Break the Excel Chains: The Magic of API-based Treasury Tech

Joseph Drambarean:

Welcome to Fintech Corner. I’m Joseph Drambarean and I’m your host and I’m joined by McKenzie Knudson. Did I get that right?

McKenzie Knudson:

You got that right.

Joseph Drambarean:

Awesome. Yes. I’m so glad I was nervous. And we are here live at AFP 2023 and I’m excited about today’s conversation. We’re going to talk a little bit about your experience at Sealaska and how it’s been going, not just with Trovata, but what it’s been like transitioning from what it sounds like was a pretty manual lifestyle, managing the cash and liquidity and what it’s like today. And I thought that before we dig into that, it’d be really great to learn just a little bit more about you and your role and how you find yourself here.

McKenzie Knudson:

Alright. Yeah, I’m happy to be here. This is quite the event that’s going on around us. So my name is Mckenzie Knudson. I work for Sealaska Corporation. I’ve been in treasury or my treasury function for about two years now. I am a former accountant, so I’ve been in accounting for most of my career. So I feel like having an accounting background and pulling that into treasury has been really helpful. And I’ve been at Sealaska for 10 years, but most recently for four. So I came back and have been with Sealaska for four and I’m working with my supervisor Mary to create the treasury function. We’re starting from square one, so we had no treasury role or function working at Sealaska. So that’s been our main goal and Trovata is kind of our step one.

Joseph Drambarean:

Amazing. By the way, I love the accounting background. I actually come from a family of accountants. My brother is an accountant. My mom, she started as an accountant is a CFO today. And I just love that background because it’s a more tactical background when you look at cash and I feel like you bring a different perspective just naturally coming from that background. And I guess to transition to that, what was life like prior to having automation with a platform like Trovata? Was it all pretty manual?

McKenzie Knudson:

We were all manual. So we had a spreadsheet that we would take and roll forward every month and we’d update it daily with cash balances. So we would log into our various portals, put in the new cash balance, and then we would manually look for any decreases in cash or known one-offs to try to project where we’d be. But we were only looking at it for maybe the next week or month. We weren’t looking out into the future and we also were only looking at it at our top corporate level where we own about 30 subsidiaries, so we were letting them all be, they managed their own cash. So we’re trying to now be more of a consolidated view of treasury at Sealaska. And so Excel wasn’t working.

Joseph Drambarean:

Absolutely, and we’ve been on this journey at Trovata for over five years now, and when we first started Excel, we like to think of Excel as our main competitor, if you will. Not really, we love Excel, how could you not love Excel. It gives you so much freedom, but the problem is with that freedom, you also have to own everything. You have to be the database, you have to be the API connection going to the banks and getting the data yourself. And I’m curious, as you went through the journey of discovering a tool like Trovata, but then also having to learn more about, well, how do you get data into a system like Trovata? What was the experience learning about APIs and do you feel like that is a continuous journey and what are some of the benefits that you’ve learned about?

McKenzie Knudson

Yeah. Well, let me give, I just came from a session on cash forecasting where we did a poll and if there was 220 plus people in the room and 71% are still cash forecasting on Excel. So I just think that Excel is always our best friend and it’s hard to pry people away from it, so I don’t, ours was a pretty easy transition partnering with Trovata and getting the bank connections established. And so once we had that and showed, and then when you have the data, once you have that data, you can actually focus on analyzing it and using it versus just compiling it so that eventually then you’ll take a look at what’s going on and then we were able to show our other subsidiaries in accounting how they can use it too. So now everyone, it was a pretty easy transition for us in terms of getting people to disregard the old Excel spreadsheet. Just one day I quit rolling it forward and nobody asked for it and I directed them to Trovata because we had it set up.

Joseph Drambarean:

Great success.

McKenzie Knudson:

So the APIs feel magical. We just can look at our balances every day and there’s a little bit of knowing which banks are connected current day versus previous day, but that’s a learning curve.

Joseph Drambarean:

I think that the word magical is interesting because the best technology is always described in that way. If you think about your iPhone or your Android device and you interact with Google or interact with Apple, Siri or any of these technologies where you just wonder how did it do that? How was it able to take all this complexity, organize it, and then give me something actionable? I think that is something that we strive for obviously at Trovata. And one of the things that I’m curious about is as you were onboarding and you went through the journey of learning about the platform, learning about things that you could do, what has that looked like? Because I think one of the things that we have found, especially walking the floor here at AFP, learning about other solutions, seeing how other people are thinking about it, it seems like there are diverse opinions on how the customer implementation, if you will, should go where Truvada, we have this stance that it’d be really great if the customer could self-service as much as possible, feel like they’re in control of the whole process.

