How BlackRock Empowers Clients Through Data Accuracy

Joseph Drambarean:
Well, welcome to Fintech Corner. I’m Joseph Drambarean, one of your many hosts this year. We’re here at AFP 2024, and I am joined by Henry Ball, who is our Head of Business Development VP here at Trovata. And why don’t you introduce your best friend here? Because I feel like the third wheel.

Henry Ball:
Very much so. You are. So no, this is Ron Hill, a dear former colleague of mine. I was at BlackRock from 2010 to 2021. When I decided to join a startup, and here I am four years later. Ron and I have known each other for a long time, and he is the guru of all things cash management at BlackRock. And, you know, I’d love to hear about your journey—how you got to this couch today.

Ron Hill:
Wow. It’s been quite a journey, and it’s great to meet you, Joseph, and Henry. Thank you so much. We’ve worked together a long time, and this is amazing to get to this point where we’re sitting on a couch in Fintech Corner. I don’t think in my wildest dreams I would have said that I would wind up at Fintech Corner working with Henry when we were sitting in Wilmington, Delaware, talking about career aspirations. So, I’m Ron Hill, and I have been with BlackRock since 2002. My team was really responsible for the product strategy for the U.S. cash management business and focused on the separate account relationships. I spent a great deal of time on the investment management side. And Joseph, you say, kind of like, how did you get to your conversation? And you’re right, it’s a journey.

In 2017, BlackRock acquired the CacheMatrix platform, and that’s really what kind of happened. I was always part of the investment management side, and when the opportunity came in the last couple of years as CacheMatrix was integrated into Aladdin, the opportunity was offered for me to go support that business. So currently, I head up the sales and relationship management team in the U.S. for CacheMatrix. The purpose is meant to build relationships for the CacheMatrix platform.

Fortunately, knowing Henry and Trovata over the years, we’ve been able to talk about cash management in a different way. That was something that on the investment management side, we didn’t spend a lot of time talking about the technology, the integration, and the data that clients need. In this role in CacheMatrix, it’s so focused on the ecosystem that everyone around that Treasurer uses on a data basis. So, I’m very fortunate to work in this role and very fortunate to work in this role, very fortunate to work with colleagues like yourselves and our clients who are using the platform today.

Quite a journey because, you know, foundationally, I’ve always understood cash management from an investment perspective, but from a client experience and how clients trade and operate, this is a totally different lens, if you will.

Joseph Drambarean:

And I’ll let you jump in a second, Henry, but the first thing that went through my mind is—you’ve probably seen so many evolutions. At the same time you were in that role, so many big changes happened in tech. You know, the introduction of mobile computing, the rollout of wider internet applications, mobile, as a bank online banking thing—you know, that didn’t exist. I can’t even imagine a world where I didn’t have the ability to do everything on my iPhone, right? 

And now here we are, not to go through that entire history, but as you look over the last five to ten years, what’s been, in your opinion, the most impactful area you’ve seen driving innovation and change in this space?

Ron Hill:
Yeah, you’re right. Every five to ten years, you come across something new and innovative where you didn’t expect it. And not to—well, I was at a bank a long time ago and their slogan was “Bank online, not in line.” Right? So that was the approach. It was smart marketing back then. But now, to your point, the advancements that we’ve gotten to—where we see today—is data is much more real-time. People want access to it. We’re accustomed to that type of data being more frequent and readily available.

And that’s something that, from a market perspective, all of us have been focused on. From a service provider standpoint, technology has to keep up with that because there are different points in time when technology may speed up on connections. It may not be as fast when you’re trading certain security types because it relies on old rails in order to transmit that data. So, as you see, for instance, like you have with Trovata, the experience with APIs and real-time cash data—maybe the markets haven’t necessarily kept up with that because of the infrastructure.

