We’re excited to add the treasury track to HighRadius. The Radiance conferences that we have each year, will just keep growing. So we like to help to make it very informative for you in a variety of different ways. Today, joining me here are a variety of different gentlemen who have been in treasury for quite a while, many of whom I’ve known for more years than probably all of us would like to count. But what we’ve seen are great changes in Treasury over the last 10-20 years.
And change is happening even more rapidly now than ever before. So I’d like to start off by asking each one of our panelists to talk about what do you think has been the greatest change in treasuries over, let’s say, the last five years? And what do you think is going to be the greatest change in the next five years?
[01:04] Russell Hoffman:
So I think the perspective that I’ve taken over the last five years is that the treasury has been more business-focused, has become more strategic, and we use that word quite a lot- ‘strategic.’ What does that mean? In the context that I see it, many of my clients, it’s getting away from some of the day to day treasury functions. So really doing away with having to process payments, having to do transactional things, but rather focus on things that add value not only to the CEO, the CFO but also to the business.
And so that’s getting involved in things like working capital strategy, greater funding and liquidity strategies, more robust foreign exchange, interest rate, risk management strategies, things that again ultimately add value. This has been a road that has been gone down by many treasuries. It’s evolving. But I think there have been great strides in that change in the mindset of treasury functions over the last five years. And as we go to the next five years, we’re looking to evolve even more. And I think we’ll probably talk a lot, today, about technology and how treasury will evolve in the next few years, specifically with technology as the driver, but also reacting to things that are going on in the world, whether that be geopolitical or regulatory-driven.
[02:32] Jeff Diorio:
Well, thank you. We’re going to have a hard time not repeating each other. So we’re taking a different tack. So for the last five years, I’ve seen treasuries kind of come out of the doldrums after the recession was kind of hit pretty hard. A lot of treasure wanted to do things and it did not have the budget to do them. And recently, I’ve seen a lot of loose budgets become available. Treasurers of all talk to me about forecasting and improving that word capital, definitely one of the areas I’m seeing a lot of work in. And so to continue the theme of technology, I see a lot of organizations looking for how to do more without growing their staff. And the way to do that is automation, to get people out of the weeds and gathering data and compiling it so that they can add value to the organization. And there’s a lot of really cool technology out there.
So, of course. But what I’m seeing is there is a stronger focus on efficiency and controls, efficiencies so that my people can do more within the hours that I have for them right there. They’re MBAs. They’re very smart people. I want them to do very strategic things for the organization and then control. A lot of automation these days is going towards avoiding bad stuff happening. And AP and treasury are the epicenter of bad stuff happening because the bad people know you were the ones that can send the money and so they’re coming after you. And so there are ways to leverage technology to control their business. That’s kind of my vision for what’s going to happen.
[03:39] Craig Jeffery:
Treasury has all strategic groups view of the treasury being a business partner- how to not only provide the capital liquidity safely, etc. but how do you support the business. That’s always been the position of those treasuries and treasury groups that take a more strategic role versus one that’s more vendor oriented. Oh, I think that your bank service. I’m separate and distinct. So that’s always been the case. In the last five years, I think I’ve seen more trends towards supporting the business. And part of that is the end-to-end view. They are looking more comprehensively across the cash conversion cycle. We’ve talked about how we’re going to have a lot in the last 15 years. Working capital has been near the top of the list of what people are doing, but more people are getting involved. Treasury being more involved in AR and AP all the way up the credit cycle.
So that involved an organization that is very healthy and very fruitful. I think another area that’s taking place on the control fund is the level of cyber-attacks and sophistication of criminals going after you. As Jeff mentioned, the bad guys getting yields that are so much greater. They’re much more patient than the dumb criminals of old. And this is requiring a lockdown on the whole payment process, not just data, but the payment process. So there’s a technology at the end of that. And then on the human side of that, those that are locking that down, it is useful. And then the final point. So we don’t take too much more time after this. Treasury has become much more risk management-focused, not just with, you know, different types of financial instruments, but in conjunction with becoming more global. Almost all organizations are experiencing globalization in their supply chains where they’re operating. It is more global. That creates more complexity. And so that’s driving them to have a risk. But they’re also looking at operationally more. And so how do we reduce errors in business processes? Another aspect of that.
