Everysk CEO, Allan Brik, joined Beyond Alpha, the #1 podcast for ops leaders in investment management. Brought to you by Enfusion, Beyond Alpha is hosted by Labib Mahfouz and features the top talent in the industry discussing everything from front office investment trends to back office best practices.
In this episode, Brik and Everysk client, Jason Beckett, of Dynamic Beta Investments, shared their thoughts on the Power of Interoperability. Enjoy the video below or keep reading for the full transcript.
Full Transcript:
Labib Mahfouz: Hello, I’m Labib Mahfouz and this is Beyond Alpha, the podcast by and for leaders in investment management. On this show, we sit down with top talent in the industry to discuss everything from front office investment trends to operational best practices. Today we will be speaking about investment management and interoperability, and today we’ve got Jason Beckett and Allan Brik joining us. Maybe we could start with some bios and intros.
Jason Beckett, DBi: Sure. Jason Beckett. I am the Chief Operating Officer and Chief Compliance Officer of Dynamic Beta Investments (DBI). I’ve been in the business since the late 90s. I started at Greenwich Capital in operations supporting the treasury teams and moved on to plenty of time at a hedge fund ranging from operations to trading, and then moved on to DBI. The opinions I’m about to express are my own and not representative of DBI.
Allan Brik, Everysk: My name is Allan Brik. I am the CEO and founder of Everysk. Everysk is an automation company. I’ve been in the business for 30 plus years, including stints at Merrill Lynch and Goldman Sachs. I was a CRO at a fund of hedge funds called Arden Management prior to founding Everysk.
Labib Mahfouz: Excellent, well welcome both of you. Look, interoperability I think for a lot of people can mean different things but to me it’s a front-end tool or it’s an application to allow users to be able to pull different sources of data into one front-end application whatever that is and that seamless integration of data across different platforms across different technology tools. You know Allan, maybe we could start with you. How has the technology world changed, especially in the investment management space, where this becomes more and more of an important tool and more of what Everysk is really working on with his clients?
Allan Brik, Everysk: Sure. I think the main change has been cloud computing. Really, I think that this industry has been served by technology that is more siloed. Prior to cloud computing, it worked really well but then data became captive in different parts of the company. With cloud computing, you can use APIs, you can use different techniques to kind of break those silos and really have a unified golden source of data which is critical these days. So this shift from monolithic providers to more modular providers has been a game-changer and I think that’s very important, especially with machine learning and having vast amounts of data. You need to be able to really break the data silos.
Labib Mahfouz: Now, while different technologies are modular in nature, starting with that single source of data, a clean bit of data is instrumental in creating a smooth process?
Allan Brik, Everysk: Yes, I mean absolutely. You need to have new technologies that are very connected. The way that this has been built by protecting your turf and not opening the gate doors has changed completely now. I mean people have to be connected. Your technology has to be able to ingest data from different places, it has to be able to process in a modular fashion, it needs to be able to distribute the data to stakeholders and be completely open. I think that it’s changing. A lot of companies now are really valuing that, being able to have modular infrastructure that will change as the firm evolves. I think that’s one of the other aspects of having a monolithic approach to this is that it served you at some point in your client and firm evolution but then as you evolve in time, you had to rip everything apart and rebuild everything. Now you kind of change modules and in a very efficient way, the technology will adapt as you grow. That’s the main aspect of interoperability that we’re talking about.
Labib Mahfouz: Now for DBI, that’s crucial across the investment management lifecycle of a trade and transactions. What are some of the tools that you think are important where maybe helping you on the operation side or on the compliance side where being able to quickly real-time or almost or near real-time, not end of day, not batch processing, you’ll get it tomorrow at 10 a.m., the batch is late, it’s 1:00 and everybody goes out to lunch and comes back and hopefully you…I think the cloud computing on one side and the speed of calculations and of course interoperability in and of itself has allowed, I would imagine, your world to be tremendously more efficient.
Jason Beckett, DBi: It’s the single source of data that you were talking about and the ability to trust that data and know that it’s correct. You know, as an investment manager, we face increased regulatory scrutiny, increased calls for transparency and reporting to a variety of investors. There’s fee compression so you can’t throw as much money at solving a particular problem—money or people. Money or people, and people you know are money at that point. So having one source that you can look at and pull all of your data into one place is extremely important to do all of that reporting.
