The Digital Transformation in Public & Private Markets
Nidhi Singh, Chief Product Officer from Charles River Development, and Jason Adams, Head of Platform Strategy and Platform Product Management from Charles River Development join together to discuss the digital transformation happening for investors in both public and private markets.
Kali Jakobi:
Welcome to Data Disruption, a podcast all about data problems, solutions and innovations disrupting the private markets. I’m your host, Kali Jakobi. Let’s talk data.
Hey everyone, and welcome back to Data Disruption. As always, I’m your host, Kali Jakobi, and today I’m joined by not one, but two incredible guests. We have Jason Adams, Head of Platform Strategy and Platform Product Management, and Nidhi Singh, Chief Product Officer from Charles River Development. Jason, Nidhi, welcome to the show.
Jason Adams:
Thanks, Kali. Great to be here.
Nidhi Singh:
Good to be here, Kali.
Kali Jakobi:
Today we’re going to be talking about the digital transformation happening for investors in both public and private markets. Can both of you give a quick overview of your companies and the technology and services you offer? Nidhi, we can start with you.
Nidhi Singh:
Sure. So, as many of you probably know, Charles River Development is a financial technology firm that’s predominantly focused on front office services that caters to asset managers, wealth management. About four years ago, when it was acquired with State Street, the vision and the goal was to really have front to back offering across the multiple segments. So Charles River enables our portfolio managers, as well as the investment users in the financial market space to be able to do a end-to-end, seamless, front to back offering. As part of us having the partnership with Mercatus with the last year’s acquisition, it clearly continues our vision of looking at the different segments and ensuring that we can get not just the front to back on one segment, but really looking at how the investors are looking the space, whether it’s on the institutional space, wealth space, private market space. The CRD’s goal is to really look at that from front to back and provide those services from end-to-end connectivity, end-to-end features and functionality, and then taking it to the next step on not just the multi-asset, but the multi-segment view from a investment management perspective.
Jason Adams:
Thanks, Kali, and thanks, Nidhi, for that introduction to Charles River. Where Charles River is focused on where Nidhi had noted in the public markets and front to back, Mercatus (now Charles River for Private Markets) is an investment data management platform focused purely on the private market segment. It is really built for that private markets’ manager who’s focused on multi-asset class portfolios within privates. So we focus primarily on data collection, consolidation, data orchestration, data assurance and oversight. What that really allows that manager to do is to focus on those primary needs of deal management, portfolio monitoring, asset management, valuation management and reporting use cases like ESG and investor reporting.
Kali Jakobi:
So let’s dive deep here on technology for investors in both public and private markets. Can you tell us a little bit about how multi-asset managers solve their data challenges? As a more public market investor who are pursuing private funds, how is that changing the landscape for your technology?
Jason Adams:
Well, I guess I’ll jump in and go first here because I think there’s two parts of this question around how are multi-asset managers solving their data challenges. And then aside to that is how those public market investors are pursuing private funds. In addition to public, how you’re looking at a holistic book. I would say that it’s a big question and I would focus really on what is the state of the industry today. Honestly, it’s not very attractive, but most managers are managing these portfolios with Excel spreadsheets and email still today. You might have a couple of point solutions thrown in for the mix for a given asset class or a strategy, but what we saw five to seven years ago of simply doing a data transformation project inside of your firm and looking to just get all the data into a data warehouse and put a BI tool on top of it, it’s just not working.
One of the insights that I’ve seen, and Nidhi, I love to get your take on this as well, is one of the biggest challenge is not actually the technology, it’s fundamentally getting consensus internally on what datum actually matters and what story does it need to tell and getting all of those different asset class owners and BU heads and all of that to agree on what we need before you can even insert technology there to help with that journey. What’s your take on that, Nidhi?
Nidhi Singh:
That’s a very good point. Look, I’ve been in financial markets for almost all of my career, dating myself back from when I used to trade on the floor, where data is always the underpinning of everything that we do in financial markets. I think, Jason, your point is pretty valid. If you go back and look at the cycles of what the initiatives that the companies have always used, like “Oh, we’re all going to go and do data transformation and we’re going to solve for this data problem,” and if you look back, and I’m sure you’ve done it in your career, I could go back and look at it, just say you start a career, you start a project and two years down the road, it’s like, “Oh, it’s too difficult, too hard,” and almost always comes down to, “Well, our technology just can’t do it.” And it’s really not technology.