[06:45] Ernie Humphrey:
Yeah, I would say take the five years, three years before the past few years, I think we talk about the evolving role of the treasurer. I think it’s been aspirational. What we’d like to do, what we talk about doing, have we been doing it? No. In the last couple of years, I think technology has enabled us to start earning that strategic step at the table. And I think we’re starting to see. I’ve worked with HighRadius for about four years and they’ve been really game-changing in terms of accounts receivable technology. I have been really involved in AP technology. So for me, I’m starting to see an evolution to AP and AR coming back up the treasury. And my next five to 10 years are aspirational. I want the treasury to take more control of the cash conversion cycle. I want to teach everyone to be more social, more collaborative, come out of their shells and earn that strategic seat at the table. So, yeah, maybe someone in McDonald’s has a seat at the table, but, you know, some other folks don’t. So I think we’ve been doing a lot of talks. It’s time to take some action and it’s time for us to actually lead across the enterprise. And technology will help us do that, which I talked about this morning.
[00:07:54] Jeff Diorio:
And I did not pay these guys to talk about the cash conversion cycle because of speaking about that tomorrow morning. So if you want to know about it, just come back.
All right. Judges do advertising for the next coming sessions. You know, there was some consistency there in your responses around controls, efficiencies, technology, and the control aspect, it’s interesting. You know, here at HighRadius, we’re definitely focused on artificial intelligence. How do you think artificial intelligence specifically can be applied to other areas? We’re focused on cash forecasting in AP technology right now. But where else can you see it being used in the treasury? Whoever wants to jump in, that would have to go in order.
[08:38] Jeff Diorio:
We started with earnings.
[08:42] Ernie Humphrey:
Actually, I was just speaking this morning with someone of treasury HighRadius folks on the floor and we talked about how we might start to see folks doing their borrowing decisions as we’re able to forecast out. So the timing of our borrowing decisions and also warnings about our debt covenants. And so how do we leverage all the capital that we have access to? So that’s an area that I think might be gaining some attraction at some point.
[09:14] Craig Jeffrey:
You know, artificial intelligence has a number of roles besides the hype and the excitement. You know, besides what you’ve mentioned, a couple of things certainly come to mind that are in process. Companies are using it. One is what’s AI and machine learning? It is good for determining what’s out of the ordinary and what’s anomalous. Where does that come into play? Where does it matter? Well, that matters with fraud detection. It matters with aero detection, quality control. Those are a couple of things that I am sure AI and machine learning are very excellent. So, yes, we have a payment process that can monitor, detect some type of anomalous activity within the stop that it can call into play, you know, payment introduction and pull those items out to someone else who’s doing something to the system.
It can stop less once a month. Treasury front more on the data front. It’s not an actual creation of data, but it also can be used for quality control for transactions. What is happening? It can be traded by comparing a banking task. You put all these things in there, reflect something that falls outside the norm. Is that a quality issue or is it a control issue? And so putting it into place in those areas could help. But in forecasting, there’s a lot of examples of how companies are realizing the solid benefits from AI today.
[10:38] Jeff Diorio:
Proactively, we’re seeing in forecasting because I gave a speech on tax bill last year and I started it with, “I absolutely hate forecasting.” There’s nothing I hate more from a financial point of view than forecasting. I had a job once where I had forecasts every week. And then when I spend more time doing work and succeeding also past my forecasts and you are getting angry at me for saying that. But AI can help you with forecasting. And that’s like, you know, everybody wants help with forecasting. So that might impress the market.
