Tracey:
All right, good morning. Let’s continue on talking about Treasury and this one, we’re going to talk more specifically about the Treasury modules that we offer and what they are designed to do, and how they can help. So why cash forecasting? Why is that kind of our entry into the Treasury space? What exactly is it that we offer? We’ll talk about cash forecasting and cash management and then, of course, take your questions. So why cash forecasting? And the answer is this cash forecasting has been the number one priority of Treasury’s growing in priority for years, and you’ve seen it even since, like 2005, increasing even to pre-pandemic Treasury was the number one I’m sorry forecasting was the number one priority of Treasuries. We’ve seen it on multiple surveys from a variety of different entities, and at the very same time, Treasury management systems teams have been rising in usage across companies, in all different sectors from the very, very large, which have had them for many years to smaller and mid-market companies. But yet, at the very same time, almost every company, about 95 percent of them will tell you that they still use Excel during their cash forecasting process, even if it’s in conjunction with something else or with nothing else at all. Just Excel. So we’ve seen technology rising in the space, but cash forecasting has still risen to the number one spot, and even more so after the pandemic.
So that says that there is a problem that has been unsolved. At the very same time, we had begun using AI to forecast within our collections module where we’re forecasting air. So it was a natural extension to us to move this into the Treasury market, to build it out further across multiple categories to build a new UI that’s directly related and for Treasury. But sitting on top of our existing technology, our existing experience that we’ve been gaining on the order to cash side. So that’s why cash forecasting, oh, somehow these slides ended up in the wrong order. So anyway, so what we offer are two modules right now. Cash forecasting and cash management. So I’m going to first talk about the cash forecasting cloud specifically about the new version, a major upgrade that is coming out in November, where we have added and are changing a lot of what the system can do, particularly in those boxes that we’ve marked in green. So essentially on the far left, you can see we can take data from any number of different sources. So that might be from your banks, from your teams if you have one from maybe an accounting system or any system or some kind of forward-looking projection that may be some other departments are creating that will incorporate some of the things that your company is doing, specifically where historical data is not going to reflect that.
Like if you’ve got acquisitions coming or some major initiative you have going on, that’s going to create a lot of growth. Well, just looking at historical data alone is not going to show that expected new trajectory. So pulling information from a variety of different sources makes the difference, and we can do so via API or SFTP, or even manually upload through the user interface. And then some of those new things that are in green are this added ability of the connected workspaces where you can share information and gather information from a variety of different sources, all in an Excel-like spreadsheet that will pull information into the system as another means of getting data into the system. Defining your own models, not just using those that are data science this team creates, so it gives added flexibility to users. It also will help us move downmarket for those companies that maybe don’t have as much or any I.T. support. You can do so much more on your own as just a regular Treasury personnel right through the user interface. So all of that so that the system then will generate and regenerate forecasts on-demand or as needed, and then provide that and automatically consolidate your forecast from that low-level forecast, maybe by a company or country or currency, and consolidate that all into a global forecast.
Very accurate doing automatic variance analysis as well. So the idea is that we are addressing a variety of different challenges, like them being error prone or very manual in that excel kind of format where you might have inaccurate forecast or limited visibility, or sometimes just for a very short period of time where having a large amounts of data is a problem. You know, Excel is not a database, so it’s not necessarily giving you the trending in the views that you need from your data historically. So that’s these are some of the challenges that we’re really working harder to address, particularly with many of the new features that are coming in this next release, where the key features are that you can automatically input and validate data even through the user interface or with some prebuilt interfaces. With the common ERPs, you can choose between ready to use models or the AI models, or do a lot of heuristic modeling of your own. Some companies tell us what forecast is accurate. I just need it to be more automated so we can help address that challenge, as well as the one for those companies that say my forecast isn’t accurate at all.
Like the gentleman I talked about a minute ago, who says he just puts numbers on the wall and throws darts at it. With our software, you’re able to put in place a real process around it, an accurate process that creates a forecast for a longer duration so that you can have confidence in the forecast that you have and see the results of that within the system. So the idea is that we are making this cash forecasting easier for not just large corporates, but mid-sized companies as well more self-service options, more ability to be in control and to understand your forecast and the variances and the data behind it. Putting all of that power in your hands so that you can manage these large amounts of data and then get the accurate forecast that you need. So I showed you kind of live demo, what you’re getting are screams and views that are designed to provide more business intelligence, more intelligence from the executive perspective, as well as for that level user who really wants to see more of the details side by side in a spreadsheet like format. So not only do we have the major release of cash forecasting coming up, but of cash management as well.