Labib Mahfouz: Let’s break this down. Let’s start with portfolio analytics. What are some of the tools that you feel are needed in order to either pre or post trade, looking at your portfolio? How has interoperability helped the industry as a whole be able to assess risk?
Jason Beckett, DBi: Well, you kind of nailed it actually right there with the pre and post-trade compliance reporting. Investors are looking for that, the regulators are looking for that, and if you can have reporting that pulls together all of the information that you need, whether that’s investment guidelines or regulatory requirements, and be able to trust that data when it’s produced before you need to execute your trades, that’s really what you need to run an efficient operation. Obviously, there’s compliance risk, which is on everybody’s mind always.
Labib Mahfouz: And then there’s obviously mitigating market risk. And so, are the tools different? Is the process different?
Jason Beckett, DBi: I think they would be almost the same tools. I mean you really want all of your reporting to be in one place. I don’t need to worry about if what’s producing my pre-trade compliance and what is producing my regulatory reporting is pulling from two different data sets. I need to know that those are looking at the same set of data and that that data is trustworthy and it’s coming from a good source.
Labib Mahfouz: Understood. You know, on the back of that, speaking of risk, there are different portfolios, different strategies. We’re in a world today where that single strategy investment manager doesn’t really exist anymore. We have some, but it’s that multi-strat, even multi-manager, and you may have the single source of data but risk is calculated differently. Different risk modules are needed depending on the different asset classes you trade in. How has that evolved? You’ve been in the risk space for a very long time.
Allan Brik, Everysk: As you mentioned, strategies evolve. Right now, private credit is huge and it’s more of an operational perspective than your traditional market risk. It’s really looking at cash flows, expenses, balance sheet, and we address that in automation. So you have to evolve and address different markets. Private credit is more operational. Multi-strategy, different types of strategies are more market risk. A big change in firms that are managing money, is to be less reluctant to outsource these aspects of their business. It used to be the case when I started that you could never outsource. You know, trade compliance or risk or, margin optimization or staging trades—any aspects of your trade lifecycle—and now it’s more and more companies can be comfortable doing that:outsourcing everything that’s outside the alpha creation. So I think this has changed quite a lot too. I mean, it was inconceivable when I started for a hedge fund, for example, to outsource many aspects that now they’re very comfortable outsourcing.
Labib Mahfouz: It’s interesting to me that just about every episode we’ve recorded, outsourcing inevitably becomes part of the conversation. And regardless, I mean, everything aside from idea generation. How have you seen that change and how has that helped you and the team to become more adaptable, more scalable, more efficient? Are you seeing that you’re outsourcing things that you just never would have outsourced before?
Jason Beckett, DBi: I’m a huge fan of outsourcing. You know, going back in my career, in the early 2000s, if you wanted to set up a hedge fund, you needed to get an IT department, a compliance department, a finance department—all of those people. And if you were launching, you would need 15 to 20 people really to run the business, if not more. With the ability to outsource and choose best-in-class providers these days, and have a choice of a lot of different providers, you can find those best-in-class providers. You can outsource pretty much the entire business outside of that idea generation. And the ability to outsource that, you can get expertise that would be potentially impossible to find in your local geographic area, plus the savings of not having to manage 25 people and the brain drain that comes with all of that necessarily. Then, Allan, on your end, that’s an opportunity in the sense of, you know, you’re no longer really working just for one firm. You’re able to apply the same tools that you’re building out—they’re customized by client—but different firms are able to utilize those tools, whether it’s yourself or any other outsourced provider for that matter.
Allan Brik, Everysk: Yes, absolutely. I think that when we started, it was really very much a client-driven approach. I mean, we were out there and wanted to look at that series of pain points and incorporate them and try to solve them with technology in a modular fashion. And when they became repeatable, they became use cases that were packaged as modules, as products. So yes, absolutely. All those aspects that are very mechanical and mundane can be automated and should be automated so that you don’t spend 8 hours a day doing those things. The machines will do that in 10 minutes, and the rest of the day is left for very useful added-value things.