I think your point is very valid. When you look at data, what does it mean to be data, data for financial markets? Is this a security type? Is it the volatility and risk profiles that I need to look at? What type of personas that different users have in the company look at the data and interpret data very differently? It’s not an easy problem to solve. I think what people are realizing is it’s easy for us to say, “We’re going to have a data solution for multi-asset platform that crosses multi-segment.” Well, that’s a lot of things in one sentence, but look at the projects that we’re working on ADP, even those are a bit challenging because you start to bring in to say, “Yeah, I can build a technology on ADP built on snowflakes and have all the latest technology that I can put in.” But it comes down to even as simple as what’s an entity? A PIMCO entity in Goldman could be depending on the business you go to is viewed very differently, set up very differently.
So, I think it’s really a normalization of that data. I think where technology can help is a creative solution of how to not push the businesses to transform completely, but be able to translate that data. But the underpinning of that is going to be you need those data scientists and you need those data analysts to be able to look at those data and interpret it to say, “Okay. An account in your world looks like this and in this world looks like this.” But at the end of the day, we need to normalize those things. I think where we can from a technology and a FinTech provider can really solve for those is if we venture into that. That’s part of the reason why even the organization, the way we’ve set up is to really have those SME experts that understand those personas, those data profiles and take that and then work closely with. It’s a lot easier for technology to be built, even to provide that flexibility if somebody actually explains what you want it to be today and where you think it’s going to evolve two years, five years down the road.
Kali Jakobi:
Both of your answers to that really got me thinking about a conversation I was having with one of our clients the other day, and he really talked about how difficult the process was for his internal team when they started adopting technology because he didn’t even realize that they didn’t know what they needed to track and things like that. So it was a lot of internal debate before they could even deploy technology, which we definitely see more often than not.
Jason Adams:
Yeah, 100%, Kali. I think that everybody wants to rush to getting all the data into one place. This is all your integrations and point management solution and interval of alignments of, “Am I collecting this quarterly or monthly or daily?” And then accelerating all the way to advanced functions, like predictive analysis and trend analysis and full data lineage. These things sound great, but where to your point and to the client that you’re talking about’s point, people get stuck in the middle and it’s not that whiz-bang. It’s getting consensus internally on what matters and identifying the most important rules and assurance rules and data quality rules you need to play by by asset class. Getting those two things done is a large bulk of the effort, and the technology platforms that we build and bring to market are going to help with the rest. Hopefully, by being a trusted advisor, we can accelerate that process too and help guide our clients in the right direction, but those are definitely the biggest challenges that I see.
Kali Jakobi:
Absolutely. So, let’s talk more about the digital transformation journey for an asset manager or owner. There’s a lot of options out there that we’ve already chatted about, but you could either build a system, partner with technology consultants, buy platforms like offered by CRD. So, what are your all’s advice for CFOs and CTOs trying to navigate the beginning of this?
Nidhi Singh:
I could give my perspective. I think people may look at it selfishly since we’re in the FinTech business and solve for that, that it’s always difficult to build. But I can give you my perspective, having one of the unique things that I feel that I bring to the table is I’ve been on both sides. I’ve been on the customer side. I’ve been at banks like Goldman and Deutsche Bank that basically deals with the data problem across departments differently. I’ve worked at FinTech firms and startup firms, right? So I think it ties into the first point that we were just talking about, right? The simple answer is going to be it’s always going to be difficult to build something internally. The reason for that is think about if you take any clients, at least I could tell you from public side, I’m sure even as we are working on the public to private, but if you take even one segment, the number of touchpoints and the different data sets that you have is not always just all in-house.
It would very easy for you to build and software it if you built everything from scratch in-house. But you have Bloomberg. You have MSCI. You’ve got Axioma. You’ve got providers like CRD. I don’t think a company and our clients, that’s not their bread and butter. They need to have data that can enable them to run their business better. Should they really be spending their technology dollars to build all these connectivities, scrub this data versus actually saying, “Look, we’ll have a smaller staff that can integrate with the rest of our systems, but let somebody else deal with a lot of the integration.” Just working through and looking at the projects that we have today, and Jason alluded to it, it’s a lot of effort to even scrub and clean that data.
I always tell our clients when we talk about it to say, “You do have to have the right partners, but a good FinTech provider is not just bunch of techies who can just build a latest and greatest technology. It’s a combination of really good technologists that are paired with really good SMEs, right? You can actually have those subject matter expertise that do this day in and day out,” right? For a FinTech provider, our P&L and our revenue is to make these products better. When you look from a client perspective, they’re the expense, right? You want to look at the expense at the lowest cost and partner with someone who can provide those solutions. So I think my approach has always been structure your product organization and your financial technology organization in such a way that you can actually understand those problems, work with clients to solve for those data challenges that we talked about in just a short while ago, and then build a really good technology that can service that.