Peter:
Thanks, Tracey. So I’d like to talk about our cash management offering, which is coming out next month. At the moment, we have very basic cash management pulling in balances, et cetera. But what we will do next month is extend it out to a full cash management system. So again, like in cash forecasting. Cash management requires the ingress of data from different places. So big files, bank statements, files, etc. either by API or manually importing. And then once you get it into the system, you need to be able to cash position. You need to be able to see global balances. You need to be able to see into company activity with LIBOR pools, et cetera. You need to be able to reconcile. You need to be able to make forecasting decisions, and you need to be able to compare the bank actuals with your view of the world. And then lastly, you need to be able to report. So these are the challenges that our October release will be addressing. Other items coming in the future will be the ability to create cash accounting and then further on down the track to make payments. But on the bank connectivity side, we already in our integrated receivables products have the ability to bring in bank files that’s required for the cash collection module. So we have that ability.
We already utilize it. We can bring in any type of file SFTP API or manually entered. So obviously, you know, there’s a lot of automation benefits there. No manual entering of balances on the global cash visibility side. We can define bank accounts. Bank accounts belong at banks. They are owned by entities and non in countries regions, they have currencies. So when we slice and dice all our bank balances, we can see them how we would like to. We can take balances either manually entered, we can take opening available, we can take ledger balances, track float, etc. all via our bank statement imports and see that within the application. Then we have a positioning feature, so you’ll be able to design your own cash positions worksheets. So whether you want to see things by activity code out, by time, by bank, by accounts, et cetera, you’ll be able to design all these. View them on the fly and see some screenshots in a second view in any currency. You’ll be able to drag and drop funds, move funds from one account to another operator, and pull clear funds from multiple accounts into one account or within the one screen. And the ease of use is the great feature. Here you’ll be able to link back to accounts, find details out about balances, et cetera.
We have tried a reconciliation, so you’ll be able to create tagging rules. Firstly, to tag your bank actuals for cash flow categories and the cash forecasting module, you’ll be able to create cash transactions for Zeba sweeps the bank activity that we may not know about in the Treasury system, but the bank provides us with, and then we’ll be able to reconcile those against bank actuals and then we’ll be able to match up bank actuals with our own view of Treasury activity, either one to one, many to many, etc. So all automated via very complex rule set. So this is all coming in October. We’re just currently working on bank account signatory management, so obviously we have bank accounts. You can open and close them. You can track details about the type of account, lockbox investment, concentration account, master account, etc. We are just working on signatory management, so you’ll be able to attach documents attached signatories to accounts. Bulk update them when people get promoted or move out of the company, etc. So manage all the details of your signatories. You’ll be able to use that also to track perhaps board reporting signatories. People often like to do that and with signatory details. So all this is a data repository. So along with all our millions of lines of invoice information, our bank actuels, et cetera, the ability to store and tie all that together, viewer, etc.
All in a single repository. And then in our cash position, you’ll be able to create target balances, minimum transfer amounts between accounts. So as well as seeing your position, you’ll see be able to see what you need to do and then make your investment and borrowing decisions. And next year, we will start to integrate money markets. Funds and the ability to to make investment and borrowing decisions or actions from within the system. Ok? Some quick looks at some of the screens, so this is our cash position. So you see here, I’m looking out in time with my columns. Sorry, lot times I’m looking at different bank accounts in each of the columns. I’ve got opening balances and then on the left hand side and in the rows, I have all my activity codes. So opening balances, Treasury activity and on Treasury activity down the bottom. My final ending balance, you can see it’s kind of easy to read negative numbers in red, so forth up the top, just above all the numbers. There’s the ability to drag and drop. See things in every currency change. My view on the fly and the top left is a template field. You can change to another view on the fly.
