AI Built for the Real Work of Client Management with Bassam Chaptini

What does that actually mean in practice, and how is it different from the wave of point solution AI tools we're seeing across the industry?

[00:00:36] Bassam Chaptini: Yeah, no, great question. So we are an operating system for client management. It is a white space in the industry that has been around, honestly for more than 20 years.

It's all about onboarding and servicing and managing complex client relationships There's never been a solution in the field. People would use different point solutions a lot of swivel chairing. If you have to get the context of a given client, you have to, go to 15 different systems to assemble all that knowledge.

So we created Avantos to be truly an operating system to provide the full context around your client relationships, not just to onboard them and servicing them, but deepening the relationship. And what we mean by operating system, we truly mean a holistic view of your clients, but not just your client data, but also yourself, you as an advisor, the team that you're part of, and also the product that your clients are buying.

All of that interact heavily, and we created that system of context, which is what we call AI native, a knowledge graph behind the scene that serves as this holistic view, for any advisor to service their clients.

[00:01:47] Douglas Heikkinen: There's a lot of excitement around AI. We run so many stories, which they're usually pretty informative.

But you've said most firms are still in the early innings. What does real enterprise grade AI adoption actually look like inside a wealth management firm today?

[00:02:04] Bassam Chaptini: So, yes, exactly. There's a lot of experimentation and R&D going on, in a good way, in a good way. A lot of the features that we are seeing are some point solutions that work well, like note taking is very classic example of a way where AI works, it improves productivity, but it's more of a point solution, a feature that you're able to do.

What we are pushing and seeing in enterprise, where we are deploying for our clients, is what we call an advisor AI. A truly an AI that sits along with the advisor and holistically help them, not just in meetings or in certain workflows, but holistically help them. For you to be able to do that as an enterprise, you need your data to be represented in a way that AI can consume it.

And so what we do is behind the scene build that knowledge graph of client data, advisor data, product data, and the work to be done, the journeys, the client journeys. And our AI agent sits on top of that so that it has literally the same context as the advisor servicing them. And so this way it can be a co-pilot.

An advisor can ask it literally anything that exists in that knowledge graph, and it, the AI will help that advisor service their clients, whether this is starting a money distribution, or onboarding a net new client, or having a conversation and meeting with a client and identifying all the follow-up actions and executing on those actions.

All of that is able to do as part of the operating system. And for us, that's truly the impact. Not just one sliver of what an advisor can do, but a holistic approach to how we help advisors.

[00:03:48] Douglas Heikkinen: After all this time, client onboarding and servicing are still major friction points for advisors.

Why have these areas been so difficult to modernize, and where are you all finally making a measurable difference?

[00:04:02] Bassam Chaptini: Yes, that is a fantastic question that we've been playing around for the last 15 years, my co-founder and I. We've been in the space, in that client management space, in different shape and form. As consultants, as tech providers, and now with Avantos.

The fundamental problem is complexity. But some of that complexity is built in into the flows. Financial products are a complex product to buy. You're not buying something off of Amazon. It's a complex financial product that has a lot of regulations around it. For good or bad, it's just complex as a product.

But the flip side of it, the systems that either support the clients or the product are completely fragmented. They have different data models behind the scene. They have different workflows behind the scene, and it's a patchwork of different things. And so it becomes what should be a straight-through automation or a straight-through process becomes a fragmented process to collect all that data, assemble it in a different way, and deploy it.

People have tried different systems, but as I mentioned, it hasn't been a holistic view of what you need for a client management. It ends up being swivel chairing and a lot of work. So that is the white space that allowed us as a company, Avantos, to be created to solve it in a holistic way so that we can streamline all that processes.

AI helps a lot, by the way. AI helps a lot in terms of behind the scene, collecting all that information and building that knowledge graph dynamically. It also helps a lot with the execution of the workflow so that you're not waiting for two days to collect data and then ping your client again to get other data and what have you.

It can be proactive in collecting all of that data and surfacing it with a human in the loop to be able to kick off those either onboarding or servicing events.

[00:06:00] Douglas Heikkinen: Your platform is built around a knowledge graph connecting assets like 401ks, RIAs, and 529s. How does that unified data layer change what advisors and AI agents can actually do?

[00:06:15] Bassam Chaptini: Yeah. I touch on a few points with the knowledge graph piece. One of the key pieces that you are highlighting here is the cross-product ability of our platform. So one of the things that advisors do want to do is service, again, their client holistically, not across one product, but across different types of products.