[11:19] Russel Hoffman:
I would add that I think we’ve still got a long way to go in AR, specifically in the treasury. I think we see many use cases within finance- AP and AOL, and that’s sort of the evolution of AR. There are some very sophisticated corporate treasuries that have the skill sets and the analysts that are able to build algorithms and do things.
And we see a little bit of that in foreign exchange, risk management, and exception top analysis. But I think that the world within treasuries is still evolving, that’s got a long way to go. Treasury can certainly benefit from the forecasting aspect that’s taking place more broadly in the company. But again, I think I want to temper the half on AR just a little bit.
[12:06] Craig Jeffrey:
I’m going to comment on a note. I mean, you know, treasury versus finance. I think that’s a really interesting part of external audits. That’s not a great business to be in America. They’re all putting AI to do a lot of things at a massive level. That’s a big change. That’s a very different story for the treasury. Treasury has never been high with staff. And over the last seven years, the treasury has had systematic increases, not dramatic, but systematic slow growth. But they still can move up. We can leverage that technology to do much more. It’s always needed to be done. And that’s a much better environment, I think, to be in a place where AI is reducing.
I think there’s a clear difference between automation that helps do really repetitive tasks. So that’s kind of an easy application of it. But beyond that, moving into where there are clear decisions that must be made as a result of the data that you have, like if you have a policy, if it’s easy to apply that policy to the data, that’s also something that can be automated, particularly with A.I.
So don’t you see applications not just around, maybe broad and looking for anomalies, but maybe in hedging were given this policy, the fact that we have whatever the exposure level is, these are the recommendations of the trades and policies that should be made. These are the recommendations of investment and debt decisions should be made. Given the data that you have, not that it necessarily transacts for you, although that’s possible, too, but ideally kind of decision support. Do you see other applications of that throughout the treasury?
[14:04] Russel Hoffman:
I think that’s where it’s certainly going in terms of those applications. But again, when we talk about machine learning, it’s really AI’s ability to learn from exceptions in the past and create smarter decision making. I think most of what we see is gained more of the RPA and automation. That’s not quite necessarily the learning aspect yet. And that’s evolving and developing. And again, I’ve seen a few cases, but those applications, I think will become much more popular in the years to come.
So you kind of applied a little bit of drawback saying, “Don’t get too excited by how fast it might be moving.” You know, for all those people that are here working in the treasury. What does this mean to them as we talk about, you know, perhaps you mentioned, in auditing, they should kind of fear for their job, given that so many of those things can be fully automated. What does it mean for people in the treasury? What types of tasks are they doing right now that are probably going to be entirely eliminated?
And more importantly, then, what can they do to prepare for the future? What kinds of skills do you need now? What kind of education should they be getting right now? How do they prepare for a world where some of these things can be automated?
[15:29] Jeff Diorio:
So I did a study last year on how satisfied treasurers were with their technology, and by and large, the answers were, “Yeah, it kind of works.” What we found was the best treasuries that were getting the best value from their technology had a whole bunch of really smart finance people who understood how to use technology. They were able to apply the technology. And if I go back to my years as head of client services in certain terms, I always found that the very best uses of our technology had people that really understood how to use it.
And so, I see in hiring decisions these days, people come to me and they say, “We’re looking for somebody. Do you know anyone?” They’re looking for someone who has a finance background and a technology background. So they need to have both. And if you’re trying to stay valuable going forward, you’ve got to find ways to be the person who knows how to turn the knobs on the technology.
[16:29] Craig Jeffrey:
Now, I think that the trace of your point on some thoughts and hearing my words come back, I need to fear the AI, I guess the aspect or perspective is that when you look at what AI can do. Or what Robotic Process Automation can do to your automation, we need to look and say, “What am I doing? What am I good at? Where is this taking us and how can I fit in as I go forward? Can I leverage technology? Can I guide my team? Can I do these types of things and take advantage of the chain that we feel is good for us? Because otherwise if you’re like, “Oh, I really like the manual clean and through keying in the information or more sophisticated population of the database.” That’s nothing. I like doing that. And when that job goes away because you automatically go somewhere else. What’s going to happen? You’re going to use Robotic Process Automation, robots to replace that.
