Gavin Little-Gill

Let's switch gears a little bit and talk about simplification now, I think the pendulum definitely swinging back, we see this pendulum swing between sort of best of breed and integrated solutions across the landscape and the pendulum is definitely swinging back to simplification and bringing technology together. The simple answer to this question as in terms of why is for cost purposes. Right. But there's a lot more to the story than just just cost.

People are really stopping and it ties back I think to the operational resilience. Right? How do you think about shared services? How do you think about leveraging people across those silos that we've been talking about from a product perspective, data perspective from a geographical perspective, you've got to think about not just bringing those people together and training them, but you've got to think about, do they have access to the technology and how many people do you have access to that technology, how many applications that need to be cross trained on?

So how can you simplify that environment to be able to support that operational resilience and those specific efforts. But the last piece of this is about people that are forward thinking of really thinking about it from a capabilities perspective as well.

Right. How do I grow the capabilities in terms of supporting all the new products and services that we have to deal with, all the regulations have to deal with, how do I accelerate time to marketplace, how do I create agility my market space?

So let me address my first question to Neha because I know she's thinking about the overall strategies and a lot of these businesses are out there right. So, Neha why should firms be focusing on simplification as a critical initiative and and how do you recommend that firms approach simplification sort of across these silos?

Neha Singh

Sure. So I think the challenge for capital markets firms today is that they have to deliver two sides of the same coin. What I mean by that is not only do they have to reduce costs but they now have to do it in an uncertain environment where you need to be a child to grow and deal with all of the change that's taking place. I think someone on a panel earlier today mentioned that we're seeing more regulatory change now than we saw right after the financial crisis. So, I think this is why simplification across silos is so critical.

I think it provides a way to remove all of this friction between applications and in the workflows and achieve all of these different objectives in one goal. And so Gavin to your question like how do you simplify, we look at it as two flavors of simplification. The first is horizontal, so which is simplifying across asset class in regional silos and the second is vertical. So, which is simplifying across the trade lifecycle and closely connecting the front, middle and back office.

I think both of these flavors need a few things to be successful I think first is a common view of data, I mean that is an absolutely critical element to successfully break down silos and two I think is componentization, so just modular capabilities that can reduce duplication.

You also need interoperability between these different components and then you need scalability to deal with all of the changing volumes. So I think those are the principles and the question is like how do you really apply those and in our experience helping firms drive simplification, what we've seen is that the right approach really varies by form. So it depends on what's their starting point.

So, what is their footprint of legacy systems? What are the critical pain points that they need to solve and it also depends on their business priorities and where they're looking to grow and so you can use these inputs to then define a target state and a set of incremental steps that can actually get you there and I can share some of our simplification journey at Broadridge to illustrate this, we realized that to achieve two sides of the coin, we needed to move away from monolithic solutions that gave efficiency but they took a lot of time and effort to implement.

Instead, what we needed was a component based approach which essentially consolidates data as well as capabilities to get to more efficiencies faster and also increases agility and so we've developed a number of post trade components that go across silos.

For example, we built component that provides a consolidated view of positions and that can actually be deployed globally as well as across asset classes and I think the key is again you can roll out these components incrementally so it's almost like you're getting a series of wins as opposed to you need a big bang transformation to drive that.

I think that's really critical because you have to be able to see value at every stage of the journey. So yeah, I think that to me is the beauty of simplification. Like you can deliver both sides of the coin and it's like you're defying gravity in the process.

Gavin Little-Gill

Great Mike, how does that ring true? Like when you think about that from a Broadridge perspective and how does that apply to your business and what do you say?

Michael Walsh

I think when I look at simplification, when we look at simplification, I think it really comes down to data and making sure you have the right data and use the data correctly.

So pre pandemic, we have started a pretty large team, data management and data management scientists and really looking at our data across the board from books and records, point of view, risk point of view, a client point of view and I think when we we continue to make good success on that and I would say as you standardize the data, the data management office has been working well with the business lines to support areas and with that, we've made great progress in the last couple of years and I would say what specifically for an operations perspective there, we have done really well with understanding our clients and knowing our clients much better than we did.