Also, products outside of your traditional wealth management space. We have clients that want to service not just their wealth management, but help cross-sell life insurance, annuity, banking products, along with the wealth typical brokerage accounts or wealth management services like taxes and what have you.

Again, there hasn't been a platform before that is able to support all those types of products, and that's what we're doing with our knowledge graph in Avantos. We can represent different product from different industry sectors with the complication of the workflows that comes with them and the data requirements that comes with them all in one plane.

And it truly allows advisors to also start recommending and thinking about other services and products their clients are interested in. If you're a client of an advisor, and you mention, for example, you have a newborn, you might want to open a 401k, you might want to open a 529, for example, open a trust, update your beneficiaries, but you also might want to increase your life insurance or get new life insurance.

Things that typically have been extremely manual and things advisors can service now they can do it holistically.

[00:07:49] Douglas Heikkinen: We have to have the compliance question. As many firms are hesitant to introduce AI into client-facing workflows due to compliance concerns. So how do you design intelligent automation that enhances productivity without introducing new risk?

[00:08:06] Bassam Chaptini: Yeah. Yeah. so we've designed our AI to be as autonomous as possible while having a human in the loop. Our AI does not do anything without a human in the loop confirming what it does, for compliance reasons, for risks reasons. The accuracy of the AI is actually fantastically high. It's not because there's doubt in terms of what the recommendations are.

It just from a compliance perspective, we want to make sure there's a human in the loop, somebody's looking at it. From a client service perspective, we typically so far provide a lot of the tools for the advisory team, and they interact with the clients as well, but this is assisted by AI.

Very concrete example. I'm onboarding a new client. I have a whole bunch of missing data I need from the client, missing documents. I want your taxes, I want blah, blah, blah, all that stuff. Our AI is able to look at an onboarding workflow, an onboarding journey for a client, tell the advisor, "These are all the missing information.

I have this information, and these are all the things that are missing. Here's a draft email that you want to send to your client. Review it, confirm it so I can go and collect it." They confirm it, it sends a link, and now the client can either digitally upload those documents or they can send them directly to the advisor, et cetera, et cetera.

So as you see, like it is automation with a human in the loop to allow for that productivity increase.

[00:09:35] Douglas Heikkinen: We're seeing a big shift from fragmented tech stacks to a more unified infrastructure. So what's driving this modernization cycle, and why is it happening now? Is it more than just the obvious?

[00:09:49] Bassam Chaptini: I think it has long been, it's been long due in terms of just making sure things talk to each other.

Some of the issues that we find, realistically is that it's hard to move data. You might want to modernize your tech stack, but it's hard really to move the data, and the ROI is tough. moving data, it requires a lot of testing, a lot of integrations into the same system. Our approach, as Avantos has been that keep your data where they are.

If you have a system that works or if your data resides in a client master or product, if you have your product master, leave them as they are. But now deploy a layer on top that abstract all that data and all those workflows, and have that unified layer on top of your existing system so that you're not going through the pain of data migration, integration migration, and all of that.

So the need for a unified system is absolutely there, and this is what we provide for our advisors so they don't swivel chair. But behind the scene, it might still be a fragmented system, but it's completely isolated, and it's completely abstracted away from the actual Avantos users.

[00:11:09] Doug Heikkinen: Avantos has already onboarded firms like Vanguard, Mercer Advisors, and Guardian.

That's really impressive. What are those institutions prioritizing when they evaluate infrastructure partners?

[00:11:23] Bassam Chaptini: So there is a common theme and different thesis for each one of those firms. The common theme is deepening the client relationship. That's what they really want. And wealth is a place where there's a premium at deepening that relationship and at having a system that's able to deal with the complexity of it.

Vanguard, Guardian, and Mercer have different thesis in terms of how they want to approach it, and this is why we love them as partners for our journey. Mercer wants really to build, a business where their advisors holistically see their clients. They are growing fast, and they keep on adding advisors, adding clients, and they truly want a unique system, a unified system to do all the things I described.

Vanguard has the same needs of having deepening the relationship, but they have a different thesis as well. They have a lot of clients who are on their brokerage business, and they want to promote certain brokerage clients to be full-fledged wealth clients now. But they need the system to promote them, to construct the different, elements that you need for a wealth management business.

So they partner with us to build that system. Finally, Guardian, as I mentioned before, they have a wealth business already within Guardian, and they have their life and annuity business as well. They want to cross-sell products. They want their wealth clients to be able to buy life and annuity and vice versa.

