Maximizing Investment Insights with Data: Leveraging AI for Smarter Decisions with Robert Huntsman

[00:00:25] Robert Huntsman: Hey, thank you for having me, Doug.

[00:00:27] Doug Heikkinen: Robert, I think you're pretty new to the team at iCapital. Can you talk about that and go into your role within the technology organization there?

[00:00:35] Robert Huntsman: Absolutely. So I joined iCapital a little bit over three months ago. And formally, a Chief Data Officer is responsible for data governance, data management, analytics, and artificial intelligence.

Practically, what a CDO does is build and continuously evolve the teams, the technologies, and the processes that enable a company to optimally ingest, store, protect, and analyze data in service of its business model. So I think about my role at iCapital as helping the company to optimize the use of its data so that we can deliver optimal outcomes for our customers, our partners, and that we can really streamline our operations.

[00:01:15] Doug Heikkinen: In your opinion, what's the most important technology driven tool that wealth advisors are seeking today?

[00:01:22] Robert Huntsman: it's a great question. So, in multiple conversations with wealth advisors and the marketplace, what we found is that wealth advisors really want to provide their clients with access to world class investment opportunities that are matched to the unique needs and objectives of their clients.

One of the key tools that we're looking for today is the ability to analyze a massive amount of information and to be able to get down to a set of recommendations that are ideally suited to the needs of their clients. So when I think about tools that advisors use, in many cases, it's research, it's portfolio construction, it's performance attribution.

At iCapital, we've done a lot of work in each of these areas. We've got a dedicated research, tool called Alts Decoded and a research team that spends a tremendous amount of time culling through the information that's available, coming up with insights on trends, and really trying to arm our advisors with insights.

We've coupled that with cutting edge technology. We use AI to transform unstructured data into structured data. And then we're using distributed ledger technology to integrate all of the data into a single place where advisors can see the positions of their clients.

[00:02:40] Doug Heikkinen: Data accuracy and reliability is paramount to advisors. How does iCapital, ensure that?

[00:02:47] Robert Huntsman: So data privacy is one of the top concerns for any advisor. And for us at iCapital, we're really in a privileged position because we sit at the intersection of the alternatives investment world and our clients.

So our goal is to protect their data. So there are a few things that we do. One is we have formal processes that govern all of the data that we either see or we ingest or that we store. We use cutting edge technology. So we have technology that encrypts all of the data both in transit and at rest.

So when you think about sending out data, you need to make sure that you're sending that data only to people who have the right to see that data and that that data is always encrypted. And when you store data, you need to again, make sure that you're protecting that data. We use encryption. We also have strict governance around who can access data, even if it is encrypted.

So all of this is part of our data ecosystem that we continuously evolve as regulations change, as the types of data that we deal with change, but we're continuously, and I say continuously, this is something that we look at on a daily basis.

[00:04:01] Doug Heikkinen: Can you share any information you have on how the regulatory environment is going to change relating to data privacy?

[00:04:09] Robert Huntsman: We think that regulators are going to continue to emphasize PII, which is privately identified information. And we think that there are going to be new regulations potentially around the responsible use of A. I. So in Europe, for example, there are new regulations that are coming into effect in January, which are going to govern how you protect personally identifiable information.

And so we've already been thinking through how we're going to respond to that. We've been investing a lot of money in what we call the data vault, which is a solution for protecting PII and really walling that off from anybody other than the small set of people who should have access to it.

[00:04:50] Doug Heikkinen: All right, let's talk AI. How will data and AI machine learning help advisors making some more informed decisions based upon more advanced data management and solutions?

[00:05:02] Robert Huntsman: One of the challenges that advisors have is, it's a challenge that we all face and that's Just the explosion of data. We have an explosion of data, and it's not just in the world at large, but especially in the investment management space, you've got a lot of unstructured data, unstructured data that these are documents that, especially in the alt space, you've got documents such as private placement memoranda, you've got investment prospectuses.

You've got a tremendous amount of research coming out all the time. So how do you make sense of all this information that's out there? AI is a key tool for really being able to take a large volume of data and to be able to apply AI models to extract relevant pieces of data from a large body of unstructured data.

So we are spending a lot of time and money investing in developing AI models that will extract insights from a large body of data. And then really also empower advisors to be able to use AI to ask questions and get answers. So these two tools I think are critical to allowing advisors to really find the needle in a haystack when you've got a lot of data and you need to get to an insight, or you need to get to a key piece of information and answer to a client inquiry.

AI is that tool, which is going to help advisors to do that.

[00:06:27] Doug Heikkinen: Let me dig a little deeper into this AI thing. How are AI driven technology firms transforming alternative investment data aggregation management and reporting for financial advisors and asset managers.

[00:06:42] Robert Huntsman: Great question. So AI firms are investing right now in large language models, and the training of large language models, to extract structured data from unstructured data, and it's really transforming the alternatives investment world because processes that used to be purely human driven, for example, entering information into a reporting platform.

That process is now becoming partly automated and very soon it should be almost completely automated. And that's due to the advent of AI and the development of AI models by, AI firms in the industry. So for example, if you've got a large body of clients and you want to be able to really easily extract information on the performance of their assets.