Our pricing models are much better than they ever did and our books and records and our risk management reports are much better than they ever were before. And even on the client side that I think because good data means good clients in our mind and I think that we know more about our clients than we have. We can always learn more and horizon is still out there for us but I would say is that we are now starting to use that data more effectively operational process.

So, before fair was a fail and we just moved on now, we know which clients are good clients, which ones that we have very high success rates with and which ones are bad and what we can do about that. We've got more data about our collateral management and what we have is on calls on collateral management, we know the risk and we know it daily now used to be almost like an end of the week report and said where it is.

So, I would give a lot of credit to our data management office, even our management above us to kind of say the investments that they made paid off. And again, I think it stands right at the top of the list as far as simplification for us.

Dan Delahanty

I agree with Mike on that, right. I mean data is so fundamental to our solutions, right? Whether it's the static data and referential data that's being loaded into the system. If it's the data model that being used to communicate between systems and platforms or if it's the data that we're providing to our end clients right for them to consume.

Without that being working in a normalized standard, standardized fashion, you're not going to achieve the straight through processing that you want to achieve, right? So from a vertical simplification standpoint, having the same data across the front, middle and back is so critical from that perspective.

Then, on the horizontal perspective it's the same thing. Right? So having that data model where these components that Neha was speaking about can speak to some of the others legacy systems and internal systems of firms providing a standardized way for them to consume that data it really all starts and gets driven from there

Neha Singh

Yeah. And I, I'll add to that, I completely agree. I think data standardization is really at the heart of driving simplification. If you look at vertical simplification which goes across the trade lifecycle today firms have several front middle back systems, they are integrated using point to point connections. Each sort of having its own data model, that's really creating all of these fragmentation challenges that we've been talking about and so you can solve this through the common view of data, and we actually look at a couple of ways to do that.

The first, as you mentioned, just a common view of reference data but creating that view across front middle and back. And one of the panels today, they talked about, moving from exception-based processing to eliminating exceptions and I think that's exactly the concept here, let's attack the problem at the source and which which will create fewer mismatches and fewer breaks for operations teams to reconcile.

Right. Um I think the second thing is the common data model right? So are having the system speak the same language right? And making the data visible across the trade lifecycle. So that makes it possible to share consolidated front office data with the back. So that makes downstream functions like reporting much faster and more accurate and then enabling sharing of data the other way around.

So back-office data with the front to be able to provide business insights and help make better decisions. Right? So, for example, the front office had a consolidated view of positions and risk and margin that would help them make better capital and collateral decisions and help them better target their clients.

Right? So, you can see how these insights can then start to lead to some differentiation for the business as well once you're starting to expose data. I will say it's definitely a journey, we've been on our own journey at Broadridge and we're investing in these data levers going across from front to back.

For example, we've created our own common data model for Capital Markets. I think what's helped us in this process is taking a practical approach. So rather than try to include all possible attributes from a data perspective, really focused in on what are the business outcome data points that we need to include and then we've looked at specific use cases that we can build on, so you can actually see value at every step.

Michael Walsh

I just one more point Gavin, I would say it is that one of the things that happened with us when we were doing data we said okay we gotta get better. I think the drivers was really risk management saying my risk reports are wrong when we had an industry event or some major markets went out of business, we didn't really have the right data to know where our exposure was. So, they were the driver.

I think the Fed pushed that as well for banking perspective for us. And then I think then we started to say, well then, the risk isn't right then the books and records and as a byproduct and probably wasn't in the original plan from an operational process, I think it really made a big impact if your client referential gets better, your product information gets better so that the risk reports are better, the accounting much better.

At the end of the day, the operational processes got better. So out front to back, reconciliations, which is all most of the reasons why you have to break this, because bad referential that fixed itself almost. And then the same thing as far as cash breaks with the custodians and so on, that all kind of massively went down and massively is like 70% whatever large number was. But there was a lot less work for us, on T+1 to do our job and I think that's what it has to do with making things simpler.

Gavin Little-Gill

It's a great point about what we're talking about data and I think that everyone stop and say, yeah, what it makes perfect sense. You can create clean data, use that same data consistently across the enterprise.