Labib Mahfouz: Let’s talk about, you know, shifting a little bit, redundancy and knowledge concentration. Interoperability, how does that solve for that where you’re able to, you know, perhaps not depend on that one operations person or those two risk individuals? How have we seen interoperability really make investors and the investment manager a little more comfortable in how they run their business?
Jason Beckett, DBi: I think right now what you’re seeing with the ability to share data back and forth is that your risk system could talk to your order management system and they can communicate, let’s say, those pre-trade or post-trade compliance rules. And they’re able to communicate that clearly as opposed to, you know, 20 years ago when each of those would have their own individual feeds coming to maybe that one junior trader or that one operation person. And they were having to pull that all together and make sure that you’re on a spreadsheet and make sure that your rules were all correct and you were passing all of your pre-trade checks. And so it allows, I guess, one redundancy and obviously, you’re able to scale—you don’t need to hire more individuals.
Labib Mahfouz: But does that increase risk in your reliance on providers?
Jason Beckett, DBi: To an extent. And the counterpoint is that you really need an enhanced vendor due diligence process. You can’t just rely on going out and finding one vendor and deciding that they’re the best one. You need to do annual risk-based assessments of all of your vendors, enhanced cybersecurity if they’re dealing with, let’s say, trading or other sensitive data. You need to make sure that you’re not tied to one vendor, that if something’s not working out, you can easily cut the strings with them, move on to the next, and just not get bogged down there.
Labib Mahfouz: Along those lines, when you’re looking at the transition of your career from a risk manager for a single firm or a fund or fund of funds and then moving to essentially risk and interoperability across the spectrum, what due diligence hurdles do you feel you guys need to go through? What are investment managers and asset managers asking?
Allan Brik, Everysk: Yes, we had to go through a vetting process and our baptism happened with our largest client. And that client is a public company, largest asset manager in the world. And so we went through a very stringent vetting process that we could cope with scale and we could perform on our technology and grow with them. And I think that prepared us for the next large client. And, you know, to work with clients that have sophisticated and complex requirements doesn’t happen overnight. It is a lot of sleepless nights and white hair. But yes, I think that it’s a process.
Labib Mahfouz: When you’re speaking to your investors, what risks are they concerned with? What do they see that you’re looking at outsourcing that they feel—what are the risks and what if that business disappears the next day? How do you address that?
Jason Beckett, DBi: We have to go through what our due diligence processes are with them, what we did with the onboarding, how we looked at different investors, how we got comfortable with the process. Let’s say a risk provider is providing or an OMS provider, and what sort of checks they have in place themselves, how the information flow is working, whether it’s set up with an API where it’s seamless or there’s an email flow back and forth or something older like an FTP, or what the technology is like and getting them comfortable. In some cases, we bring in that outsourced provider into a due diligence meeting if we’re having those to discuss their background and the information about their firms.
The other thing—Allan touched on it a couple of minutes ago when he was talking about a very large client. I think you’re seeing a lot more outsourcing from the big asset managers, and that’s made everybody a little bit more comfortable with that process. Twenty or thirty years ago, that did not happen. There were hundreds of technology people that would be supporting a large business.
Labib Mahfouz: Right. And so when investors see a large company or a large asset manager utilizing these tools, they become more comfortable. It all flows downstream. When you’re looking at trade processing and trade flow, what are the first things that you’ve looked for where interoperability was the most important to you? Was it creating the front office front-end tools for risk managers and traders and portfolio managers, or was it on the operation side, or was it on the compliance side?
Jason Beckett, DBi: We look at a lot of it together. Once the decision has been made to trade, everything sort of needs to be tied together from that one decision through the settlement of the trade. You need to have your investment guidelines in one place, your pre-trade compliance rules in one place, and your execution. Let’s say if you’re a systematic strategy, you want everything to be as automated as possible, and all of those different systems need to be speaking clearly with each other all the time to avoid any hiccups.
Labib Mahfouz: Go-to-market strategies—has interoperability affected your firm’s opportunity set in being able to go to market with different products or different strategies a lot faster than in the past, given the technology stack they may already have?
