Valerio Trinchi:
Thank you. Good afternoon. I mean, sounds like a familiar little family reunion I told to the HighRadius friends, your bold to try to organize something in person these days because you never know. But I mean, I was surprised to see some attendance, I was expecting less. But thank you for being here. We’ll keep this colloquial given that we are just among friends. I mean, I think I’ve been told we have roughly 20 minutes for me to speak and 10 minutes to get questions. So I’ll try to stick with that then they gonna me. I mean, as I was introduced, and part of the why I lead the Treasury technology offering and the US out of New York.
Being in Treasury, I mean, most of my areas as a practitioner, and seven years in consulting. And today, I mean, we’re gonna call it a little bit about what are the transformation opportunities that technology are enabling these days? So given that is a really short section yours, I organize it in like in three main sections? I mean, what is it? Can we overlook the transformation opportunity? I mean, or should we? Are we force in order to stay competitive to consider what’s out there? So that’s one angle, the other angle, okay. If I need to look, what’s out there, what is out there? And then how do I get started? And then I mean, we can close that with some question. So do we have the luxury today as an organization not to evolve not to look at what new technologies are offering and stick with our like, legacy workflow? I think the answer is probably not. And why is that? Because I mean, the requirement for Treasury, if we look at the last probably 20 30 40 years, are more or less the same. But how do we get to the output? And how do we organize our workflow and process are, is changing, because technology allows us to do things better. And so if you think about them in our competitive position in the market, I mean, what really matters is not just how we are doing things, but our competitors are doing things.
And so as they are evolving their way of doing things for us to remain relevant, not just externally, but possibly even internally is to consider, okay, should we revisit our workflows? Can we do and get to our output faster and better. And so if you think about our things in our organization change, for example, an acquisition, for example, for example, regulatory change, and libraries, changing new regulation, ask within the organization for more rationalization and acquisition that requires us to revisit any in house banks, bank structure, you name it. So if before we have the luxury to do we really need to invest in technology, do we really, really need to revisit our we do things? I think right now, it’s it’s a must, in a way, in that sense, I mean, if I’m trying, I tried to summarize here, like and simplify from a treasury perspective, I mean, what are the challenge from a cash perfect perspective that the Office of the CEO CFO is really looking at? And so I summarize it. In this, we may are your you didn’t include something else, but just for the sake of argument this afternoon? Let’s say that this is yet. So if you look at the cash positioning, forecasting, reporting allocation, okay. The question becomes, do I know that I have pain points? Do I? Am I taking too much time? Do I really consider my output reliable? And how much for me and my team are making to get to that output? And so if for under these lands, the question becomes, in my cache positioning, is it to manual?
Is it prone to error? Is the information coming too late? Right? cache reporting? Do I have all the data points in order to get to an output that covers all the metrics that my organization would like to see from me? forecasting same, the action scenes on data access, do ma my organization and eventually the system that I’m using has access to all the data points because sometimes and I’ll touch this briefly later, access to all the roles Data is becoming the problem and also an opportunity, cash allocation, access to the information. Am I looking at all the data that allow me to do a known and secure funding liquidity planning? Right? So those are the questions. Seeing in a different, we see this from a different angle. I mean, again, I would look at this briefly in terms of, how much time are we dedicating to this activity, and how relevant these activities are, in our correct and validated is the output out of this activity that my team is able to generate.