It's gonna make everything run better. The flip side of that as people go, wow, the data I require across different instruments is totally different. The data of different applications is totally different. Right.

So and people stop and say yeah, but if we if we create that common data model, I mean, first of all, do we create this Franken monster, right? Or do we create this Jack of all trades? Master of none type of data. So how do to reconcile those data models, data lakes and data ponds, whatever you wanna call them, right. That have grown up to support specific application specific security specific processes. And they work with all of the benefits. And how do you how do you do that? Right. How do you approach that? So I don't know, Mike you're talking, you've lived this.

Michael Walsh

I would think that from our point of view, I think it was more related to how do we again make things better for us with our clients because I think our clients, what what happened, with the covid in circling back kind of towards the first question what we we did we did understand our clients wanted information more quickly. So, it was used to be was, it's okay if you get back to me, it's like I need to know it now, especially with the volatility in the markets and it's continuing right? So, I think we that's where we kind of driving was the risk management side of it and then secondly was more of the client side.

Gavin Little-Gill

Great. And Neha I know you've worked a lot on sort of common data models and approaches, anything to add around standardization or any of those aspects.

Neha Singh

Yeah, I think, it's a fair point right there, there's a reason why there's so many different data, there's a reason why, you have all these different systems but at the same time there is a lot of duplication of capabilities that there's a there's a common element right in the data.

And this is why, as I mentioned earlier, I think you want to be very clear about what is the outcome you're trying to drive and being driven by use cases. So we're not, again, we're not trying to create, as you said, the Frankenstein, right? The ultimate data model that's going to solve everything. But being very clear about these are the business outcomes we're looking to drive, and this is the data that is going to get you there right.

That focus can help ensure that you're getting the benefit of reducing duplication, right? But at the same time you're not missing out on the specificity that we need to drive.

Dan Delahanty

Yeah, I'll just add to that, the point, you're going to start with that common set of fields that make up that data model, but it's gonna be something that constantly evolves as business evolves and you start to introduce new asset classes, new security types right into into those systems, you're going to need to support new fields. Right?

And I think one of the most important things is meticulously looking at every new field that's going to be added into that to see if it is critical to running the business and achieving your objective, because if it's not, you're gonna have that Franken monster that you're speaking about.

And it's gonna it's gonna spin out and spin out of control and then it becomes unwieldy. Right? So I think that's one of the most important things that as this evolves is to look at those new elements that you introduce to your model.

Gavin Little-Gill

Right. That's interesting. I mean, I think one of the things I've just taken away sort of just in the conversation we've had here is this this whole idea that you've got to be able to communicate an effective vision around what around the goals in terms of what you're approaching this for, right?

For risk purposes or for right? It's that broader goal, in that broader broader component is not data simplification and standardization for the sake of data standardization, it's for the sake of right, it's a means to an end.

Yeah. So I know, one of the, we talked about this earlier, this is growth in crypto and private markets and all these things happening, right? And people's initial inclination and has been for years, we had new instruments, what do we do put them into a little silo put in a little box, we put a little wall between them and everything else we do in the business, right?

We've just been talking about simplification, we've been talking about how we create, use tech, common technology, common data, right, standards, common processes in order to support these things. How are we going to reconcile that operational simplicity and that movement towards building that with the addition of all these new securities that are coming down the pipeline and how we're gonna do those things in parallel. So create simplicity while adding complexity. Right? So I don't know, Dan do you want to kick us off and tell us what you tell us what your clients are doing.

Dan Delahanty

Yeah, I mean, think about the common components that we that Neha mentioned before. Right? So you're gonna have some functions that that span across asset classes and regions. And you're going to have other functions that are going to have that regional specificity.

I think the foundations that we're talking about things like inventory management, finance and accounting, trade management is going to be the same across asset classes and regions, right, at least similar enough that you have the building blocks to support new asset classes as they come on.

So, when we're designing software, we're looking at it from that perspective, creating the foundation to add those additional asset classes so you just have to make changes to those foundational elements to support those. Right? If you look at something like crypto, we spoke at a client recently that we on boarded to a crypto platform for bookkeeping. They use our traditional equities bookkeeping platform for this but, the change that they made for crypto is actually adjusting to support eight decimal points on the securities themselves. Right? So that's the idea of using that same kind of foundational element and then adjusting to that market and and their needs as they come on.

