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Home Financial Planning

Why Dynasty built a data lake for its AI-driven platform

by TheAdviserMagazine
6 months ago
in Financial Planning
Reading Time: 5 mins read
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Why Dynasty built a data lake for its AI-driven platform
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Partnering with around 60 firms representing more than 400 advisors with over $100 billion in platform assets, the St. Petersburg, Florida-based wealth management solutions provider Dynasty Financial Partners has a lot on its plate.

At the helm of its technology stack is Leslie Norman. She has been Dynasty Financial Partners’ chief technology officer for over three years, leading the product and engineering, information technology, cybersecurity and technology services teams.

Prior to that, she served over a decade at Raymond James, including as business technology manager and on the product development team, “leading the build-out of many of their marquee advisor technology offerings.” 

“My role at Dynasty is to continue the build-out of a platform that was phenomenal before I got here, but we’re focused on continuing to respond to the needs and the demands of our very elite clientele,” she said.

READ MORE: Why Dani Fava is a ‘techno-optimist’ on AI in wealth management

The firm offers Dynasty Desktop, a unified platform that integrates proprietary and outside technology.

On the artificial intelligence front, Dynasty has also introduced the Client 360+AI platform for meeting prep and Private AI Chat for “personally identifiable information (PII)-friendly use.” (PII can often be particularly vulnerable to attack when fed into external models.)

In addition, Norman said Dynasty works with a team of advisors — its Technology Advisory Board — to help refine the current technology stack and evaluate its future.

“The voice of the client is something that we take seriously in our product development,” she said. “We don’t build technology for technology’s sake. We focus on making sure that everything we do is purpose-driven and solves real problems for advisors and their clients.”

READ MORE: What Facet has gained building its tech stack from scratch

Norman took the time to discuss with Financial Planning the advantages of a unified approach to its platform offering, how the firm plans to keep personal data safe when it comes into contact with AI, why Dynasty wanted to develop its own data lake and more.

This interview has been lightly edited for clarity and length.

Financial Planning: I know Dynasty has a unified platform offering. What are the advantages of that approach? What are the most important pieces?

Leslie Norman: At Dynasty, we recognize that there was a big gap left by the two options that RIAs have had historically when it came to building their technology stack. One end of the spectrum is that you can go with an all-in-one technology platform that has arguably all the things you need to run your business. But that comes with limitations in terms of flexibility. It can feel pretty integrated, but doesn’t tend to be as sophisticated and flexible as we’ve seen many of our clients need. If you don’t want to go with an all-in-one, you could handpick from the hundreds and hundreds of technology tools that are marketed for RIAs. You’ve seen the Kitces Financial Advisor Technology Map, right?

But the challenge that we have inherently in our industry is that a lot of these tools don’t talk to each other. Integrations are lacking, which can lead business owners to spend way more time than they should focusing on, “How do I integrate my performance reporting and my financial planning tool?” when we think their time is better served focusing on how they can grow their business and deliver great results for their clients. So the experience that we built aims to bridge that gap, and it all comes down to the desktop. What we’ve done there is create a single pane of glass for our clients that pulls together the essential information about their day: their clients, business and investments. What’s unique is that underneath the hood, it is powered by their choice of best-in-class technologies, but it’s extremely integrated. And over time we’ll continue to add more to give them that one-stop shop … to run their book.

From there, we’ve got a number of additional tools that we’ve built at Dynasty to address places where we’ve seen gaps in the marketplace. It’s around data collection, around business analytics, being able to help answer those hard questions, “How is my business doing?” Often it takes seeing what’s going on with not only your financials, but your assets, your billing information. Because we’ve invested in our data lake and aggregating all that information together, we’re able to do that uniquely.

FP: You utilize AI in your tech stack, but what is your general philosophy when it comes to implementing these tools? And how are you ensuring data safety since PII is involved? 

LN: We as an industry are still extremely early innings when it comes to AI adoption. It’s an incredible time, because I’m seeing more interest and appetite to adopt this technology collectively, than I’ve ever seen with any other technology entrance. It’s awesome, but some firms are bogged down by compliance and the regulatory environment. And obviously, there are considerations around, “What are the right use cases for AI?” We believe strongly in AI as an enabler for the advisor. Co-intelligence is something that we talk a lot about, and we see AI as a way to help advisors make them more productive. It’s like a “duh” moment for us, “Yes, obviously we want to apply AI to add efficiency.” That’s the category of AI applications we’ve focused on — efficiency plays for advisors, but also for ourselves in our engineering development processes, especially when it comes to information collation and reviewing.

On the security aspect, one of the biggest fears people have is their client data leaking out, or training models in a way that they wouldn’t want. So, one of the ways that we’ve stepped into that is, we’ve created a private instance of ChatGPT for advisors within the desktop, so it’s all contained within Dynasty. They don’t have to worry about that information leaking back out; anything sensitive about their clients.

We’ve invested over the last three years, in particular, in building out our data lake and making sure that we’ve got robust, clean data underneath the hood, that it positions us to do a lot of exciting things with AI. We see a lot of people who are looking hard at their data strategy right now and saying, “Man, I’ve got a lot of work to do to be able to get this data AI ready.” But since we’re there, we’re able to put AI on top of our client data. We’re piloting an experience we’re calling an AI chat within our Client 360 platform, where you can use the AI to curate touch-point ideas and look through what could be years and years of client information and communications. The AI can help tee up those ideas for deep and meaningful conversations with clients.

FP: You mentioned your data lake. That touches on something I’ve been writing about lately, which is the importance of firms owning their own data. And especially if you’re using AI, it’s only as good as the data. What was the process of building that infrastructure?

LN: It’s a project where you crawl, walk, run, but the approach that we took was focusing in the beginning on what we considered the core in terms of data. What are the tools that financial advisors need to use every day to run their business? Let’s start there. So that looked like curating, organizing their data, then looking at CRM, financial planning, performance reporting and custody. We wanted to focus on the most important datasets first, and throughout, as we were doing that, build business applications on top of it. In our analytics, we have a sandbox for creating these new views with these datasets that we’ve pulled together.

Now that we have the infrastructure in place, as there are new entrants, we’re able to integrate them into the data lakehouse environment piece by piece.

There’s a piece to that puzzle still, where pushing the data into a partner platform requires some APIs and connectivity. Frankly, that’s one that we’re still chipping away at, but an idea of data synchronization.



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