So usually in typical finance, slash Treasury organization, I organize these also in terms of like, time-consuming effort, I mean, payments, reconciliation, reporting and compliance, I mean, planning of any sort with forecasting leaves, like the opportunity to make and spend time on strategic decision and put a lot of pressure on that, taking away valuable time. So in this first group of slides, I tried to possibly condensate, the concept of why we should look at technology as an opportunity and why you shouldn’t pass now then the conversation becomes, what should I focus on? And that is, possibly I mean, something that I am gonna attempt to try to cover next. So what should we look into, right? nowadays? What is relevant? I don’t know if you’re surprised or not, I didn’t put any ATMs or anything like that just yet, I want to stay and not shop. So I think is more on the concept of like data access, and what kind of capability we have to process this data, right? So I give the TMS or any other software sort of a given in the way in this look, because what’s more important is out netcentric my system are connected to each other. So what we’ve seen and the kind of conversation that I’m having with like organizations like yours around the countries, okay, do I have all the information in one box in order to really achieve an output that can cover all the needs in an acceptable amount of time? And of course, it needs to be correct, right? So data management in this sense, goes back to the core, the concept of data, lakes, the data mart, whatever you want to call it. So just to be sure that the, all the systems share the sort of database, so that even like access to advanced analytics, access to advanced reporting, is not prevented or limited in terms of like, the data set that it contains. And of course, analytics is the capability to process and analyze events in the life of the companies in order to basically forensically Look what app an answer to the wide app and also project what will happen or might happen in a stress test scenario. So again, maybe I went a little bit I add, but if you think about analytics, I mean, I break down this in diagnostic, descriptive, predictive and prescriptive, which is basically the why things are happening as I said before, I mean, add enough historical data to identify patterns. And this is applicable to many different topics in the organization, whether you’re looking at cash flows, regional stats, for like business units, procurement, sales, whatever you write, but it becomes something having enough data to basically understand pattern then to put into your forecast that there are scenarios and then once you do have those that you can refine time over time, then you can stress test that we don’t what-if scenario, the catastrophic scenario you can apply the algorithm in order to basically I mean, understand what happens in certain circumstances. This is also applicable to your edging strategy. For example, right? Again, of course, I mean, are we what else we can leverage that I mean, I think data management, and analytics, per should be on top of these other like, tools that you we all have heard about, like artificial intelligence and machine learning, Intelligent Automation, these are application, right. But if you don’t have fertile soil, where to apply them, the output is gonna be much diminished, right? So it’s also going back to the concept of, I want to maximize my return on investment. So I never advise people to invest in technology, per se. But I mean, it needs to fit a plan, it needs to fit the purpose, and you don’t need to buy a Ferrari, if we just need a fourth, right. So I think it’s also like a gradual approach to enhance your own processes, and not just like, go for the shiny object. Not saying that it’s easy to make a business case and get money in Treasury to get some financing to to invest in technology, because it’s not. So again, I’m not gonna spend too much time on these slides. But again, there is the application of ml and AI, in forecasting software, I think, even our host here as a powerful system that leverages that. But I think it’s important to put things into context, right? So things about investment in technology, when you have like a game plan, and you have like, the different actors in the organization that is working together for that object. And I think today, the best return on investment is also to have like, secure access to two different data that can qualify reporting, even in Treasury with data that are not necessarily in ATMs. So although we start right, so if we look at the DVLA out, sometimes I mean, more often than assuming your organization app has a treasury management system, sometimes these treasury management system, and other systems in the organization, they operate in silos, they don’t talk to each other, or they talk to each other, only partially in so leaving in the quality and the kind of the of reports and data that you can process. Right. So I think, when I look at this, I think that the very next step is to create access to more data points. Right? And, okay, five minutes left. Okay. So jumping adds, thank you. So, this is like an imperfect attempt to show what I’m trying proximally not so clearly to describe. So the TMS justice, I’m assuming as being into tertiary people is then the lower-left corner, but just a piece of the puzzle in,
in a system like the landscape in which access to a shared database would enhance and improve the quality of the output out of it. So I think that and then I mean, on top of that, like advanced bi reporting can qualify and improve the reporting output as well. And I think that’s the way that when I look at what should we be thinking nowadays is also leveraging while we are but how we can conduct it better with another system within the organization, I do understand that this is becoming more and more like an enterprise initiative, they cannot just be Treasury right. circling back, if you after what I briefly said, I think you go back the objective should be like more access to data, time access to data that they will allow more and more qualified analysis and output from like, specific analysis that you can set up to respond to specific goals that your organization put to put on your take away. Depending on where you are, you can definitely I mean, understand what are you missing out of your BI tool assuming you have a BI tool or your like reporting structure currently, what additional data would increase enhance the quality or allow you to insert more metrics, right? So little steps, where do I start? So look what you have right now identified things that you know, your organization, your leadership would rate important and start to work on, how can we get there, instead of like, shooting for the moon from the start, right? machine-learning goes into the equation of whether or not you want to invest in specific software, the leverage the kind of capability, I think I see machine learning more applied, when you will, we look at from the Treasury angle into cash forecasting. And so in that sense, I mean, if you do have the opportunity to invest in software because cash forecasting is really important, any organization that’s where machine learning is probably is going to be the most useful. Link to the other one, and then at the end of the day, I think this should be part of like a wider strategy in the organization starting from the Office of the CFO. With that, I’m going to stop my really short speech today. And I’ll give the opportunity to ask any question that I’ll attempt to answer and even complaints, please raise it.
Moderator:
Thank you, Valero. Yes, q&a. Questions pop into your mind?
Audience Member 1:
I have one. Yeah, sure.
So when you begin an engagement with a client? As in why I’m curious, do you see Treasury transformation initiatives, often being part of a broader digital transformation strategy within the overall company, are they kind of venturing out on their own knowing they need to transform and change and in engaging you directly at that level?
