Trading Tomorrow - Navigating Trends in Capital Markets

Reimagining Investor Engagement Through Agentic AI

• Numerix • Season 4 • Episode 40

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Imagine an AI that doesn’t just respond, it thinks, acts, and drives results. That’s the promise of agentic AI, and it’s already shaking up the world of investor communications.

In this episode of Trading Tomorrow - Navigating Trends in Capital Markets, host Jim Jockle chats with Chris Cummings, Chief Strategy Officer at InvestorFlow, about how this next wave of automation is changing the game for private market firms. From raising funds to managing thousands of LPs, firms are turning to AI agents to deliver speed, precision, and personalization at scale.

Jim:

Welcome to Trading Tomorrow Navigating Trends in Capital Markets the podcast where we deep dive into technologies reshaping the world of capital markets. I'm your host, jim Jockle, a veteran of the finance industry with a passion for the complexities of financial technologies and market trends. In each episode, we'll explore the cutting-edge trends, tools and strategies driving today's financial landscapes and paving the way for the future. With the finance industry at a pivotal point, influenced by groundbreaking innovations, it's more crucial than ever to understand how these technological advancements interact with market dynamics. Today, we're exploring one of the most transformative shifts in capital markets the rise of agentic AI, autonomous, goal-driven AI systems that are changing how financial decisions are made.

Jim:

From predictive analytics to real-time investment insights, ai agents are ushering in a new era of efficiency and intelligence. Joining us is Chris Cummings, chief Strategy Officer at InvestorFlow, a fast-growing platform helping investment professionals replace legacy infrastructure with intelligent automation. Chris brings a wealth of experience in product and go-to-market strategy, having advised numerous B2B and SaaS technology startups. He holds senior roles in leading tech firms like Cleversafe and NetApp. At InvestorFlow, he's helping to drive strategic growth as the company pioneers ways AI and agentic technology can reshape investor communications, fund administration and data-driven decision-making. Chris, welcome to the podcast.

Chris:

Thanks for having me, jim. Really appreciate it, yeah, so let's just dive in.

Jim:

So agentic AI is being called the next frontier of enterprise technology. How do you define agentic AI and what makes it so disruptive in the capital market space?

Chris:

So I think we saw the first round of AI, which was sort of a prompt and answer, and now we're able to deal with a whole series of prompt and answers that run in a stream and you can deal with the if-then-else scenarios. And that's really what drives this value of agentic, because now you can get to the bottom of an issue but not have it be just a simple input output.

Jim:

And you've been focused on digital investor experiences since the early 2000s. How is agentic AI pushing that evolution even further?

Chris:

Yeah, it's having a real impact. Having a real impact If you think about investor experiences and in our case, for InvestorFlo, we're really trying to serve both the mid-sized to large firms that are growing their count of institutional investors by literally the hundreds. One of our largest has 5,000 LPs in a single fund. So imagine trying to deal with the level to provide the level of service they want to provide, but do it at that kind of scale. You know, agenti really has the capability of helping these investor services professionals, engage these folks, get them everything they need, because they are the number one source for their next fund.

Jim:

So now at InvestorFlow, you're reducing processing time by up to 60% by using AI. Perhaps you can walk us through some specific examples of how Sure.

Chris:

So let's start from the beginning.

Chris:

The first thing that the firm needs to do is say we're raising a new fund, what do we go do?

Chris:

And you think about that process for the head of IR, who tends to be the first for driving that next fund. So, instead of bringing in their team and mining through, looking for conversations here and there where they might have found an institution that says, hey, I'm interested in this type of fund, I'm interested in digital infrastructure fund, or I'm interested in this type of return with this type of risk rate, well, instead they can use us as a way of mining through not only the records that they may have in a system, but meeting notes, emails, and come up with a targeted investor list based upon pre-existing interest that they have, and they can do this with the click of a button. Now, we're not saying that this is your 100% list go forth and conquer, but you are shaving massive amounts of time off of this process and you're giving a much higher probability of which institutions are going to be interested. So this one use case gives you a flavor for just how powerful this can be for these high-powered firms and these high-powered professionals.

Jim:

So some tech leaders like Oracle or predicting a future, AI agents are going to surpass human uses in many financial systems. I mean, do you see that happening in private markets? And if yes, you know when is this coming?

Chris:

I certainly think that it's possible in the future. I would say, based upon our conversations with our client base right now, this is really about making their people better, and you're talking about extremely educated, extremely smart and extremely driven people. These are the people that are really pushing the envelope on the work life boundary, let's say, because that's what it takes to get ahead in this space. But if I can have AI be a force multiplier for me, find more opportunities, find on-target conversations and then decrease the time that it takes to get to an answer in and around a particular whether it's a fundraise or whether it's a particular investment that wants to be made, that they want to make If they can drive that and get advantage out of AI, it really is where they are now.

Jim:

But one of the biggest challenges is data. Yeah, and so what are the foundational data requirements for a firm that really wants to implement AI agents effectively?

Chris:

So this is a great question. It turns out that it seems really like it's the more data the better. And you know one of the things that we know and you brought up Oracle, interestingly enough, which was, you know, an older player, say, in the CRM market at one point in time. But you know it's a time-honored tradition that nobody likes updating their customer relationship management systems, and this is where a lot of this information is stored. This is where you know. I spoke with Jim today and we talked about the following things. Jim was interested in the following things Nobody likes to do that and, as a consequence, if you can just make this whole data capture problem just simpler so that it's not a tax, it's not a burden on people, the more data you have, if you can look at emails, meeting notes, records, anything that may be stored in a meeting itself, if you can tap all of that, you can get a 360 on an opportunity way faster.