In the last, to answer your question, few years, it’s been about the speed in which data becomes available. People have become more accustomed to having data on their phones today. And not missing that. We hear it a lot when clients ask about—I’ll do a quick compare and contrast—when we were looking for fund holdings or other types of data, it was something that wasn’t released until 30 days after month-end. Now clients can see holdings on a daily basis, right? And they’ve become accustomed to that. That’s where the market has migrated. You apply that same thing to every type of piece of data that they’re used to because they’re being asked. When senior officials or leadership are looking for risk or where exposures are or what payments are—that’s the type of speed we’ve seen in the last few years. Hopefully that makes sense.

Joseph Drambarean:
Yeah, absolutely. One of the things we’ve been thinking a ton about over the last five years—because we’ve been at the forefront of working with APIs—is that many times we were the first integrators for APIs that come out. And one of the things we continue to see opportunities for all of our partners, especially when it comes to integration, is—can we get closer to near-zero implementation?

And, you know, not to put you on the spot, but I’m curious, what do you think about the landscape of integrations today? Because APIs have been a buzzword for a while now, right? We’re probably in year seven, maybe, of public API programs that a lot of the major players we see here even at AFP. Where do you see things going? How do things improve from here?

Ron Hill:
And apologies if I think about it a lot because you say the term “near-zero time integrations,” right? And integrations are important because you talk about implementations or integrations and the time it takes to do that. We’re used to operating on a scale of 12 to 18 months where people have to integrate a new system or something of that nature. But the reality is, it doesn’t necessarily have to take that long if you have the resources to do it. So the skill set is different, where people have to be more equipped to be able to access the data and understand where the data is and how to access the APIs.

So, from a skill perspective, you see that timeline condensing down immensely—into measures of weeks, if not days—because you have the ability to make that happen. But it still takes, I think, if I’m answering about implementations as opposed to integrations, it still takes that time and effort to understand what the business process is, right? You can’t miss the key points, or the key data points, or the key metrics that people are using today, in order to accomplish the end goal of getting a new process stood up or a new platform stood up, if that makes sense.

Joseph Drambarean:
Yeah, absolutely. Sorry, Henry, if I’m taking all the questions here, I feel like I could talk about API strategy all day.

Henry Ball:
Ron’s the celebrity, not me. I work here. 

Ron Hill:
I was hoping Henry would chime in and give me some lift here. 

Henry Ball:

But there’s actually something that you said, Ron, at the very beginning, that I think a lot of our listeners don’t know about. You used the term “Aladdin.” From a BlackRock technology perspective, they’ve been focused on a single source of truth and distributed technology—having the same information around the world—for a long time.

And “Aladdin” is the name of the trading system, the broader technology platform of BlackRock, which is actually an acronym which BlackRock analysts probably have memorized or tattooed: “Assets, Liabilities, Derivative, and Investment Network.” Did I miss something?

Ron Hill:
I think that’s it.

Henry Ball:
But BlackRock’s always had a focus on technology. And, thank you. When I joined Trovata, a lot of what resonated with me about our platform was the API-first approach, the single source of truth information, real-time visibility, and really just a data-first way to operate. It really reminded me a lot about BlackRock because that actually started back in 1996 when BlackRock rolled out BlackRock Solutions or BRS. Which was the first time they sold technology and risk services, not asset management services.

So, having a data platform that they used in-house and also sell externally—BlackRock sells probably north of a billion dollars of software every year, in addition to being the world’s largest asset manager. So, that approach and the acquisition of CacheMatrix really follows the same philosophy around being data-first, and then actions come afterward.

Ron Hill:
Yeah, and Henry brings up a great point about the data and the single source of truth—that’s a foundational philosophy of BlackRock and Aladdin. You know, if you think about the security setup, these are all data points that we talk about, whether it’s account data, whether it’s organization data, whether it’s security data—these are all different vendors we deal with. And to your point about implementation—how do you do that?—it really depends on the partners you have to get that data faster. The speed for real-time is only as fast as the people working on it.