The other side of the house is, well, we could have a team of consultants that play the role of learning how to do all of the various things that you might want to execute on as a team, and then they’re responsible for training your team and all of that. I wonder where do you stand on that continuum, if you will? If the bleeding edge is you do it all yourself and you are equipped to do that, and then the other side of the house is you rely on a team of experts from outside of your organization.

McKenzie Knudson:

Yeah, going through implementations mostly on the ERP side, usually you hire consultants and you lean on them a lot With the Truvada implementation, the nice part was the system is so flexible that we didn’t feel tied into decisions we had made that we couldn’t undo because of working with the Truvada team. Mostly David, he’s here. We’ve been catching up.

Joseph Drambarean:

Shout out David.

McKenzie Knudson:

Yeah, so I wouldn’t, I’d say we were somewhere in the happy medium where we did most of the setup heavily using Trovata’s help and well, we didn’t have any consultants, so it was nice in terms of we knew how the setup, how we wanted it to be, but we made on Trovata to get us there. And then if we didn’t like our end results, the nice part was it’s flexible enough, we were able to just change our strategy and set things up differently because we have the subsidiary structures are set up into different divisions, and so sometimes companies move divisions and the tagging was flexible, searching transactions is flexible, but being able to do it ourselves with Trovata doing all the heavy lifting, it felt like that we connected with the banks via Trovata and we didn’t need IT, which is huge. So that

Joseph Drambarean:

That’s crazy. I think that that’s one thing that we, from the beginning when I first approached this industry, I come from the consumer side and it’s interesting because on the consumer side of the house, there’s no such thing as IT, IT is someone in your family that decides to play that role, but ultimately when you download an app on your mobile device or if you use any website, you just use it and the expectation is you figure it out on this side of the house, especially on the corporate side, it seems that you can’t get anything done without having it involved install something to secure it wherever it might be. So the phrase no IT involved, it’s almost as if it’s an unbelievable phrase. You have to doubt it. The first instinct is to doubt it, but I truly, I think that that’s where we see a lot of the innovation coming is that self-service, the ability to be in control ultimately of if you add another bank, add another bank, no problem, right? It’s not a arduous process where you have to involve other stakeholders and explain to them what’s going on and they have to then implement whatever it is that you would like, and then you have to play a project management role to execute it. And I am curious, does that change the way that you behave moving forward, having that kind of freedom and flexibility?

McKenzie Knudson:

I definitely think so. We’ve been a lot more, I guess looking for ways we can optimize regardless of what bank we’re using, because it feels a little like we’re bank agnostic now that we have Trovata. There is a lift in terms of connecting your payments straight to a bank. That’s never fun. You do need IT for that, but in terms of being able to optimize our current treasury setup and giving people data that they didn’t have, and then so we can see it in a normalized way, it’s been a huge lift, not lift inside of data that we never had. Instead of doing all of this data gathering, we’re accessing it all in Trovata, and it’s been great for even our accounting teams now that they see what’s in there, they’re creating reports. So it’s less of trying to get people on board for a change and more of just showing them how to use the system. And it’s been pretty self-explanatory. Once people click around that they’re off and running and learning instead of manually creating ZBA journal entries at the end of every month, they’re downloading their info out of Trovata, and there’s a lot less manual error in that type of process than

Joseph Drambarean:

Absolutely. I wonder, so you mentioned that search has been an area where you guys have been taking advantage of that, and it’s obviously involved in reporting and all of that. One thing that we think a lot about is the transition from a world in Excel where obviously VLOOKUP is such a powerful tool and it’s such a cornerstone of everything that you do in Excel, the transition then from that, which is a precision thing and a filtering tool to Trovata’s search, which is an open-ended tool. It’s a tool that you can obviously whittle down sets of transactions if you wanted to, but it also allows for you to do complex things like layer tags, one on top of another and have absolutely no limitation when it comes to that. Has there been any, I don’t know, learning curve or limitation in terms of your approach to how search could play a role in not just building the basic cash flows, but expanding the universe, if you will, to even more smaller microcosms of cashflow and how that might garner insight?

McKenzie Knudson:

No. Well, it depends. So all of our subs have been doing this in different ways, and so showing them the abilities of this search tool and how they can refine their searches to get exactly what data they want, because we’ve been working with them to set up their own tags so they know how to use their tagging structure to get the data, but instead of pulling it into Excel, which what they were probably doing before and VLOOKUPs or filtering, it seems like we’re able to pull kind of just add in, not this or that. Using the new tool has been, because I probably use it the most, I get asked questions all the time that are just off the wall. So ad hoc questions, I can answer them so much faster than in a few, in less than an hour when I work it into my schedule versus I’ll get it to you this week. So being able to answer on the fly questions has been a huge improvement from that type of search ability versus having all the data, but trying to whittle it down manually to get what you’re looking for.