We expect to see a lot more of this, especially with the rise of crypto and other digital assets. I think someone mentioned on one of the earlier panels today privatized securities, obviously that's a very interesting space. I think it was a $3.1 trillion market I believe was the interest on that. So we expect to see more of that and firms wanting to move into more of these different types of asset classes. We are keeping that in mind with our design when we build these foundation elements.

Gavin Little-Gill

That's great. What do you think Mike?

Michael Walsh

I agree with everything that Dan just said. I think one of the things that I would say is the regionalization of data, right? So, I think that in many cases for good reasons it's localized but I think the real push now is to try to get that information positions, P&L, and all of that more consolidated on a global basis. And I think that there was good reasons behind it, maybe time to market maybe just local practices. But I think they're now the plan is more to make it more global and be able to add on to new asset classes and I think that if you have the right structure, you can do it again. It goes back to kind of making sure to try to keep things simple.

Gavin Little-Gill

Build a foundation first and then make sure that it’s solid before you add additional floors on the house.

Dan Delahanty

Yeah, I mean it's really future proofing your system if you wanna think of it that way. Right? You want to build something that puts you in the right place to make easy modifications to allow you to enter quickly into new markets and asset classes. That that's really the goal.

Gavin Little-Gill

Yeah, that's great. That's great perspective

Gavin Little-Gill

A lot of what we've been talking about has to do with technology right? And just there's a ton out of it and it's enabling and its potentially disarming right? I mean it's it has potential to allow you to gain or lose competitive advantage or get competitive leapfrogged in this market space.

How do you how do you handle that? Right. So I guess the question I'd ask of each of you, you start thinking about technology, what areas of the trade lifecycle two questions really. What area the trade life cycle do you think it's gonna be most impacted by emerging technology and what is the one piece of technology that you would stop and say has the potential to have the most impact?

Neha Singh

Yeah, I can start I think technologies like DLT and Machine learning cloud they're all going to see increased investment right? And we're going to see a greater scale of impact over the next couple of years.

And just some numbers around this our research shows that capital markets firms plan to increase their I. T. spend in next gen technologies by 30% over the next two years. Personally, I'm most passionate about machine learning because I think we're only starting to scratch the surface of what's possible there.

And as the industry progresses on the things we've talked about simplification, creating a common body of data that's when we'll have the foundation to really have AI/ML take off at scale. And I see it transforming all areas of the trade lifecycle, the front middle and back office. For example, we've created machine learning models that can find patterns in historical data and predict the likelihood that a trade will fail. And if you think about it, this sort of inside can benefit multiple users across the trade lifecycle.

So from an operations perspective, this can help the team really prioritize what are the open trades they should be looking at to prevent them from failing. From a front office perspective, they can use these insights to say, well what are the risks and potential costs of the trade even before they act on it? And that's valuable. Both of these are valuable if you think about the move towards to T+1 and if you think about the penalties under the CSDR regime, this is valuable insights for them to have.

From a funding team perspective, they can now get to better funding projections because now they have a view of risk of failure. So you can see the pattern here, right? There's these sorts of insights that can start to transform the way we do business going across the trade lifecycle.

Just a couple of things I will add as we look to AI in the future. I think first to move from doing cool proof of concepts on the side to actual on the ground impact from AI. You have to be able to embed these AI insights in your day-to-day workflow and this is why you see leaders being successful, they're actually deploying AI as part of their core business and they've done the hard work, they've invested in simplification and access to clean data and so to be able to see outside benefits from all of this.

Second, I think AI will become a necessity for forms to just simply stay relevant. The reason I say that is we're seeing leaders create a competitive gap with the use of AI, I think that's only going to widen as their models get more sophisticated, they're better using it to power their decisions.

Our research shows that about 18% of firms are at this advanced level of AI adoption, but in the next couple of years that's expected to go to 39%. So, we're going to see firms investing internally and also in an ecosystem of partners that can really help them embed AI into their business and and be able to get these benefits of scale.