I think that probably answers the question at least from my perspective that it’s always difficult. I’ve seen firms, including when I was Goldman, to try to solve for these in-house, it’s near impossible because vendors will evolve and you have to keep adding and keeping pace at it. In all fairness, subset of these datas are commoditized, right? In essence, once you can figure that out, there is not… There’s a unique way of interpreting the data, but the underlying data is still the same, and it’s just a matter of publishing and storing and archiving and providing those data sets to the clients is where I think a client should look at a good partner that can actually have skin in the game to provide that technology suite and product suite to solve for those problems.
Jason Adams:
I’m going to piggyback off of one of the points that Nidhi just made around tech-enabled services or tech-plus services. One thing that I always take a look at is no one’s ever going to in the FinTech space, specifically in the space that Charles River operates in going to deploy software and then never touch it again. Clients are never going to be successful and there’s a lot of reasons for that. I can speak to the private market landscape today. The data collection complexities alone across many of the common asset classes, private credit, real estate, technology simply can’t solve it today effectively. So it requires technology, it requires services and it requires that subject matter expertise that Nidhi was mentioning.
Another aspect that I think leads to this challenge of the journey that an asset manager or owner is going to take as they look to build versus buy or partner is the technology skillsets that you need in order to harness and actually bring to market, whether it’s a bespoke system internally or something broader with bigger aspirations. I think you’re going to find that running a product and engineering organization as a wholly internal FinTech firm is difficult, right? To do it right, you’re not going to be able to do this with just a couple of analysts and someone who knows Python. It’s just not going to work. You need to have true backend developers, front-end developers. You need to have infrastructure engineers that can manage your clouds in multiple geographies.
That’s typically what we also see not thought about when you think about the build versus buy conversation is you might be able to build something that’s very, very opinionated for what you need to do inside your firm. However, what I see that tends to get ignored are the flexible aspects of the technology, so being able to handle the unknown use cases, being able to onboard effectively a new asset class that might be in an emerging market, and then basic things, like how are you handling permissions and access control to data across your firm or you can’t just let everybody have access to everything. Now, you’re starting to build into platforms and that’s expensive and adds compounding maintenance efforts. How are you going to handle resiliency, right? A lot of the commercially available public product, such as Charles River, we’ve spent tremendous amounts of investments making the service resilient be able to fail over across geographies, have SLAs with 99.9 and insert the number of nines you want on the back of that. These are items that you typically don’t see on in-house built tools.
Kali Jakobi:
Before you know it, you’re building a technology company within your own company and that’s just… No one has the true budget for what that is. So I know we’re seeing a lot of CFOs beginning to hold back on larger technology purchases and deals due to economic uncertainty. That’s the elephant in the room in just about any conversation you have these days. Can you tell us a little bit about what you’re both seeing from clients, and how should investors be thinking about technology right now?
Jason Adams:
I’ll take a crack at this one. I have been having many conversations on this matter as it’s the topic of choice and the client that we sit in today. I understand the risk and concern. Capital expense and capital investment projects are typically the first to go in an uncertain economy. However, not making a move could be a devastating decision as well. So one thing that I keep pointing towards is that regulatory pressure and LP requirements to push GPs into further transparency demands is never going to subside and it’s just increasing because of that climate. So shuffling your staff around on reporting tasks and validation efforts is really expensive, and people, no matter what, are always going to cost more than the technologies that you might deploy.
So, my recommendation to a CFO or a CTO at a firm would be that you would want to hedge with technology to give your business really the opportunity to meet those increasing compliance obligations without adding headcount, to give the firm an advantage via technology to adapt to new and emerging asset classes and to diversify into different asset classes that they may not be serving, and finally to provide more transparency and give yourself a competitive advantage to LPs if you’re a manager, to be more competitive in closing new funds and managing those funds more effectively, you become more competitive in the space.
Nidhi Singh:
I’ll piggyback off of that and maybe everything that you said is probably applicable in public space as well, but I think maybe slightly different perspective in the sense that if you think about at least on public space or institutional space, people have for decades now have outsourced their services and part of the reason why you outsource those services is because it’s a cumbersome job that’s not part of what you want to do. If you think back whatever, 20, 30, 40 years ago when perhaps technology was not at the forefront in financial markets, if you ask anybody today to do their job effectively in financial markets, it’s powered by technology. That doesn’t necessarily mean that you turn into a technology firm. I think that’s where it’s the same point that Jason make, but maybe a slightly different perspective to think about to say when you look at your business case, technology enables your business to grow and you want to be able to partner and you want to look at the technology and see which components of those can you outsource or which component of those can you actually partner with somebody.