You can drag money from one account to another. You can create a cash transaction. You can link back to the account. So all within this one screen, you can kind of manage your cash activity, then our cash transactions here, so you’ll be able to see your cash transactions. The nice thing here is that if you do transfers, we will create both sides of the transfer at once. We can also create what we call a four legged CTA. So if you want to track cash into company cash movements with intercompany accounts, you can create mirrored company activity as well as your cash transfers, all with a single screen entry. So very efficient in terms of time and usage. So as Tracey mentioned, you know, where are we on our time frame? So next month we’ll have our cash management module that I’ve just covered. In November, we’ll have our new cash forecasting module. So if you’re going on to AFP Book of Time now to see all this because there’ll be live demos of the new modules then and next year, we will start on financial instruments. So obviously we start simple with money market funds. Keep working capital instruments, credit lines, etc. And over time, we’ll move further into the financial instruments. So we’re making rapid progress towards building out a TMS. Ok. Questions.
Audience Member:
Thank you both. Questions on AI for forecasting or the cash management that’s coming in the new release.
Audience Member:
So the cash forecasting model you get said you actually have it coming to you in November. So what do you have currently?
Tracey:
Currently, it’s already in I cash forecasting module, but it does not have what I’ll call self-service capabilities. So right now, our data sciences team builds the models, and that’s the the forecast that you get with the addition of what’s coming out in November. It allows you to take control over some of the categories where you might like to build some of your own models, maybe still using AI for particular categories, but maybe you own certain categories, and it’s just to give greater flexibility above and beyond what there is right now.
Peter:
Yeah, so so to add to that, our data science team builds the models based on your data that you provide us. And then if you you can add to that, you can override manual entries. That’s in our existing product. We’re going to provide a third level of kind of modelling which you will control and it will be very excel driven. So if you want to pull in hundreds of thousands of invoices and then categorize them in the pivot table by customer and calculate average days outstanding by customer, you can do so in our excel like sheets and then by formulas. Just like you would in Excel. You can then create your own forecasts based on your own excel formulas rather than our data science models. And that will be another way that should be able to build forecasts. Some answer your question.
Audience Member:
My question. It looks like you’re building a full fledged teams based on the phased approach. And one thing that’s obviously missing right now is that management capability inside of the system is that what you’re planning to include in 2022 when you talk about financial instruments or that’s a separate effort for that.
Peter:
Yes, that’s exactly what we plan to do. And obviously, we will start with the working capital debt, the short term debt, you know, the the credit lines and revolving facilities, etc. Keep borrowing or on the investment side, you know, investing in Treasury paper or CPE or money market funds rather than complex interest rate derivatives or capital markets instruments. So we’ll start with the working capital instruments first and then gradually extend out.
Audience Member:
So for customers that have complex debt portfolio currently, which is either outside of the Treasury management system or in other softwares, you planning to kind of just gradually maybe you targeting cash management one hundred percent and then integrating debt right later on?
Peter:
Yes, though in the interim, right now, you’ll be able to import the flows relating to that long term debt into our cash forecasting module or cash management module for positioning purposes or forecasting purposes. So you be able to do that, what you won’t be able to do is book the, you know, the five year bond and have the accrual accounting and the accretion and amortization of discounts and things like that.
Tracey:
So the goal is definitely to grow in those directions, but it’s important to keep in mind that all the modules can be standalone, if desired. So for companies that maybe already have a TMS or have some type of technology, you might just choose to add on the cash forecasting module and to kind of plug that one hole. But for a company that maybe it’s still doing everything in Excel, then choosing to add on these other modules as they become available can be a very good option.
Audience Member:
a question on interfaces to make the cash forecasting work, you have to go out to R and AP. Typically that information’s in SAP or Oracle or some other general ledger. Do you have plug-and-play interfaces so that you can make it very easy to get a hold of that information, right?
Tracey:
Just like the other lady from this morning, I’ll make sure I pay you later on. That was a great question because I do have a great answer, which is that yes, we have very standard extractor tools with all of the big ERPs and then build them on-demand with some of the smaller ones. So for SAP or Oracle NetSuite, Microsoft Dynamics and I’m missing one sage, I think we’ve got standard interfaces so it can make that extraction process and it part of that extremely fast and easy.
Audience Member:
I know I have a question, kind of. I don’t know. I’m dense on the learning side, right? When you’re doing the AI forecasting models or using all of the customer data, like for a company or is it just specific to them? Does it learn what their data or is it learning with all the data from all your customers?