And, as Henry knows, having worked at BlackRock, we’re constantly focused on reinventing ourselves, constantly focused on making improvements, listening to our clients, and developing new enhancements to respond to what they’re looking for. So I think that the reason you’ve been able to migrate so well from BlackRock to Trovata and carry that same kind of approach is great to hear. 

Joseph Drambarean:
I’m curious, I did this little exercise you were talking and pretended as if you never mentioned the word “investment.” It kind of sounds like you’re a data company. What do you think about that?

Ron Hill:
Fundamentally, investments are about the data that you have and your investment decisions are probably, and I’m probably the wrong person to specifically say, but we spend a lot of time, Henry knows this from his prior life, is that when there’s data inaccuracies or data problems, that can really consume someone’s day. Right? And if you’re an investor and you’re looking at the data that you have, and if a yield or duration or a coupon is incorrect on a security that you’re looking at, you have to make that decision and hopefully that data is accurate.

That’s why you take more than one source of data point on your data. So, we spend a lot of time around data accuracy for the end result of generating returns, right? And that is kind of key and critical. I think the operating models surrounding it, the ingestion of data, and how you can speed that up. Can you find third-party vendors or people who may provide that data? But you’re right. I mean, we do think about not only just the security data, but then, what we’re sitting here talking about, right? Cash data, you know, in a corporate treasurer’s lifetime, you know, they’re wondering where their cash is, how much cash they have on hand, and how much cash they will need. You know, that data is as important as the other security master data that I was just talking about.

Joseph Drambarean:
The reason I bring it up is because it’s all about framing when you think about the future, right? If you’re the same company that you were over the last 30 years, right? Then maybe you are not seeing the transformation that is happening in front of all of us, right? That data is the new gold, right? It’s everything when it comes to the value that AI and any other systems that would be trying to create automation, trying to create insight, trying to create, you know, the next level of human performance, if you will, from a financial perspective. It can’t be done without data, right? And that foundation.

I’m so fascinated by this because, you know, we’re on this precipice of entering into the age of AI, if you will, right? And you’re sitting on a foundation of data that is mission critical, right, for so many. Do you think that that nexus point is important in the story of BlackRock’s future?

Ron Hill:
Absolutely. I think the idea of processing data at faster speeds is part of this conversation, right? Consuming more data, not just more, not faster, but just the ability to consume and contain and make decisions based on that. You know, if I was at a conference last week and they were talking about the weather app, and it was actually Sudhir talking about this and the way that, you know, weather models were based on maybe, I’m going to get the numbers wrong and I apologize for that, but the magnitude’s similar, right? If the weather predictive models were based on 100 samples, now they’re based on tens of thousands of samples. And that’s because you can use more data and a faster processing speed, but that’s going to take more capital.

And that’s really where it’s going to come from is how do you increase the amount of power that is there to consume that data, process that data, and then give you the results back on that data. And that’s going to take time. So yeah, I would agree that you are kind of nearing this point where it’s not just the current data you have, it’s the additional data that you’ll be able to consume that will make your decisions more informed.

Joseph Drambarean:
We’ve been interacting with customers on the AI front at this point for, it’s been two years since we released Trovata AI. The first iterations of it were not tongue in cheek, but close because it was like, we don’t even know if anybody will use this. And we wanted to see what would happen.

And what happened was actually very unexpected, that it became a core area of our product where we’re continuing to invest significantly in it. One of the reasons is because customers are able to start to analyze more information all at once because they have almost an integrator that’s sitting in between, right? That has exposure to their cash data, their investments data, their AR/AP coming from their ERP system. And instead of having to deal with that data in their own mind or in Excel or whatever their technique is, they now can just ask a question of this thing, right? Nameless thing.

Ron Hill:
Yeah. It is, I mean, and you guys are close to this, but I think we all have this and, you know, as you get AI integrated into your meeting invites, you know, there’s a history on my meeting invite of things we’ve talked about with Trovata. Right. So it gives me prep notes ahead of time, right?