Gavin Little-Gill

Great perspective.

Michael Walsh

I would say that the piece of technology that we're looking at is obviously blockchain and DLT and I would say, three years ago, you could be at this panel and people were saying blockchain is high, blockchain is five years away, keep your fingers crossed, maybe it's five years, but it could be 10 and so on.

I think we've been on the hunt for blockchain technology for the last three years and the hype is over because I think is really there's products out there now, there's that are working today. So in our case, we've been involved in the Broadridge blockchain project that is out there. And we're expecting to go live, we just found the news today. We're gonna go live next month will be the third firm on the blockchain. And we believe we're not doing it for the hype, we're doing it because we're gonna save high six figures in clearance cost reductions.

So it's a fact, it's real money and we're going to do that and we believe if we were rolling it out for internal our affiliates, SG affiliates and we believe that number will go up to seven into the seven figures in reduction of clearance cost by using blockchain technology at Broadridge.

The same thing we've been actively involved in testing with blockchain for with the Paxos. So, we're one of the three teams firms that tested with them in the initial phase and we again we see shorter settlements, maybe better reduction and operational risk and funding, so we see the benefits and as of two weeks ago we've been talking with DTC and looking to join the ION project.

So, we're on the hunt is clear, we're looking at on an equity swap business what we could do this blockchain up and running, we'd like to join that blockchain. We were told by one of our clients a matter of fact you're a large equity derivative player, why aren't you not on there? So it was actually a client request for us to do something there. So we think that it's blockchain technology, we think it's here and we're gonna continue to be on the hunt. We've also created a company in SG called SG Forge which is doing blockchain which has long a digital product, a bond. And they're talking to do doing the same on the structure products.

We believe that blockchain is here for an efficiency cost savings, wait for us to do the business because again, I think, we've done everything we can in the back-office systems to, in the back office we've nearshored we've offshored, we've outsourced the Broadridge, we've done everything so that the math can't get any lower there.

So, the only way we could do is you just said Gavin, but earlier, the only way is technology, right? So now we're AI will work, we haven't done much there, but we definitely are putting a lot of bets on on the blockchain and open to do as many block chains and if someone fell. And so what, we'll take the 80/20 rule and be happy.

Dan Delahanty

My perspective very similar to Mike’s on this in that I think distributed ledger technology, blockchain has the potential to transform settlement, right? I mean, if you look at it, it's being used now and Mike mentioned, just within the Broadridge perspective for repo transactions, but that's, that just scratching the surface.

I think, more and more firms are gonna start to adapt this. It provides that instantaneous settlement which which becomes very, very important in the T+1 and T+0 world. It cuts down on your counterparty risk because you're locked in on the blockchain. It just has so many benefits beyond traditional settlement. Every client I’m out to speaking to now, is talking about blockchain or DLT in some fashion. I think right now, they’re just figure out how to apply it to their businesses.

Right? So, I think that's gonna be the big thing that you see over the next couple of years is you're gonna see more and more use cases coming out where there should be distributed ledger technology can be used. I mentioned privatized securities before, digitizing, a private security and being able to transact that and sell that on the blockchain will greatly increase efficiency in that space, where it is a very manual process today of trading the securities.

Right? So that's another area that we see picking up quite a bit. Is the digitization of those private security. So, I guess I think distributed ledger will kind of lead the way in the next couple of years to come.

Gavin Little-Gill

Yep interesting. I'll just add one quickly to this. And it's only because we're having a conversation about data management, but it's what we're starting to see in terms of the cloud and data. And as you start thinking about snowflake, and I'm as I'm talking to people about how they're deploying snowflake and how they're beginning to share data back and forth across cloud providers across, by leveraging, sort of the mirroring of different snowflake instances across those clouds.

It's fascinating. And you start thinking about the potential to get rid of file transfers and then your head starts to explode, right? Because you start thinking about just the compression of time frame and how we can actually instantaneously be looking at the same data across enterprises. And that's just fascinating concept to me.

Gavin Little-Gill

as we kick off this off here, let's talk a little bit about operational resilience. Operational resilience is absolutely one of the top topics that, and hottest topics at the sea level when we get out there and talk to folks. 