Tracey:
So typically the data from that particular client, we’re usually starting with about two to three years of their historical average, but our historical data. But over time, I would imagine that there will be things that we continue to learn about a particular industry or an area where they’ll be learnings from other clients. That might very well apply to where at some point we might say, Well, we’ve got this CPG model, and let’s use that one first and let’s see how and what kind of results that’s producing and then tweak it as necessary client by client. So I would think that there will come a point when we will have more kind of, let’s call them industry specific models that will be able to start with and then tweak from there.
Audience Member:
Ok, thank you. I’ll stop there. Great suit.
Audience Member:
So it’s kind of a two part question, one being given that there’s a lot of alternatives out there, different TMS is both cloud based and otherwise. While you’re kind of building the the capabilities for for a Senate, TMS is the focus, at least in the near future or long term, primarily to sort of augment existing TMS capability to bring in AI into sort of dumb TMS, yes or no. And then essentially, is there a specific revenue or market segment that you’re focused on or how would you look at it?
Peter:
Yeah. So Tom saw that Tracy will add to it is our background is in integrated receivables A/P. So, you know, we’re really coming to this in the forecasting side and AI signed that is the value. Add our distinguishing feature, though we’ve bought over the last two years and we’ll continue to bring, in fact, we’re extending our kind of differentiation in that area. Cash management is part of that because you need the actuals to be able to compare to forecast to see how you want. And so we’re building that out out in terms of our and we’re going to keep going, but we’re kind of building out from our existing strengths. Our target market is not the TMS, so not the big sun guard product or the office products or whatever. Obviously, you know, we’re starting from a certain point and you can’t just jump there. Our target market is really clients who want specialist forecasting or who use Excel for cash management forecasting. At the moment, that’s really our target market. But in the forecasting, we can bring a lot of value to very large companies and we do right now because of the specifics around AI.
Tracey:
The other thing I would add to that is that the the new thing and why enter even into the TMS space at all is that we’re doing so with this new tech stack. So as you heard, Sashi talk about autonomous software is where we believe things are going and you can’t just grow into that from an old tech stack. And so, you know, every 10 to 20 years, there’s this kind of technology revolution. And it’s kind of how when you think about Salesforce or something that came along kind of displaced, everything that was there before it, same thing will continue to happen unless of vendors really able to keep up with the latest technologies. So when you look at most of the Treasury management systems that are out there, even the cloud based ones have been around since the first one started coming on the scene in 2004 and 2005. Really, adoption really picked up around 2010, but they’re not made for big data. They’re not made, and that’s why people don’t use their cash forecasting modules. Almost every system out there has one, but yet people are still doing it on the side and excel doing their forecasting there and then maybe using their TMS just to consolidate some data. So there is a market for cash forecasting, without a doubt. And then, as Peter said, we can just pick up the people who haven’t adopted any kind of system when it comes to the the other kind of more common modules. But in time, I would expect that will begin to replace and some of those will die out. Just as you know, I CMS has died and SRT and all the names. If you’re old enough, you’ve used all these other platforms many, many years ago.
Peter:
And if you think about cash management, there’s probably, well, there are many interesting opportunities for AI and cash management. So, for example, exception management in the reconciliation process, if you can build AI so so most people have to get their exceptions on their bank reconciliation and figure out what’s going on. And that takes a lot of time to do that. But if you can bring AI to suggest or create rules to automate that, you’re going to create value for clients with cash positioning. There’s a lot of concentrating. So typically in the US, you can’t concentrate across banks, they won’t sweep for you. You’ve got to do it yourself each day. So there’s a lot of kind of AI. You could apply there and start to automate the positioning process, and that will vary from client to client. But some clients may be able to automate a lot of that process the investment management process, finding out what are the best rates and then automatically investing money. That’s true. So there’s a lot of possibilities,
Tracey:
Lots of opportunity for AI within Treasury, around hedge management payments, fraud as he mentioned, repatriation investment allocation. There’s lots of different areas where we can see AI being applied so as we build out the system. Our goal is not just to build it in an ordinary way, but also look for some of the applications for this new technology to make a difference in spaces that have long been the same.
Audience Member:
So if there are no other questions, thank you guys very much.
