For over 25 years, Uma Meyyappan has been a technology executive working in wealth management and financial services, and she is a pragmatist: Even in the era of generative AI, she says, “Do not speak too broadly about the impact of technology in generic terms…be really grounded in a use case or a case study.”
Meyyappan is currently Senior Vice President, Supervision & Regulatory Control Technology, at LPL Financial, and we spoke with Meyyappan about AI, partnering, and talent as part of our research report, Creating New Value in Large Organizations: What It Takes.
With $1.1 trillion in assets under management, LPL Financial is the largest independent broker-dealer firm in the US.
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Tell us about your current role, and how past professional experiences tie into your current role.
I was at Wells Fargo in different roles leading up to being a key innovator, trying out new things where I thought the company should be, and setting up different labs to test a variety of emerging technologies. Using emerging technologies to add business value is always the key. I led and produced multiple new initiatives across different organizations. I moved into my current company, LPL Financial, to launch an innovation group. After that, the company needed additional help taking on key engineering development groups. This is an area where a lot of new application development is going on… a lot of innovation opportunities exist in this particular domain for internal innovation.
At a high level, I have always been really passionate about bringing new technologies to an organization to propel business value by using emerging technologies and new ideas. And not through rocket science or complex things, but by simplifying things. That has been a key approach for me. And along the way, I became very passionate about women in tech — mentoring, speaking, and helping women in tech succeed.
How does your department define value creation in 2024?
First, the key thing is building awareness of newer technologies. Second, you need to create that “innovation DNA” across the company. You should always continuously be exploring things in a lab. Business units usually only do things when it is a true internal requirement. Whenever you are asked to meet a business need for the direction of the company, always think of options to modernize what you have. Every single sizable company will have some sort of tech debt. So, whenever you touch code — and have the opportunity — try the new approach and modernize it with new tech.
Does your organization have strengths and/or weaknesses in value creation? What are your priorities for the remainder of 2024?
We have set up a true AI Accelerator and are setting up foundational things for next year to put a lot more effort into AI — not AI for the sake of AI, but all the new things that we need to build for cost reductions. We are looking at everything. 2024 has been more tactical this year, but at the same time, the AI accelerator has been set up — which we will latch onto next year for more strategic innovation.
What has been the response to the hype cycle and or real business impact of AI in the last two years?
With all emerging technologies, you’ve got to sell it internally. Again, people just do what is required. Data science and modeling have always been central to what we do and how we deliver value to the organization. But ChatGPT is easier, and people caught onto it — like “a kid in a candy store” is the phrase that comes to mind. And people thought, “Oh my god, it is like a new magic wand.” So, ChatGPT gave us a little bit more visibility and made what we do more tangible. AI could clearly solve a lot more problems. It has provided awareness to the business folks, and [that] helps with prioritizing and budgeting future projects.
How important are value networks, platforms, and ecosystems to your organization’s strategy? Can you describe how your organization participates in or contributes to industry ecosystems or value networks?
Strategic partnerships are key. But we are still a financial services organization, so we have to be really careful about things that we put out externally. We will not be doing any common or large external language models (LLMs), for example. We would be building things on our own, and unless it is a private cloud-type thing, we will not, in any sense, go to all the big names out there and expose our data. So, we would partner and try to get a version of any models for our own purposes because we are highly regulated.
What is the role of talent in value-creation efforts?
I think finding the right talent is important, but finding the right talent at the right time is the issue… What we are finding out is young talent, like fresh grads, they come with a lot of knowledge about technology, but they are really raw and don’t necessarily have any business knowledge. …Either you take a seasoned person and train them in the new tech, or you take a new person and train them in business practices. We have to do both and find the right balance.
With my efforts in women in tech, when I look at that diversity in general — not just women in tech, but true diversity — that definitely becomes another angle we look at. For the existing people who are already in the workforce, we do training and mentoring. It is something that needs to be done constantly. Are we where we want to be? No, absolutely not. We need to continue our efforts because it is not like ChatGPT changed all the world’s behavior. The talent challenge still remains.
Deliver more than you promised, and never make it all about presenting decks. You are going to fail if it is all about updates via deck presentations.
What is one piece of advice you commonly share with other innovators in big companies?
I would say innovation acceptance always needs to come from the top down — or else the group will fail immediately. Innovation teams are often seen as sitting on the edge of the organization and not doing anything. You have to find a senior leader who is an innovator to get the buy-in…. Lab projects and R&D efforts need to solve the real problems of the company, and not just come up with new ideas for the sake of new ideas. Do not speak too broadly about the impact of technology in generic terms… be really grounded in a use case or a case study. Closely partnering with technology executives, taking a pain point, and solving it for them without hindering their current flow and without saying, “I need your time and I need more money.” Listen to them. Take the use case, solve it separately, and give it to them. Deliver more than you promised, and never make it all about presenting decks. You are going to fail if it is all about updates via deck presentations. Do more — and show them tangible results.