The pandemic may be one reason why it may have sort of crystallized, this is the topic in, in the front, in the, at the board level. However, it's far from the only reason, right? It's you hear conversations about things like climate change, operational risk, cybersecurity, third party risk and interdependencies, and there's a whole host of regulations that are occurring globally around those topics in terms of how do you manage your business and how you're engaging in operational reasons and the challenges this? 

Right, we've just talked about all the things that are changing all the increased complexity that is coming to your business while you're being asked to engage in operational resilience. 

Right? How do you do that? So let's ask our panelists about how they're starting to see that. Let me let me start with you, Mike, if you don't mind. So how did covid and now this sort of global events change, how people think about operational resilience, both on the industry level and the regulatory level and how our firm's approaching it now. 

Michael Walsh

I would say for a Soc Gen, I think, we've been grappling with how we can bring people back to work and obviously, and deal with resilience there. So our model is more of a hybrid model. 

We were expecting people back 2-3 days a week and we see the benefits of people coming in the office for collaboration, teamwork and mentoring and developing junior talent are really important for reasons why we should be in the office. 

And then again we have a couple of days to work from home. And I think the point there is more of, people are stressing that they want, they want a good quality of life and and and they could work from home is giving them an opportunity to do so. 

So we've got to make sure that we have that delicate balance there of making sure people can develop in the office, working together in collaboration as well as being able to have the good work life balance. 

And I think what goes along with that is making sure that we can retain good people because if we don't have that, there's an opportunity to lose people which we don't want to do. I would say that's the domestic side of it is when we come to our near showing and offshoring locations becomes a little more complex. 

So I think, when you talk about our location in Montreal, obviously the pandemic was a little later in the cycle than than where where we were the vaccines were later returned to work is later, there's mandates from the from the government. 

So as if they just were allowed to allow people in unvaccinated in the offices, last last Monday just or yesterday. I would say then we have the issue of what's going on and with India and so on. 

But I would say Gavin, is one of the things that's out there more and more is about what happens if there's a crisis in in one of these countries and we have an infrastructure problem where we have a covid problem and how do we re onshore? 

So we did a really great job of reshoring offshoring but we've kinda now the big and we haven't talked about it for years now with covid. Then the conversations have been much more granular, okay, what do we have to do to re-onshore our rex? 

And of course people aren't there and where's the balance and what's the process? I think that the other thing that's out there is cybersecurity and I think that we spend an awful lot of time planning and and working on with the teams if we were attacked or if the industry was attacked or our firm was attacked, what is our plan, what do we do? 

And what what do we do with our partners? How can we work with them in the event of cybersecurity? So, resiliency is, is definitely one of the hottest topics we have. 

Dan Delahanty

Yeah, I agree with what Mike said there and I think a lot of firms have refocused on their business continuity plans if we go back to 2012 when Hurricane Sandy hit. I think a lot of people looked at the business continuity plans then and really focus on the technology and system availability. 

Right. A lot of, a lot of people didn't have access to the systems they needed that that's on we go to Covid, years later it's a completely different problem. It's not so much a system problem at this point, it's people are out for extended periods of time being sick, you're potentially your whole operation could be out with Covid. 

So, I think firms are looking at how they address that problem. You pair that with a great resignation where people are just resigning from their jobs are not coming to work. You end up with a major shortage and work staff. 

So, I think firms are trying to address that in a couple ways. One is having for example on demand resources, so partnering with other firms where if they are in a short period of time being able to spin up some operational staff that can help them. 

Another way is cross training. So cross training other other regions, other asset classes to perform similar functions to be able to cover when other people are out. Those, I think are two big themes I think that have kind of come across the industry around the operational resilience. I think technology has to play a part in this as well because you're gonna have people coming onto your systems that they're unfamiliar with. 

Usability is a big factor. So having things like a common user interface across systems, we've seen, I spoke to a number of firms at this point that are really trying to unify that common user interface, so if they have people who need to cover for one another, it becomes natural to them. 

Right? So, that's something that we're looking at at Broadridge as well, is really trying to create these tools to enable that that cross coverage when we do have a shortage of people.