So, in one sense, there are certain things that a firm might say, “Look, I want to have that as my core proprietary system and I want to be able to have those pieces.” I always say having done post-trade and the back office perspective, and I always tell people it’s like clearing is going to be clearing. You’re not going to modify the world by building your own clearing system, which is hard and difficult. It’s the same thing from portfolio management perspective, you have certain risk models that’s going to be certain risk models. How you interpret those and how do you do some of those, take that data and create the model analysis is what changes and what sets you apart.
I think the decision really is what Jason said, right? You want to have your technology not as something that you always have to constantly worry about as part of your P&L, but something that you can partner and say, “How do I optimize my cost? How do I partner with firms like CRD that actually have some of the core offering that I can integrate with something that can enable my users and my business to grow and scale much faster?” Whenever we talk to the customer, I generally say, “Do a comparative analysis and see if you were to build everything, what your profit margin and operating model is going to look like versus partnering with someone that can actually continue to enable you to do that.”
If you take the example of somebody who has for an office applications and all of a sudden they want to get into a private space, it’s easier for them to then say, “Hey, CRD, now that you have partnership in private markets, how are you going to enable that?” versus them having something on their own and now they’ve got to start a brand-new initiative to say, “I’ve got to integrate something.” So I think technology is an enabler. I do think that they have to embrace that as part of their business model, but it’s something that always going to be an impactful thing for their P&L and really needs to be looked at from that operating model and P&L perspective.
Kali Jakobi:
From a forward-looking perspective, I’ve heard a lot of discussion about how investment data platforms will evolve with emerging technologies, such as machine learning, tokenization and blockchain. I mean, I just talked to Jay about this last episode. How do you guys see this space progressing though over the next five to 10 years? What is your all’s opinion on that?
Nidhi Singh:
I can give my view. Look, I think there are areas where some of these things are very immature currently that needs an evolution, but I think there are areas around that actually can benefit. I think when we look at it from… If we go back to our data conversation, there’s the aspects of data and how you analyze it, and that’s, I think, where the machine learning or AI models can actually learn and continue to evolve. To me, I think the benefit and where I think it’s going to be very useful going back to the operating model and expense ratios and reducing that footprint of the cost is, “Look, you can have our staff.” It’s not just about your portfolio managers, but it’s about the operations staff that you have. Can you make them a bit more efficient? Wouldn’t it be nice for them to be able to just do a quick query to say, “Give me everything in terms of portfolio risk models that were higher than 10%”?
Right now, it takes enormous effort and it takes a lot of challenges within the operations team. So I think as a industry, there is definitely benefits of the areas where we’re going to grow. I think the AI models, the natural learning and the machine learning, that can help support not just the investment managers, but really taking that data and making it easier for them to run queries, bringing it more real time and interpreting that. I think I’ll make very quick point around digital space where we all look at it and we all think about where it’s headed. The reason why I said it’s at the infancy is it’s going to have to be balance of regulations and technology.
Again, it goes back to our first point of we could build anything in technology, but sometimes 100-year-old trading model, to transform that into a very different way of looking at it, is going to have a view from a regulator’s perspective so that you don’t have some of the things that you’re hearing news today in terms of digital market. But I think it is a different way of looking at it and I think it’s definitely there. Some things I do think is going to be probably in the next two to three years you’ll hear a lot more about AI and natural language and you see a lot of the chat bots and a lot of the things that I think has got a very applicable thing for portfolio managers for our operations stuff, and there’s going to be things that’s going to be much further down the road.
Jason Adams:
I’ll go off of the AI point and I’m the technology curmudgeon probably in the room, or I guess I’ll call it the realist. I think a futuristic lens and embracing and moving towards general AI is fantastic. I mean, we can all dream of days when you can send any format of any data into a neural model and it’ll come out and have context to know exactly what it means and the intent is, and then just go ahead and populate your data warehouse with the according data. That’s fantastic.
Kali Jakobi:
What a world. Yeah.
Jason Adams:
What a world. But honestly, we’ve seen capital call requests on napkins in the private market space. I’m serious. So I think we’re a bit far off until we can get some standardization that’ll help drive some of these technologies there. But I do think that there’s aspirationally moving towards concepts such as digital twin, where you can have a true digital representation of a tangible asset, like an infrastructure asset, for example. How is this airport in any given geography going to fare as it relates to natural disasters, economic disruption, war, et cetera? Not only that individual asset, but modeling down to those granular pieces and components. You can see though that portfolio might go in those scenarios.