Jason Beckett, DBi: From my perspective, I would say it has. In the old days, you would have to go out and make sure that your developers knew what the products were, knew the ins and outs of everything, or hire new developers. In this case, I can go to a vendor that I’m using and say, “Hey, this is what we’re going to be doing,” and I’m going to rely on them at that point to bring the expertise in-house. So we’re relying on the experts that we’ve hired as outsourced providers.
Labib Mahfouz: Now, on your end, there’s a world where people create the experts—they’re not actually individuals at all, but they’re, you know, you call them robots or processes where you’re able to kind of recreate a function and repeat that function over and over again endless amounts of time. How has that changed how investment managers look at their portfolios and how they run their operations?
Allan Brik, Everysk: As you mentioned, you can codify these things and call them digital robots. There are many names that you can call this—processing units. It’s really powerful if you can interconnect these processing units, and all of a sudden you have a very robust replacement for spreadsheets. Spreadsheets are really good; I’m not going to bash spreadsheets here, but they work to some extent and up to some amount of complexity, and then they break. In compliance and risk, if you deal with multiple funds and your firm starts to become a bit more complex, you really cannot rely solely on spreadsheets to do the job. We go into places where it’s incredible the amount of spreadsheets that they rely on to do very critical pieces of their jobs.
Labib Mahfouz: And saved on a server, right?
Allan Brik, Everysk: Exactly. A local server. The main thing right now in firms that we talk to as part of their digital transformation is to eliminate what they call an UDT—a user-defined technology, which is the spreadsheet. Something that was written by an individual to solve a topical problem, but it’s a black box ultimately. There’s a huge effort right now in firms to decrease or eliminate this technology liability. Firms are really embracing consolidated data, APIs, machine learning, and automation. Those are coming to the fore because companies are acutely aware that a single source of knowledge in a spreadsheet can be very dangerous.
Labib Mahfouz: Are you seeing this just on the investment and asset management side, or are the banks and side firms also present in this space?
Allan Brik, Everysk: It runs the spectrum, definitely. Everyone has a concerted effort right now towards digital transformation. Everyone needs to modernize their infrastructure across the board. You ought to be thinking about automation if you’re starting your management firm, wealth management, or other money management firm. If you already have one that has grown over the years and you are captive to some different monolithic providers, you ought to be thinking of ways to put a layer of automation or some intelligence to connect these different silos and try to bring the information to one place that you can manipulate easily.
Labib Mahfouz: In today’s world, keeping up and keeping pace is super important—new technologies, new rules, new strategies. Where does interoperability fall in that space where I have a fixed data set and a data stream, where I have a central source of data but now I need to buy another tool or outsource to a new provider that never existed before? What questions should a chief technology officer or a COO ask when they need to pull in a new tool, and interoperability is paramount in them running their business so that they know that tool can adapt and be configured to their existing tech stack?
Allan Brik, Everysk: First and foremost, connectivity. The new technologies are API-centric. You need to be able to talk to different technologies; you can’t be isolated. The second main aspect is scalability. The cloud gives you this for free—you don’t have to buy new servers and put them in the back room. You can just instantly create a new farm of servers in the cloud and gain scalability very quickly. The third aspect, which I particularly like a lot, is to enable these technologies to be very modular. I build something that you can compose, drag and drop, and solve different problems with the same modules just by configuring them a bit differently. That type of adaptability is important because firms change. A firm that’s a $2 billion firm is very different when they reach $10 billion—they have different requirements, different products, different markets. So I would emphasize scalability, adaptability, and connectivity.
Labib Mahfouz: Jason, what are your thoughts there?
Jason Beckett, DBi: Allan nailed all of that. I was thinking about time to market in terms of scalability. When you need to comply with a new regulation or a new request, like when there was the 18f-4 reporting that came in from the SEC, being able to go to a provider and say, “Can you guys put together this reporting? It’s critical, it’s a crucial reporting requirement, and we need to get it done quickly and accurately,” having a provider that can do that is very important to us.
Labib Mahfouz: So it’s about pivoting and scaling and speed. Speed to market, making investment decisions, or building out investment processes faster so that you can make better decisions sooner seems to be a recurring theme across a lot of the episodes we’ve had. One area that everyone is speaking about is artificial intelligence. It’s really hard to avoid, and really the distinction between machine learning and artificial intelligence sometimes gets comingled in the same conversation. But I’d like to split that up, and if you could share a little bit about your thoughts on machine learning first and then how that transforms into artificial intelligence, what you’re seeing from clients, and what people should be thinking about as they build out their business?