Joseph Drambarean:

Speaking of having to answer on the fly questions all the time, kind of being pinging left and right. We launched Trovata AI in June, and it was an accomplishment for sure because we felt like it was years in the making. It took a long time to develop a platform that can do open-ended things in a way that ai, obviously it can answer any question. One thing though has been a curiosity ever since we launched it is how would end users behave? How would they, first of all perceive this technology and is it scary? Is it something that you imagine incorporating into your daily routine? And I guess if that’s the first question is what is the outlook on it? The second question, the follow-up is do you trust it, especially for these types of use cases? My boss just asked me some question that I know it’ll take me an hour to put it together maybe through a couple of searches and a report. Maybe if I just asked Trovata AI, will it come up with the shortcut to that answer? I’m curious, how do you see this? How do you see the progression of generative AI in relation to finance?

McKenzie Knudson:

Yeah, I have high hopes for the ability of it. I have some, not hesitations, but where there’s so much training and learning to be had to feel confident about the data. So I think anything I’m going to be trying it out, reviewing what it gives me and learning from there and along with my coworkers as we learn how to use it, which I’ve sat in on a couple sessions this week so far about ai, and it just seems like everyone’s talking about it. So we got to figure out how we can use it. And I’m happy that we’ll have Trovata to lean on for this help on how we can use the data that’s all in Trovata, because I mean, we have a few years worth of data in there now, so it’ll be really nice to learn how to write the right. I know you have to be very descriptive, so be able to write that descriptive question and get what I’m looking for because like I said, I have high hopes for it.

Joseph Drambarean:

There have been so many challenges to just get used to this new way of thinking, believe it or not, even for myself, transitioning from this search mindset that has just been ingrained from the first time that I used Google decades ago, and having that as just repeat behavior. I know how to write good Google searches that will just get me what I’m looking for. Transitioning now to a new world where that prompt engineering, if you will, just crafting the right phrases that will direct and steer these AI algorithms is so interesting. And if I can share a little bit about what we’ve been seeing watching customers kind of start with the basics of can you just find a transaction for me, almost like a needle in the haystack. I know what I’m looking for, it’s this type of transaction, just go find it to then the most complex question that I’ve ever seen is, can you provide me a derivative hedging strategy for my Euro accounts?

And it’s like, what? You’re going to trust? That’s the system to come up with that. And obviously there’s a range of mastery from the most basic of let’s find this thing to open-ended, come up, a fully fledged solution, a strategy that is multi-step. I think that everyone can play somewhere in the middle of there. And some of the most fascinating use cases that I’ve seen have been ones that are conversational. You start with a question and then you just keep digging. You go further and further down the rabbit hole until you get to a conclusion of some kind. I’m curious, where do you see your team and kind of your use of this technology going forward? Do you think that there will ever be a world where an assistant like this can almost play a role in your team, almost be part of the team?

McKenzie Knudson:

Yeah, I think for sure it’s going to be one of those crawl walk runs situations in terms of teaching the team, well, teaching all of us. I don’t know if we have anyone in house who’s all that familiar with how to use it, what it could do for us. But once we figure that out, conceptualizing, to me, I see it with the cash forecasting right now. One of the big struggles is building cash forecasts at our subsidiary levels for companies who, they’re all different. They all have different inflows and outflows and business trends helping us maybe create our base forecasts and then using Truvada to really narrow it down and getting a better pulse on instead of looking at things. We have a pretty wide range of what we think is okay in terms of being on the forecast. I think we’ll be able to really narrow it down. And I don’t know how we’re going to do that, because I guess that’s why I’m here to learn about AI and how we’re going to implement that, but it feels like we’re going to be able to use it somehow. And I feel like in cash forecasting and using all of the data we have to create a more accurate cash forecast.

Joseph Drambarean:

Last question, and it’s okay if the answer to this is, I don’t know, but we’re here in a dreamland, if you will, everyone is pitching their thing and trying to come up with what the future will look like. What if you put the product hat on your head and you kind of wave your magic wand? What feature or solution or opportunity is there to improve your workflow?

McKenzie Knudson:

I think. Oh wow. Well, just more time in the day. No, I’m just kidding. So yeah, we have, we’re really at the beginning of creating our actual treasury framework, so I don’t know what would I want.

Joseph Drambarean:

We’ll check in next year then.

McKenzie Knudson:

Yeah, better analysis of a way to analyze our numbers. Take all sorts of time, I guess KPIs or looking at cash turns, just, I’m not really sure what I want, but I know that as we get things set up, we’re meeting in a month or so to really narrow down what our expectations are for our overall view. So I feel like next year I’ll have a better answer.

Joseph Drambarean:

Awesome. Well, Mackenzie, thank you so much for joining the show. Hope you enjoy the rest of your time at AFP and really appreciate your time.

McKenzie Knudson:

Thank you. This was great