But I think something that a little bit less sci-fi and far out that I think is probably realistic is as we look at public to private views and as we look at the private markets maturing a bit and we start to see some inklings of bright spots of standardization and a language that we can all talk amongst ourselves in that means the same thing, I think we can start to use some technologies like distributed ledger systems and standardization of data agreements to drive something like consumer participation in private market asset classes. I think that’s really exciting because I would love to see a day when you can go into your preferred brokerage account and be able to not only participate in ETFs and stocks and bonds, but also be able to make direct investments in a school building in South Africa, for example, because you think the economics are there and you can see the models and you can put a micro-investment towards that as a consumer. I think that day is probably closer than we think.
Kali Jakobi:
So many things to come in the future. I can’t even personally fathom the capabilities that we’ll have. Well, Jason, Nidhi, thank you guys for joining me today. That is all my questions for the data side of things, but I always like to end my podcasts with a personal question and that for you all today is if you could travel anywhere in the world right now in this moment, where would you go and why? Whoever has their answer ready can go first.
Jason Adams:
For my answer, I might need a little bit of prep, just at least pack a bag so I don’t die upon arrival. But I’ve always been fascinated with the raw landscape and beauty and challenge of Alaska and that’s probably where I would want to go.
Kali Jakobi:
Yeah, you definitely need to pack for that one.
Jason Adams:
Yeah, I wouldn’t want to be dropped there right this second, even though I’m sitting here in my Midwestern flannel, I don’t think it’s going to be sufficient. But no, I love the nature, the raw, untapped beauty and the challenge. We as humans and people are always drawn to challenges and being able to be in that element and to face all those is exhilarating and something that I would be passionate about and love to drop myself into right now if I could.
Kali Jakobi:
What a great answer.
Nidhi Singh:
When you asked me about it, I had two different things. One was if I could travel anywhere, my favorite country by far has always been Japan. It’s probably similar to Jason’s raw beauty and I’m a big foodie, so just being able to go and do the mountain hikes and go to the rest stops and being able to have a really good meal at the end of the day. I think Japan, just the sheer nature of their perfectionist, every little thing has to be just right. It’s not often that you have a country, where it’s like, “I just sell eel and that’s it.” It’s like, “Okay. Well, you get a small one, medium, one large one, that’s it,” right? But they do a really good job.
But I will cheat and I will say if I had the choice, the only other reason I would give up traveling to Japan is we are all well aware of the climate change, and one of the things that I’ve always wanted to do, and it is on my list is… Before I joined CRD, I was actually supposed to go to Antarctica, not just on a cruise ship, but actually go to Antarctica research station to be able to do some of the ice climbing and spend time with the penguins. If I had to pick something… Those glaciers are not going to be there. People always tell me, it’s like, “Oh, it’ll be there for your lifetime.” It’s like-
Kali Jakobi:
You never know.
Nidhi Singh:
… you never know. I think that would be just similar to Jason, I would have to pack. But I think push comes to shove, I would probably pick Antarctica and do my trip where I could just go and look at the white desert and just the sheer isolation of that part of the world that you generally don’t see. It’s always amazing how there’s certain things and certain people who can survive in that environment.
Kali Jakobi:
Yeah. Wow. You guys sound like some great travelers. I am so glad I picked this question with for you all. I would have to say I’d love to be just dropped at the top of Half Dome in Yosemite if I could. I’ve done that hike before and it is quite the trek to get all the way up there, so if I could just skip that part and sit on the top. I’m not really one for heights, so that hike definitely gets your stomach turned in if you’re not a fan of heights. Well, thank you for your travel recommendations and imagination there. Thank you all for your expertise in the data space, in the technology space. If anybody has any follow-up questions for Jason or Nidhi, I am happy to connect you. That’s all for this episode of Data Disruption. Till next time.
Jason Adams:
Hey, Kali, thanks so much.
Nidhi Singh:
Thank you, Kali. It was a pleasure to be on the podcast.
Kali Jakobi:
Thanks for listening to this episode of Data Disruption by Charles River. If you like what you heard, share and leave us a review. It helps others discover the show and I thank you for it. If you like additional insights related to this conversation or others, go to our website at www.crd.com. Till next time.
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The material discussed is for informational purposes only. The views expressed in this material are the views of the author and are subject to change based on market and other conditions and factors, moreover, they do not necessarily represent the official views of Mercatus and/or State Street Corporation and its affiliates.