Those are the things that are kind of, you know, we’re thinking about where this large language models go, right? The consumption of data, but where the efficiency is prior to that, I was scanning through my emails. What did we talk about last time? Where are we going? What agreement haven’t I finished or what haven’t I responded to? But if I bring up our collective kind of meeting notes and say, I’m meeting with Henry and Joseph, it’ll tell me, here’s the last five things that you’ve done, right? And not so simple terms, but it certainly helps bring efficiency and research to it. And that’s just another example of data.

Joseph Drambarean:
How do you see AI as a topic when you consider kind of just the product portfolio that you manage today, right? I just came out of a panel this morning where one of the crux questions of the panel was, “Should I be afraid of AI as a practitioner? Will it replace me?” Right? Do you feel that that kind of tension exists in the product portfolio space that you manage today, or do you embrace AI as a vector for change that will be positive?

Ron Hill:

I think that anytime, you know, we deal with this all the time and not just with AI, but I think in any times that you’re having conversations about whether it be an asset management assignment or some increased functionality whereby that was typically handled by spreadsheets or something like that, someone’s always thinking, my gosh, that’s my job, right? 

Like that’s ultimately like what I do. know, hopefully what the response is, that, you know, the age old response has always been that you get time back into your day to focus on the things that really matter. And, you know, I think that people kind of, you know, how many times can I search through the help desk to figure out how I need to find whatever I need to find if AI can give me that answer much quicker than the benefit is real. Right. So, yeah, the tension’s there. It is a concern, but I think at the same time, I think the benefits are not yet realized. 

So as you kind of ease into the results of what you’re getting back from whatever AI you’re using at this point in time, then you’ll start to realize the benefits, right? So it’s kind of a slow grind, if you will, of how the AI can enhance your day, improve your day, and then you go from there. 

Joseph Drambarean:

Henry, what do you think? When customers, like, they look at our solution, they look at CacheMatrix, they look at kind of all of the opportunities that they have to make informed decisions.

What is the right tool or do you think that it’s a combination? Where do we go from here? 

Henry Ball:

That’s a great question. I think it’s a combination. And when we talk about our platform or the benefits of seamless integration or comprehensive information in one place, it’s kind of a one plus one equals three scenario where it’s not that it’s replacing you, it’s actually giving you your time back. Right? So that one hour that you’re saving is now worth more than the one hour you were spending because you’re providing your value, you’re deriving insights, you’re having conversations about a much more rich set of information. You had to spend zero time aggregating and doing the basic work to make it available. 

So I think it’s synergistic and it’s very much a one plus one equals three conversation. And that’s how we sell Trovata even on direct sales motion. We have the wonderful kind of ROI, know, pitch of what do you get out of the platform? And it’s not just aggregation, it’s aggregation done for you so you can do other things. What are those other things? What are those actions you can take and the decisions you can make because of that better, more real time information powered in a large part by AI.

Joseph Drambarean:

Yeah, absolutely. it makes me wonder, you know, sitting here just thinking about AI and thinking about the future, where do you see the future of your own kind of product roadmap, especially when we think about how we’ve kind of interacted up until now, integrations that we could potentially continue to do and improve? Where does the future go from here? Knowing that AI is a thing, knowing that RPA is a thing, everybody’s talking about it. Amazing right.

Ron Hill:

We even hire, you that’s a very kind of, would think a skillset was very much building macros when I was coming out of college, you know, skill sets, know, your blue prism and Python engineering skills, right? Automation is kind of the natural where you go and you can use that in any, I tell my daughter this, she’s a computer science major and I tell her, like, your job will be anywhere where you want to go and people will look for that efficiency all the time. 

But, you know, to answer your question, where do I see that? I think about two things. I think about the first, is the goal that we ultimately have, and I think about this in CacheMatrix, Henry we’ve talked about this, is our clients are all focused on many applications. So the more we can bring that, reduce the number of touch points that they have to be more efficient in their day will help scale their days and give them time back into your analogy of one plus one equals three. That starts in a lot of different directions and that’s ease of use and functionality. 

