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Home Financial Planning

Carson’s Dani Fava is a ‘techno-optimist’ on AI in wealth

by FeeOnlyNews.com
5 months ago
in Financial Planning
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Carson’s Dani Fava is a ‘techno-optimist’ on AI in wealth
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A year ago this month, Dani Fava began her current role as chief strategy officer at the Carson Group. Before that she held executive positions at firms including Envestnet and TD Ameritrade.

For a significant portion of her nearly quarter century in the wealth management industry, the self-described “techno-optimist” has been heavily involved in the implementation of artificial intelligence.

Lately, Fava has been focusing on using AI to increase both the number and net worth of the households Carson Group can serve. The Omaha, Nebraska-based RIA, which manages approximately $40 billion in client assets, has increased its average household size by 11% over the past two years, she told Financial Planning.

“We’ve successfully done that because we are focusing now on bringing technology to the advisor that helps them meet the needs of more complex, high net worth clients,” she said.

READ MORE: Carson Group’s Dani Fava on data strategy, AI bias and disconnecting from your desktop

To that end, the Carson Group launched Carson Tax Solutions in February.

“We are leaning aggressively into tax planning,” she said. “We’re seeing demonstrable success there, too.”

READ MORE: Raymond James’ new AI chief opens up about tech at the firm

Fava spoke with Financial Planning about moving AI from the back to the front office, keeping the humans in the loop, AI creating and solving cybersecurity concerns and more.

This interview has been lightly edited for clarity and length.

Financial Planning: What are your overall feelings about AI in wealth management? Where is it headed?

Dani Fava: I’ve been working with artificial intelligence for about eight to 10 years. It’s incredible to see generative AI now come onto the scene, it feels like overnight and becomes accessible to every person. We have been working on predictive data analytics and machine learning for a long time behind the scenes. There were these big promises that felt for a while like they weren’t coming to fruition. We were doing some cool things at TD Ameritrade with fraud detection and predicting a client departure. But now with the advent of ChatGPT and the open-access availability of large language models, the future seems limitless. It’s happening incredibly quickly.

I’m a techno-optimist. I’m incredibly excited about what generative AI is going to do for the financial advisor space. It’s aligned with where we focus quite a bit. There are, generally speaking, two ways an advisor can grow: by increasing the number of households that they manage or by going upmarket. It’s clear AI is going to increase efficiency and the number of households they manage. We thought we capped out at 150 clients per advisor. An advisor could never manage more than that. I think AI is going to challenge that. In three to five years, that number is going to double. Many tasks will become automated. 

What’s going to matter is the personal relationship that the advisor has with the client, the ability to explain complex scenarios and meet complex needs and be able to translate that into something that makes sense for a client. Our tech stack [which includes AI-powered note-taker Zocks] is focused on delivering those automated capabilities, freeing up the advisor and focusing on that relationship. It’s going to be consistent across the industry.

FP: In my discussions with advisors for our Show Me Your Stack series, if they do use AI in their practice, I consistently hear it’s in the back office — rote, repeatable tasks behind the scenes. They seem mostly comfortable with that. It’s less about client-facing uses. Do you see that dynamic changing? And are you at all concerned the human might not be in the loop any longer if it does go that route?

DF: I do think it’s going to continue to make its way to the front office, but I think it’s always going to stay in a way that augments the advisor’s relationship with the client. We’re not just transcribing and summarizing the meeting. We’re capturing the task that the advisor needs to do. We’re updating those tasks in the CRM, and prompting the advisor to complete them. 

In some cases, we’re using agentic AI [capable of behaving autonomously using independent decision-making] to complete the task. For example, on a call, I asked the client to send me their tax return. I can see that I didn’t get that tax return yet. Agentic AI can create a draft email and drop it in my Microsoft Outlook that I can send to the client, reminding them. We are not only transcribing the meeting but also doing all of these automated workflows that are also powered by AI to continue to enhance that advisor-client relationship and make it easy for the advisor to complete the task.

Inside of that meeting transcription, we capture the client’s interest. If the client said they went whitewater rafting, we’re capturing and storing that. In the next step, we will be able to curate information for the advisor to share with the client based on their interests. Now, that doesn’t take the human out of the picture at all. What it does is it makes the human a way better partner. If you think about all the people you know that you want to stay close with in your life, you could have augmented AI giving you insight that you could share with that person. Like, “Hey, I thought about you when I saw this article.” It doesn’t replace you at all. It just makes you a better friend and partner.

We think about other industries that have been automated, and you can apply the same logic there. If you need to get a routine surgery like an appendectomy, it’s quite possible that a robot is going to perform that surgery. I’m OK with that. Robots probably have a smaller margin of error. But what I want is to sit down and talk to a doctor about what’s going to happen. I want a human being to tell me that I’m going to be OK, and explain what my recovery is going to be like. A lot of these surgeries and procedures have been automated, but that doesn’t lessen the value of a doctor. It’s only shifted their focus and skill set they need to have to be successful. We’re going to experience the same thing in the advisory space.

FP: You describe yourself as a “techno-optimist.” I’ve written several stories about fears, especially around cybersecurity, relating to AI. What are your main concerns with this technology?

DF: Agentic AI is happening next. Another thing that’s going to happen is artificial capable intelligence. Rosey the Robot from “The Jetsons” is going to be real. Very soon we’re going to have AI in our homes capable of performing tasks like folding the laundry. 

Again, I’m a techno-optimist, so I think this stuff is all amazing. But I’m aware that throughout written history, bad actors have been able to have more of an impact, based on technology. We started with a bank robbery that would be committed by a single person at a single branch to rob a single teller. Then ATMs came on the scene, so a bank robber was then able to rob a whole city’s worth of ATMs. Then we moved to the cloud. So now a bank robbery is stealing the identity and hacking into thousands of people’s accounts. This concept is nothing new. There’s always going to be a bad actor. Now technology is giving them more access, power, reach and scale. In the same way we say you get scale on the efficiency side with this technology, it also gives scale to nefarious actors. It’s going to continue to happen every time we make leaps in technology. There is that side of the equation.

I do believe that AI will solve this problem. AI will cause nefarious actors to have a broader reach, but it also increases our ability to control because of how quickly we can learn scale and deploy fixes to the problem. AI and machine learning will be able to prevent cyberattacks using AI to combat the various factors, which will be able to scale more. It balances out, as we’ve done on every other technology innovation. The good will outweigh the bad. We will learn how to protect data and systems from a cyber perspective, which we’ve proven to be very good at. It’s a net benefit.

FP: What is the best piece of advice you’ve ever received?

DF: I try very hard not to draw conclusions until I have all of the evidence. That’s helped me in my career. There are so many biases that we are victims of, like confirmation bias and recency bias, I try to keep an open mind and fight against those biases. That will open your perspective, and give you an edge that you know other people don’t necessarily have.



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