Chris:

So bringing all of that together is critical. And in the private markets, as you know, there's the raising of the funds, there's doing the initial deal and oftentimes there is a secondary deal which might be looking for a co-investor, because now I've got to find somebody. This is just too big for my profile or my risk profile. I want to have more people in on the deal. Or maybe it's in the debt area. They want to find a way to syndicate that debt. If you've got what's going on on the fundraising side integrated with what's going on in the deal side, you short circuit this conversation. You make it faster. So data is critical. But I think you know we spent a long time thinking about the need for data cleansing. I think you know AI is the thing that helps us just aggregate and extract and synthesize.

Jim:

Well, one of the bigger challenges in that is, as all these tools are coming to market. They don't necessarily all play together, though. Right, we utilize, where you know we have our CRM, or we have, you know, tools that are listening into phone calls and providing transcripts and insights from the sales organization. You have, you know, an Office 365 ecosystem. You know, how are you getting all of these to play right? Because you're almost getting different sandboxes along the way. That's right.

Chris:

So one of the big things here is, as you say, how can you tap this? But how you make it easy for the user, and and so this is where proper, you know, tool propagation we've seen in so many other instances. That's not exactly the key to adoption, and and the reason why I talk about adoption is not just that you and I say are comfortable using this technology, but adoption is key to actually getting the data and therefore starting that cycle of more data, better insight and better outcomes. So what we're trying to do is really take the core workflows that we serve in these firms the fundraising workflow, the capital deployment workflow, whatever type of transaction it may be and the investor services workflow and have those integrated together and on a common data platform, which again propagates the data, but stitch AI into these different applications, as opposed to AI as sort of a bolt-on add-on. After the fact. That just makes it. It's going to make it a lot simpler for people to use. That's our at least that's our premise.

Jim:

You know, looking back historically, investor portals used to be just document repositories. You know, today there's sophisticated engagement tools.

Chris:

How is your team redefining that experience? That's a huge element here, I mean, if you think about it. Let's go back to that example of thousands of LPs. Well, those thousands of LPs in a particular fund they do not want to be treated like a number. And the firms that rely on them as part of their funds they don't want to treat them like a number either. So engagement is all about making them. You know, we talk about enabling these investor services teams to deliver the white glove treatment that these institutions expect. That means their data, their preferences, their profile and make it engaging, not just a document repository. I still have some scars, I think, from SharePoint in the early 2000s, so that is not the point. They want to profile and make it truly engaging. They want to profile what's unique about their firm and their firm strategies, not just provide a bunch of documentation.

Jim:

I'm not going to comment on SharePoint. Let's talk fundraising for a second. With tools like interactive PPMs and virtual diligence, how are AI and automation reshaping the capital raising lifecycle understand more?

Chris:

clearly who do you have strong relationships with and who in your firm has those relationships, so that you can have your best people talk to the most appropriate contact at these various institutions. That's what leads to a much better sales cycle. It really is a sales process for them and making that seamless for them. So so when you're in a conversation, and then automatically provisioning them with a diligence room to get access to that information so they can understand if this fund, the fund profile, is right for them, that's that's key, and we've seen some results, some early results, where just shaving the cycle time off of that process means you as a firm can just be moving a lot more fast, a lot faster than, say, your competitors, because it's not, as you know, it's no longer unique. What's your particular fund? I mean, everyone right now wants to go after a digital infrastructure fund. Okay, we all read the same news and see the same returns, so it's got to be built on relationship strength and efficiency, so security is always top of mind for anyone at this point.

Jim:

What are the best practices that GPs should follow when introducing AI into sensitive workflows like capital calls or wire instructions?

Chris:

So we spend a lot of time thinking about the following, which is helping them get to a much faster answer but still have that human control. The final mile, if you will that has been the feedback that we universally have gotten from our early adopters is, you know, we're not trying to take, say, the call center approach where you know the idea is we could have a virtual agent take you from zero to to, you know, all the way through the end of the process. Really, really, it's about how do we just enable these folks to just be better and deliver a much higher service level to these high touch clients because they want to. These firms want to retain them and keep operating with that kind of high touch.

Jim:

And as finance becomes more autonomous, how can firms balance AI driven efficiencies with the personalized experiences that LPs are still expecting?

Chris:

Yeah, I see this playing out where there could be multiple classes, and one of the things that we're working on is how do we classify what their incoming requests are? What could be served digitally just to make it lightning fast for them to get an answer to a particular very discreet thing, versus, you know, a much more nuanced sort of inquiry that really does require an investor services professional to have their their you know their eyeballs on top of that, on top of that response. So I think that's the next, one of the next steps and that's one of the of that, uh, on top of that response. So I think that's the next, one of the next steps and that's one of the things that, uh, you know, our, our dev team is is at work on.

Jim:

So, chris, unfortunately we've made it to the final question in the podcast. We call it the trend drop. It's like a desert Island question. So if you could only watch or track one trend in AI, uh, at this point in time, what would that be?

Chris:

Boy, this is a tough one, given how fast this is moving. You know, one of the things that we saw very recently is how is this going to be integrated into your own personal devices, right? So you know I'll go real time on you. Yesterday, openai decided to buy Johnny Ives' company, which is a device making company, and you know who knows how this is going to be brought together in the future. But I definitely think we're going to see this integrated into various you know all different experiences, so watching. You know, how is this integrated into email? That's something that we already do but how is this integrated into these different systems of record and different systems of engagement? This is going to be a key trend to watch.

Jim:

Chips in the head are coming. Yeah Well, Chris, I want to thank you so much for your time and your insight. Really appreciate it.

Chris:

Thank you, jim, really appreciate you.

Jim:

Thanks so much for listening to today's episode and if you're enjoying Trading Tomorrow, navigating Trends and Capital Markets, be sure to like, subscribe and share, and we'll see you next time.