So I would hope through things such as AI, APIs, anything that provides them with real-time information that helps reduce all that time. It improves the connectivity, it increases the exchange of information, and then subsequently gives us all better richer products to offer to our clients. And then the question for the clients is how and when do they want to access that data? What is the easiest way for them to do that? Or the function, not just the data, but also the functionality that they’re looking for to get invested or to access what their forecasts are.

I think those are, when I think of roadmaps, it’s hard to think more than 12 to 18 months out because there’s so many things that we want to get done in the near term. It is easy to talk about. Roadmaps are such a, and I’m sure I’ll get in trouble for anything I say about the roadmap, but the roadmap is always something that you really want to spend a lot of time being thoughtful on and taking feedback from clients and what we can develop in a reasonable amount of time. And I think those are, I’d say, directionally where you head.

Right. Like those aren’t like specific answers, but directionally where you go, you know, you can really kind of get to some points where clients are seeing benefits of your platform. And I think using tools like that, that’s where you kind of go. So it’s a challenge, but you know, if I looked out three to five years, you know,I sit here and I look at all the booths here and I think everyone’s got a new application for a client to use. Right. And I think like, do clients really want that many? Right. Or are they looking about, okay, how do I get more of what I want into a single source from that perspective?

Joseph Drambarean:

I promise these questions will not end up on TikTok as some spicy new hot take, but I wanted to honestly get your perspective on something. This morning I was having a conversation and it was around the topic of will we ever trust software and AI or both to just make the decisions for us. And in this world, it’s obviously moving significants amount of money.

Making decisions that could have massive impact. And I’m curious, where do you stand on this? Because obviously robo, you know, advisement, investment, that is a thing. It’s been a thing forever. It’s not what we’re talking about right now specifically, but it’s adjacent, right? It’s something that has been explored. This new topic of, well, what if, you know, large language models, all of this data that we’re talking about starts to inform almost a super set of strategy that is non-human, right? That is automated through systems that are able to calculate things and see things that we could never see, right? And act then on those things, right? How do we feel about that? I’m curious, Henry, to hear your take too. And do you think that this is something that will happen? 

Henry Ball:

I think the reality is we do that already, specifically in the cash space, Identifying your optimal cash positions, your balances in certain accounts, and then either moving money in or out of those bank accounts by buying or selling money funds. A lot of that can be automated through knowing what the cash balance is in the bank account. 

So we are actively using software, the automated bank information, the Trovata aggregating and display elsewhere to let that decision be made for you. Set it and forget it. It’s really. It’s totally an if-then statement. And we do that presently and we could do that through CacheMatrix. 

There are applications where we’re already leveraging software to take our rules and guidance and make decisions for us without thinking about it. So I think we’re already there. And those more complex decisions are going to become more common over time, more layered thinking, more complex if-then statements, if you will. But I think the time is now and in the present that we’re actually already doing that. 

Ron Hill:

I think that’s it. You’re right. I mean, we have worked very hard to build automated investing modules within CacheMatrix and give clients the ability to auto invest, but there’s still governance over it, right? So you always have the human touch and there’s rules and parameters, there’s approvals that take place to ensure that whatever you’ve automated to a degree has gotten going to respect whatever boundaries that you need. Even though we think about the ease and efficiency, one of the things I spent a long time of my career doing is looking over investment policies.

And there’s always these, can code those into, you know, we know it as a BlackRock Query Language or BQL, but that is something that, you know, can be coded into a system for trading. And at the same time though, you know, if you can automate that, that saves you time, right? But at the same time, there’s a person who has to oversee the results, even though you can automate compliance, you still have to see the results. You have to have actions, right? Corrective actions and efficiency. 