If you want to be able to do reporting, the use of AI and the firms that have come into the marketplace that have developed AI models is really accelerating that process. So, it's squeezing it from weeks or days down to just a matter of minutes or even seconds in some cases.

[00:07:51] Doug Heikkinen: What are some of the latest innovations in technology and data management in making private market investing more accessible and easier to manage across lifestyle of these investments?

[00:08:02] Robert Huntsman: So we at iCapital, we're really at the intersection of the investment advisor landscape and the alternative manager landscape. So we sit at the intersection.

So data flows from private wealth managers to alternative investment managers through our platform. And we view our role as really leading the development of technology that streamlines that process. So just to give a few examples, when you subscribe to an alternative investment, historically, you've needed to fill out lengthy subscription documents. Those go back to the GP, you're exchanging information with administrators, once you're invested in a fund, to be able to do things like report on the net asset value of a fund, or to be able to get investment performance. What we're doing is we're streamlining those processes.

We are using artificial intelligence to extract information from complex documents so that this work can be done, for example, subscribing to a new investment. So this can be a semi automated process or the month end process of actually reconciling a PCAP statement or a NAV statement, reconciling what the administrator says with what's in the books and records.

So using AI for these purposes is streamlining the process of getting information into the hands of advisors much more quickly and also in a much more consistent way. So instead of having humans read through and do reconciliations manually, the use of AI can automate a lot of that process. So then you have humans, with expert knowledge and judgments, able to look at the results of an AI model and to validate that the model has done the correct reconciliation, or the model has done the correct extraction.

So, we're seeing that AI is the most exciting technology for helping to make alts much more accessible and it's simply by squeezing down a lot of this manual work into a very manageable process.

[00:10:07] Doug Heikkinen: So talk about the key data challenges that are occurring as private market investing continues to expand crazy.

It's great for you guys.

[00:10:16] Robert Huntsman: Yeah, I know. There's a massive growth in the alternatives industry. There's also a massive growth in the percent of assets that are allocated from private wealth managers to alts. So we've seen that really accelerate and we expect it to continue to accelerate.

It's not just that there's a lot of money going into alts in the private wealth space, but we see that rate of change actually increasing. And so what we're seeing is that, the management of this data, the aggregation of this data is a challenge because you've got new funds, new types of offerings.

So if you look at structured investments, for example, we currently have 177, 000 structured investment prospectuses in our database. And we've created a structured data model. However, every day there are new types of structured investments that are being invented. There are new types of products that are coming to market.

There are new funds that are coming to market. And every time you've got a new structured investment or a new fund or a new annuity, any type of alternative investment, you've got a new data structure. So the volume of data, the type of data that is coming into the market is just exploding. And really the biggest challenge is how do you make this accessible?

How do you allow a company to scale, a company like iCapital, how can we scale our operations so that with each new fund that's launched or each new note that's issued, you don't have to go and have a team of people that goes and reads the documents and creates a new data model to model out that new structure.

And that's really where we've been relying on AI to find patterns in the data.

[00:11:53] Doug Heikkinen: So what's changing in the way we structured this massive amount of unstructured data?

[00:11:58] Robert Huntsman: What's really changed is the advent of large language models. Large language models are neural networks that are trained to predict sequences of words to extract information from documents.

The biggest innovation in the market has been the advent and the widespread adoption of large language models for extracting structured data from unstructured documents. And this is really the key for us. This is how we're able to train a model to recognize patterns in documents so that when you get a new document that may not be for the exact same instrument, so you've trained it on 177, 000 structured notes, but then, you know, note number 177, 001 comes along and it's different than the rest.

These models are now good enough that they can recognize the patterns from the other documents they've seen, and they can actually go into this new document that they've never seen and extract the right pieces of information so that we can add that new note to our platform.

[00:13:04] Doug Heikkinen: All right, Robert, last one for you.

What is the future of data solutions?

[00:13:08] Robert Huntsman: So we see the future of data solutions as a combination of technology and people to massively accelerate the ability of iCapital and our people to get data to our clients and to their clients much, much faster. So, we have a data solutions business that historically has done the very painstaking process of accurately getting information from statements, from private placement memoranda, from prospectuses, and putting that data into a structured format.

The future is that. Rather than have teams of people, that have to grow every time you add new types of investments, what we're seeing is that they can leverage technology like AI, like robotic process automation to be able to automate a portion of their jobs so that their time is spent in review and in really trending the models versus doing the work of pulling down information, reading through hundreds of pages of documentation and then having to themselves extract that information.

[00:14:20] Doug Heikkinen: Robert, you took us through a lot of complicated stuff and made it understandable. Thanks so much for joining us.

[00:14:26] Robert Huntsman: Thank you so much for having me. It's a pleasure.

[00:14:28] Doug Heikkinen: To learn more about iCapital, please visit iCapital.com. Please follow us for timely updates on X, LinkedIn, and Facebook, all @Advisorpedia.

For everyone at Advisorpedia, our producer Julia Smollen, our engineer Tory Miller, and the Power Your Advice podcast team, this is Doug Heikkinen.