Valerio Trinchi:
I think we see both. Usually, I mean, the enterprise wise initiative are funded, because Treasury notoriously doesn’t have much budget. But that also makes the difference between like, the spectrum of what’s in scope, because usually, I mean, working with Treasury, we will focus more like on some smaller initiative, it can be a TMS election, a TMS upgrade, a process transformation within the organization. If it’s an enterprise why’s that is when I mean, as part of a wider finance transformation, we’re looking at, like data management, advanced analytics, because that usually intertwined with our department. And so you’re not just Treasury, but basically, you have the CFO requiring the risk management code, the treasurer group, the finance group did find a group to basically enhance and qualify even further the output that is receiving and also the time within which he’s receiving that output.
Audience Member 1:
And just a follow on to that, does Treasury seem to do a decent job of hooking into maybe the enterprise-wide BI tools that they have, are they often going out based on your recommendations and acquiring their own tool?
Valerio Trinchi:
I mean, we see bi as a mature technology right now. So more and more clients day you have within the organization, a BI tool, whether that is Power BI, tableau, you name it, it becomes on how they’re using it, or they’re deploying it. And again, more importantly, the most typical, like a project that I have right now around BI tools is like data access, because sometimes they reside in only a part of the organization. And they don’t have like, a certain set of data. So preventing them to generate the dashboard and big output with certain metrics in an automated fashion, because they’re lacking, like 30% of the data to get to that out. So I think that’s the effort that we’re seeing organizations like engaging gas to help them achieve.
Audience Member 2:
Because you mentioned that earlier, right? Without that fertile baseline of knowledge, right? BI tools AI. Where are you seeing the biggest gaps with some of the tertiary groups that you’re working with, where they’re struggling to get the right data to be able to use the software.
Valerio Trinchi:
So for instance, I mean, TMS, sometimes I mean, as financial instruments in it, but they don’t have. So other groups may manage some other parts of those instruments or strategies. So that the output that say Typical organization is able to produce out of that TMS is only limited to let’s say like of course like a list of the instruments their maturity there are some other metrics related to those instruments but they cannot be combined with the liquidity planning that is basically sitting with FEMA or other groups right and so sometimes I mean the CFO wants to see those two things like combined to say okay, we have this an in an automated way because yes, right now organizations are still doing that they’re doing it in a more manual way right are creating this macro Excel file and put things together I think it’s just like putting that together in an automated way so that’s what I meant by the shared database as a set of data is coming from the system a set of data is coming for the TMS and then you can customize and automate the generation of our report related to that topic with a regular cadence in a near real-time I open.
Moderator:
other questions on that
Audience Member 3:
this might be very like the granular type of question but I’m curious if you ever worked on a project that revolved around creating I guess a repository of data lake like you refer to all payments in the organization payments coming from the Treasury workstation from the modules and then sort of doing things around you know, preventing duplicate payments you know, making sure that there’s some sort of cross-analysis between those different regions.
Valerio Trinchi:
knobs payments is another one right then our candidate I would say so usually you have like payments managed through the RP, AP, non-Treasury then you have the Treasury payments and other payments, sometimes most time channel through TMS but also all managed by other groups in the investment group or other or other groups like that. So more and more I mean, our preaching is to create like, sort of like connectivity nowadays where I can sell that because that allows us we combine with a data mart concept to have sort of like the payment factory if you guys are familiar concept that adding visibility in near real-time on all the payments according to in the organization, no matter where Jersey is jurisdiction is and be able to intervene now So you mentioned like payment fraud. So that’s another one right? So why should we not consider technology advancement because cybersecurity and payment fraud techniques are I mean, payment fraud by fraudsters are kind of like riskier nowadays and so technology can definitely help you to identify that or duplicate payments. So you can there is software that allows you and probably you guys are familiar to build certain rules of logic that can screen all the payments and if that rule is met of the circumstances is met that payment is flagged and queued for like for review so you can do that like enterprise wise and with the right arkad architecture. So any payments will be subject to that coming from any system if routed from like your connectivity, no matter which bank is going right?
Well yes, because for instance on payments can be initiated by different systems even different instances of VRP throughout the world, right? But if they are routed through like a hub then you have visibility now of course in certain jurisdictions that can be just replicated in the mirror for like jurisdiction restriction but still, you have also near real-time visibility on what’s happening in New Zealand versus like South Africa and then at least you can intervene much earlier should you need to then in a more like traditional way of processing things in which that DRP locally is just talking to the banks locally. And you’re gonna know though the fact like three weeks after something right.
Audience Member 3:
Yeah, there are a few vendors out there that have payment factory payment have with a lot of the critical things that you’re talking about right and OFAC checking duplicates whitelist blacklist you know all that stuff. Yeah.
Moderator:
Question good stuff anymore
Valerio Trinchi:
after lunch and understand.
Moderator:
We’ll be serving some coffee here shortly. Thank you very much Valerio.
Valerio Trinchi:
Thank you.