And so if that’s what you want to do, you’ve got to say, “Ok, when my career is going to be chased out of the job. So sequentially as they put in these thoughts. But maybe that’s what you want to do. But I think it’s like I think about what I am going to do. Do I need to learn skills to control and program those things or find something else? How do I leverage my unique intellectual capacity?
[17:52] Ernie Humphrey:
I spoke about this morning. Those of you who were in session this morning. So you really got to look at what are the skills that you need to define your career success and then what are the skills you need to obtain. And so when I talk to folks that are treasury recruiters, I’m glad to hear it’s more about leadership, leading projects, collaborating, having an appetite to learn. And so hopefully with automation, you’ll have more time to do that. But like Craig was saying, you need to get your digital skills up to speed. You may not be an expert, but you might want to learn a little bit about data science. I don’t think that’s a bad idea. And learn how to add more value across the enterprise. So FP&A talks a lot about this. I don’t think we’re there yet. We should be more involved in FP&A. Why do we have a different cash forecast in FP&A than in the treasury?
So we can be more involved with FP&A and helping people understand at the departmental level, what drives productivity and helping them build those relationships and understanding speaking the language of finance and analytics. And so we need to help them measure the right things, understand how to use metrics. And then for the CFO, his job, like it or not, as to impact performance across the enterprise. So how do we become more valuable to the CFO? At the end of the day, the best treasurer is going to mitigate the time the CFO spends on non-valuable activities. You want to free the CFO to be the chief strategy officer.
We have things to do, but we can start to take some of the strategic stuff off the CFO’s plate and then we can position ourselves to elevate the treasurer. I think with flexibility, you can learn whatever you can, whatever is coming out- new technology, even if it’s whatever the next LinkedIn thing is, learning the social things have an appetite to learn and engage people at your company and learn what they do and what their challenges are and learn how you can help them and you’ll build your brand within your company and it might take you outside of treasury, but so be it. I’m not in the treasury. I’m not a stand up comic with the orange suit on. So it all works out.
I think that’s very true, Ernie, that being a partner to the business means knowing the business. All right. Getting out and getting involved in what your company does, but also being able to interpret data. I mean, right now we’re definitely in a data phase. Every company is looking for ways to harness data better, but the people who are most valuable are the ones who can help interpret what this data is telling us. What decisions should we make differently? How are we going to use that data? Thank you for providing your thoughts and insights. Each one of these gentlemen is here for today. You can reach out to them. You can check out their websites or some of the things that they have here are the materials that they’re providing. There are webinars. There are podcasts. There are lots of ways to access a lot more information about the treasury so that you can continue to tool yourself for the present and the future.
Thank you for joining us today. Have a great time.
[00:03] Anchor: We're excited to add the treasury track to HighRadius. The Radiance conferences that we have each year, will just keep growing. So we like to help to make it very informative for you in a variety of different ways. Today, joining me here are a variety of different gentlemen who have been in treasury for quite a while, many of whom I've known for more years than probably all of us would like to count. But what we've seen are great changes in Treasury over the last 10-20 years. [00:40] Anchor: And change is happening even more rapidly now than ever before. So I'd like to start off by asking each one of our panelists to talk about what do you think has been the greatest change in treasuries over, let's say, the last five years? And what do you think is going to be the greatest change in the next five years? [01:04] Russell Hoffman: So I think the perspective that I've taken over the last five years is that the treasury has been more business-focused, has become more strategic, and we use that word quite a lot- ‘strategic.’ What does that mean? In the context that…
A panel of treasury experts get together to discuss the treasury transformation kickstarted by Artificial Intelligence across diverse treasury functions such as fraud management, investments and risk management, forecasting, etc. and how this radical shift the approach towards processes, technology and skills.
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