And so they loved our platform and our approach of a knowledge graph to marry all those products for the same clients, that they're serving

[00:13:11] Douglas Heikkinen: There's a big gap between consumer AI experiences and deploying AI inside regulated financial institutions. What are the biggest misconceptions firms have when they try to bridge that gap?

[00:13:26] Bassam Chaptini: From a consumer perspective, the expectation is to have a modern experience these days, and people tend to be very baffled by not having that experience. They're filling PDFs or filling forms or sometimes literally paper, signing and what have you.

So they're always baffled by why that is the case. The flip side of it is behind the scene, because of the complexity of the regulations and the compliance, firms are sometimes not able to keep up with all the workflows. And because of the fragmentation of the data, they actually, it's much easier for those firms to revert back to forms because they can't update the system fast enough.

It's easier to update a PDF and have a new requirement as part of that new workflows than to go and update the system. So the legacy behind the scene shackles the firms to provide the experience they want to provide, by the way. It's not like they are not aware of the bad experience.

They're just shackled by the underlying system that cannot keep up with all the regulations and the complexity of it. That's part of the reason that we are, at Avantos, trying to solve, which is all that complexity, trying to abstract it away, heavily use AI behind the scene to marry the data and tie those different systems behind the scene.

But from a advisor and a client perspective, it's actually, they're shielded from those backend systems, and they don't see the behind the scene mess that typically are from all those systems.

[00:15:04] Douglas Heikkinen: Continuing on with the consumer, as automation improves efficiency and scalability, how do firms ensure they're not eroding the trust of the consumer or diminishing the human element that defines the advisor-client relationship?

[00:15:22] Bassam Chaptini: We see it day in, day out. Whenever advisors are using Avantos and using our AI agents, they actually end up spending more meaningful time with their clients because a lot of the groundwork that they have to do to support the, clients is actually, automated and taken care by AI, which allows them to really focus with their clients.

If they're talking to their clients, they're not focusing on, "Okay, I need now..." They mentioned, "I need to do this, and now a- after the meeting, I have to go and open the accounts or move the money," et cetera, et cetera. AI is helping with all of that, which gives them more time to actually spend with the clients.

What we're also seeing is that because of that productivity increase, advisors are able to service clients that they weren't able to service before. Clients who might not qualify to be serviced by an advisor, for example. Now they're able to do it because of all the automation behind the scene.

It's not like they're getting a robo-advisor behind the scene. They're still getting the human advisors that clients want. But the automation behind the scene and the productivity behind the scene allows advisors to talk to more people, and more clients, and help service them. So at least that's what we're seeing on the ground on the Avantos platform.

[00:16:45] Doug Heikkinen: Last one for you. What's next for Avantos? You just had an impressive funding round that's gonna give you some room to dream and implement things. What's next?

[00:16:58] Bassam Chaptini: So we have set from the get-go at building, what again, what we call the operating system for client management, and we truly mean it holistically.

For financial services, that's what we're focusing on. We started in wealth management as a starting point because of many reasons I mentioned. It is an area that is high growth, exciting for a lot of firms, and equally important, the impact for managing complex relationships is extremely high. But our ambition in Avantos is to actually be cross-sector in financial services.

So we're just starting, we're just jumping into insurance. We're going to go into banking, into capital markets, alternatives, et cetera, et cetera. And so that this way clients, or advisors can truly holistically service all their clients. So we're moving across different sectors as we go, but that's what excites us as a company.

And so that's on the business side of the equation. On the AI side, we're literally just scratching the surface of what we can do. I mention and talk about knowledge graph a lot. That is the foundation to everything that we do behind the scene from an AI perspective. And the ability for an AI to do different pieces is becoming fastly, like it's becoming more capable by the day.

You can see, for example, AI trying to optimize taxes, optimize different pieces. For us, it's all great because we can bring it to the advisors in one operating system. Say great, so now you can cut the time that you spend doing X, Y, and Z, to spend more time deepening the relationship with the client.

So all of this is extremely exciting for us, and we're literally just getting started.

[00:18:51] Douglas Heikkinen: Fantastic interview, very impressive company, and we thank you so much for being with us today.

[00:18:59] Bassam Chaptini: Thank you so much.

[00:19:00] Doug Heikkinen: To learn more about Avantos please visit Avantos.ai This has been the Power Your Advice podcast.

For our producer, Tory Miller, and the whole team, thank you so much for listening.