Allan Brik, Everysk: There is definitely a distinction. The way I see it, machine learning is a subset of AI, which is a discipline. Machine learning is primarily statistical approaches to deal with complex data like multidimensional, non-linear data. The more data you present to this non-linear, multi-dimensional problem, it learns how to do a better job. It can be supervised or unsupervised, and you can do various things that are very good at, such as clustering information, providing forecasts, decreasing the complexity of the data. So, this is all in the realm of machine learning, statistical in nature.
And now the hottest one is GenAI, which is a subset, if you will, of machine learning. So, if you think of concentric circles, and I’ve seen this in different places, you have AI, and then a smaller circle that’s machine learning, and a smaller circle that’s GenAI, which is trying to statistically infer what’s the next best word or token in a phrase. But that has a very generic concept, which could be what’s the next piece of code that I can write given that I have all this code written up to now. So, you refeed the machine.
Labib Mahfouz: It’s not just finishing off your emails; it could be finishing off your code, finishing a sentence, or summarizing something.
Allan Brik, Everysk: I am particularly interested in finishing up your code. I like to infuse technology with these co-pilots, and that’s something I am very interested in, making sure that we can have digital robots that can create different digital robots. So, you give them a prompt, and you want to do some visualization on the data, and it basically writes the code back to you on how it got the answer. And that code is reproducible, good quality code that I can then give to you or anyone else to use. I think there are going to be enormous advances. We don’t have something that’s deployed that a client would be using. I mean, we’re doing a lot of R&D on this, but I’m particularly very excited about this.
Labib Mahfouz: At DBI, would you say that’s the next step in the investment management process? And not necessarily at DBI, but in your own opinions on where investment managers are, how they’re generating alpha, would AI be a tool to help all the backends? So, you know, this intuition of this could be a trade break, this trading behavior was inaccurate, this process, given this is what you’ve done, you should check your balances. Can you talk a little bit about where you personally would think this would all fall in your COO, CCO world?
Jason Beckett, DBi: Like Allan said, I think we’re on the R&D side of things, sort of exploring how it can be additive to our business. The fact that we like outsourcing and efficiencies and things like that. The questions that we’ve gotten from regulators, from investors, and other people have run the gamut of “Are you using it? What are your concerns around it?” to “Are you using it? And if not, why aren’t you using it? And what do you plan to do?” The trend is moving to “Why aren’t you using it?” I’m starting to see that now with some investor queries, which I was a little surprised about, but I think that’s the direction people are going in.
Right now, I think a lot of people are using it to look at how they can help with repetitive processes like Allan had talked about, like just basic coding or things like that. If it can complete that for you, or even just some of the simple language models to help with, like one of the things that we were looking at—we had talked to a provider that had their own large language models silo that we could put a whole bunch of documentation in. And then I can use it to help me answer investor DDQs, all internal. So, there’s no worry about information going out or other people seeing it; it was all confidential. But we could upload a whole bunch of information to it, and then you can fill in different questions that you were looking for. It still obviously required a fair bit of fine-tuning, and you couldn’t just produce a document and send it out. It required a fair bit of work afterward, but it was a nice knowledge base that we’re still kind of working on so you can be a little more efficient answering things like repetitive things like DDQs.
Labib Mahfouz: No, it’s funny, and DDQ really became quite more robust, I’d say, after ’08, right? And I think every investment manager has tried to find a way to simplify that process. Every investor, every allocator has their own set of questions, and they ask the same question, but the words are different. And so finding the right tool to be able to, you know, you’ve got this database of answers, and you end up spending a tremendous amount of time looking for the answer to that question because it’s been asked in a different way.
Jason Beckett, DBi: Yeah, that’s 100% been our experience. And, you know, a lot of those answers are still up here. But, you know, in filling out all of these, then you have it on paper or you have it electronically. And if you can, and you know it’s not ready for prime time yet, I would have to say, but if you can have these in a spot that’s queriable and it’s flexible like the AI is where it can account for those different twists in the language, that could be a big time saver.
