So, of course, the next wave is agentic models. We have been developing some of our own, you know, picking up tools seeing how accurate we can get with those, and then putting them down again as the scale laws and the costs get really high. But I think that's something at the end of the year we're gonna start to reinvest in and it's super exciting.
[Ed: 18:31.3]
That definitely has a lot of potential in financial services, from internally running the bank as well as externally helping people to manage their own money. [Or], like, not even need to manage their own money in the same way that they do today. So that's pretty exciting and we've got all the foundations to make that work.
[Jared: 18:50.7]
Love it. And any events on the horizon?
[Ed: 18:53.2]
Well, I've just done two back-to-back. I just did Fintech Meetup, which was great, and then I went to the Nvidia GTC and we had some customer stories that we're working on. We announced that we're using Nvidia and things like that. So that was pretty cool.
[Ed: 19:08.9]
Myself, I did 180 days in hotels last year and so I will be taking a bit of a break from events for the next two or three months [to] focus on managing the business a little bit better.
[Jared: 19:19.9]
Do you have any advice for me? I was going crazy. I'm going to have 70 days this year. I just started planning all my trips and, I mean, to do 100… that's crazy. I'm even looking at 70 and I'm like: “That's a lot!” Any advice?
[Ed: 19:37.1]
I don't really know. Do you have a family?
[Jared: 19:40.5]
No. It's the only way to make it possible. You wouldn't have one for, you know, potentially very long if that became an every year thing, right?
[Ed: 19:48.5]
Well, I've done that for the last two years and it's just horrendous. I don't really know. I mean, I think the main thing is, you know, try and eat as healthily as possible – that’s the biggest challenge.
[Jared: 19:57.0]
Oh, that's impossible. Especially when every event is in Vegas.
[Ed: 20:02.4]
Yeah. There's no salad bars in Vegas! As much as I would rather have a burger, chips and tacos every night, it adds up.
[Jared: 20:12.9]
You know what one of my favorite quick spots is in Vegas? There's a spot in Vegas that's basically like this walk, you know, like the Chinese walk?
[Ed 20:23.8]
Oh, okay. Yeah.
[Jared: 20:26.2]
But it's like a more healthy version. It's like Chipotle but for a walk.
[Ed: 20:30.9]
Oh, wow. Where's that?
[Jared: 20:33.2]
Uh it's in the mall, the fashion mall.
[Ed: 20:33.2]
Oh, okay.
[Jared: 20:36.2]
Yeah. And I went there way too many times that I care to say on this because I was in Vegas for two weeks.
[Jared: 20:44.5]
I'm sorry I missed you at Fintech Meetup. We'll link up next time. Are you gonna be at Money20/20? I will be in October. Okay. I'll see you there then.
[Ed: 20:51.9]
Every year on my birthday for the last 10 years!
[Jared: 20:56.3]
Okay. All right. That's good. That's a good way to celebrate though, in a way.
[Ed: 20:58.3]
Kind of! Yeah, it's a good event.
[Jared: 21:02.3]
Well, Ed, it's been a real pleasure having you on the show here today. Look forward to continuing the conversation. Please keep us up to date on any announcements and I’m wishing you and the team all the best of luck.
[Ed: 21:09.7]
Thank you so much for your time, Jared.
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