So whatever the ultimate, you know, process is there’s still some form of governance, whether it’s hands-on governance or governance that you’ve established to monitor the results and ensure that they’re in line with what your expectations are. You’re right. Robo advisors are something that have been around and continue to be around are important. And people will have the choice. Right. Do you want someone who has accountability, responsibility, and how do you adhere to that? We spend hours upon hours of due diligence meetings, understanding who decision makers are when you make investment decisions and technology is same thing. Who’s responsible for the security protocols? Who’s responsible for everything there? So there’s still that angle to it, I think is going to be a part of the conversation. 

Joseph Drambarean:

One thing that I guess is always difficult with this topic is to what extent are we willing to expand the aperture of risk to models, right?

Everything that we’ve talked about so far is easy to dial in, right? It’s, hey, as a corporate strategy, we are not going to exceed these bounds, right? Even our treasurers wouldn’t be exceeding these bounds. So you as an AI system can’t do that. Will there ever be a time, do you guys think, where we will allow these systems to inform us on opportunities where we could exceed those permutations and lines that are set and then actually cross them?

Ron Hill:

It’s quite possible, right? You never say never. That’s the answer. think until we see what the boundaries are and what kind of exceeds those boundaries. And unfortunately, sometimes we learn by like a very bad accident of a boundary being exceeded. But, hopefully that’s not how we learn it. But I think you could foresee that the benefits may outweigh the cost. It just takes time. I don’t have a specific answer, but I think that kind of to your point like that, you know, do we get to that point where you could see that? Of course. But is it a long road and how we get there? 

Joseph Drambarean:

Probably. Yeah. The reason it’s probably fun to think about this is we are literally in a hall filled with people that are the most risk-averse people probably on the planet. So to ask the people in this hall to push that boundary will probably never happen. 

Ron Hill:

And every one of them has a different view on what the risk is. If you think about it, it’s amazing how the range of risk from a 30-day Treasury bill to an overnight deposit could be allowed or not, depending on what your risk tolerance is. And to your point, right now, there is no risk of liquidity. It’s ultimate capital preservation. 

And that’s something that you learn over the years is that you define that differently across the spectrum of people. So if the models can come to that conclusion too, then we’ll see what happens. 

Joseph Drambarean:

Last question. This one hopefully is a fun one. What are you excited about? We’re here. There’s so much promise, so many vendors, ourselves included, just providing a vision of the future. Being here, what excites you most? 

Ron Hill:

So, I mean, being with Henry and having the opportunity to do this with you, this is obviously a great opportunity for sure. But I think the benefits of what we talked about this whole session is something that makes, it’s why one of the main reasons, drivers that I chose to focus on CacheMatrix was that to help clients in a different way as opposed to the investment performance, but also just the efficiency and scale that we talked about learning that, right? Like being part of that story is a lot of fun. So, you know, that’s really kind of the benefit to me. 

Joseph Drambarean:

Henry, anything else? 

Henry Ball:

Yeah, I think the thing that gets me excited right now is there’s a big shift in banks and partners, asset managers really having a focus on being where clients are and getting their data where it needs to be. It’s not the question of how do I make my bank or platform better than another one. It’s where do my clients spend their time and how do I most efficiently get their data to where they need to operate? 

I think a lot about J.G. Wentworth commercials from the mid 90s. It’s my money. I want it now. And the reality is it’s my data. I want it now. And customers, I think, have finally gotten attention from all of their investment and bank partners of like, I’m not going to operate in one bank. One bank does not exist anymore, one asset manager may not exist anymore in terms of where you invest your cash or where you have your operating accounts and you’re going to operate in a platform like Trovata, you’re going to operate in just another ecosystem. And I think the holders of that information are kind of realizing it’s not their data. It’s the customers need to operate where they need to operate. And that philosophical shift has really been noticeable this year.

Joseph Drambarean:

Henry knew exactly what he was doing when he put that jingle in our mind and now we will be walking around the rest of the day. Alright well Ron thank you so much for joining us. Appreciate your time and we’ll see you next time on Fintech Corner. Thank you.