Labib Mahfouz: So, so far we’ve talked about mitigating risk, compliance, operational efficiency, scalability, accuracy, and AI. What’s the future of interoperability? Where do you guys see where I could have an infinite number of different systems all speaking to each other? Does it become a tool, or does it become just an inherent part of how the business is operated?
Allan Brik, Everysk: Time to market will become very short because of all these technologies. As we mentioned here in the podcast, you will be able to launch a new product in record time, onboard the client in record time, and analyze data in record time. So, efficiency will increase tremendously, and I think a big part of this is systems that talk to each other.
Labib Mahfouz: So, interoperability will actually be implemented in each system, almost like building an extension cord where you’re able to click and very easily connect the pieces?
Allan Brik, Everysk: It could be one piece of technology that might be the glue, or not, but you could have an intelligent layer, like an automation type company, that talks to different types of APIs in different companies, and everything can be put in place very quickly.
Jason gave a very good example, like all of a sudden, you have to operate in a new regulatory regime that needs a very specific report to be provided. You ought to be able to do that in a morning and not over the course of weeks.
Labib Mahfouz: Right, I have all the data, I have all the information.
Allan Brik, Everysk: Exactly. So, dissect it, slice it, and put it together in a morning, and then all of a sudden, that whole region becomes available for you because it’s not a constraint anymore. That is the future. A tremendous amount of efficiency, and people working in the industry will be happier. There is still a very large part of what we do, what I did over my career, that was boring and mundane. You know, I had to do, and everyone has to do, a lot of stuff that is designed for computers to do really, and you can start spending your days thinking about interesting things—thinking about investment ideas and not, “How am I going to generate this 18f-4 report?”—because you know that can be done by the machine very quickly. And that’s what I think is the future, really. I think it’s a good future where we’re freeing the workforce, liberating them from this mundane stuff, really. That’s how I see it.
Labib Mahfouz: You know, I’ve always thought, and Jason, I’m sure you think about this a lot when hiring your team, you want to hire really competent, intelligent, hard working people—all the normal traits. And then they come in their first day, and you’re like, you know, back in the day it was, “Alright, you know, alphabetize these files.” And then that turned into reconciliations.
What skill sets are you looking at as you build out your team as it grows, and what skills do you think an operations leader should be thinking about when they’re looking to hire junior or mid-level individuals?
Jason Beckett, DBi: In addition to what you just said, I would add in intellectual curiosity and being able to think about how this process could be done better. That’s kind of how we’ve moved along over the last 20 or 30 years—how can we make what we’re doing better? Going from writing the trade tickets down to making everything electronic and the straight-through processing that we had to now being able to tie different systems together, and they talk to each other with APIs. So, the dedication to the job, the intellectual curiosity, and a really strong drive.
I think you can teach a lot of things, but somebody needs to be willing to sit down and look at the problem and say, “Okay, we’re going to figure out what this is,” whether that’s operations or on the portfolio management side or wherever. Those are key qualities to have in-house.
Labib Mahfouz: One area that I always stress is, regardless of all the technology and all the tools, screens can only get so big. So, screen real estate becomes very, very important where you can’t have all of these tools on one screen. So you need to look at what is that central data piece that holds all the information as your main screen. And then interoperability comes in where you’re able to show reports from other systems.
Do you think that trend will continue where screen real estate becomes even more valuable, and we’ll find ourselves in a position where it’s inevitable if you have a system, you’ve got to be able to integrate with a series of others?
Allan Brik, Everysk: Yeah, absolutely. The front office is really plagued by real screen real estate. We have been to trading floors where you have a person with 16 screens on their desk. So, yeah, I think that interoperability is definitely something that will continue. You don’t have to have all the screens. I don’t know exactly how this will pan out as we don’t tackle that part of the problem per se. But I think there will be different ways, like VR headsets that you will put on, and you’ll see more screens over you and things like that.
Labib Mahfouz: So we’ll see trading floor-like environments in your head with goggles. Yeah, the way of the future. It has been a real pleasure speaking with both of you today.
Labib Mahfouz: Thank you for having us.
Jason Beckett, DBi: Thank you.
Labib Mahfouz: And thank you for listening to Beyond Alpha.
