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How different approaches to AI will shape the future of Wealth Management

It took seven years for the internet to reach 100 million users. It took ChatGPT just 60 days. Over the course of the two years since that milestone achievement, the wealth management industry has emerged as a proving ground for the power of artificial intelligence (AI) to transform client engagement, reinvent proprietary research, and redefine business models. The phenomenon has also stirred a great deal of speculation about the pace of AI adoption among firms and what it means for the future of the industry.

AI adoption by-the-numbers

Broadridge recently put a spotlight on this uneven approach to AI with the findings of our fourth annual Digital Transformation Study, which found that even though 72% of firms are prioritizing investments in AI, there is a wide gap emerging between those that are leading the way on AI adoption and those that have yet to take the plunge. In fact, we found that 51% of firms characterized as digital leaders are already investing in AI while just 22% of non-leaders are investing in AI.

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Beyond the numbers: the real-world perspective

As we’ve continued to dig deeper into the findings, talk with clients, and evaluate our own experiences, the gap between leaders and non-leaders on overall AI investment is just part of the story.

The real insight is in how different firms are using the technology, the kinds of business cases they are developing to support future investment, and how they are rolling it out across their organizations. Those details are increasingly influencing high-level business strategy for firms that are leading the way on AI adoption and helping to create a roadmap.

To better understand how those nuances are manifesting themselves in the real world, we sat down with key members of the Broadridge team who’ve been working on the front lines with the leadership teams of some of largest wealth management firms, small and midsized firms, and individual advisors to refine their current AI strategies and chart the course for the future. Here are some of the highlights.
Firm Culture and Values
Michael Alexander
President, Broadridge Wealth

Key takeaways for Wealth Management firm leaders

1. AI prioritization forces conversation about firm culture and values: Like any technological change, whether it’s the cloud, the internet or the iPhone, you have people who are early adopters, those who play it safe and everything in between. What’s different this time is the multiple ways that AI is being leveraged across different functions and how – increasingly – it’s helping firms lean into their unique differentiators.
2. Lean into existing strengths: The technology available today is making it possible to rethink ways to improve every aspect of the wealth lifecycle, from prospecting to governance to capturing clients’ values and goals in a more systematic way. The areas firms choose to prioritize say a lot about how they see themselves in the marketplace and will soon start to play a key role in how they are defined by clients and prospects.
Mike

“This is the worst AI is going to be in our lifetimes. That’s a critical realization many firms are coming to now that they’ve seen how quickly AI is being adopted and how powerful it can be once it starts to get integrated into existing research and communications tools. Even firms that may have been a little skeptical when ChatGPT first launched are now seeing its potential in things like improved advisor productivity, client engagement, and investment research.”

Michael Alexander, President, Broadridge Wealth

Enhanced Operations
Ramprasad “RP” Sandilya
Vice President, Chief Growth Officer, Wealth Management

Key takeaways for middle- and back-office professionals

1. Work towards a unified data model: It’s time to be more strategic about the middle- and back-office functions inside wealth management firms. When you look at all the various tax data, corporate actions, proxy reports, performance reporting and other operational data that firms must produce and catalogue each day, you quickly see that upwards of 80% of that data is the same – it’s just being used for different purposes and in different contexts. AI-powered analytics are making it possible to bring those complementary data points and processes together and reengineer the entire process to solve the big data cleansing and harmonization challenges people have been wrestling with for decades.
2. Unlock professional growth: Many financial operations professionals still approach AI with a sense of fear that it will replace them. In fact, it represents the greatest opportunity yet to help them level-up by democratizing access to the best ideas, most groundbreaking strategies, and proven expertise. We now have the ability to harness the accumulated knowledge of our star performers and convert that expertise into chatbots and training tools that help younger and less-experienced employees learn from the best. AI presents such a huge opportunity to grow for people who are willing to embrace it.
RP Sandilya

“There is a tendency when talking about the prospects for AI in middle- and back-office operational functions to get reductive and focus only on workflow improvements and automation. That’s an incredibly narrow vision of the role of AI in wealth and one that does not address its enormous potential to transform the way we think about big challenges like data harmonization, new product development, and employee engagement. We have an opportunity to revolutionize financial services simply by capturing and utilizing the exhaust from countless operational functions. It’s time to get creative about how we operationalize AI.”

Ramprasad “RP” Sandilya, Vice President, Chief Growth Officer, Wealth Management

Trust in AI
Joseph Lo
Head of Enterprise Platforms

Key takeaways for technology leaders

1. Without trust, AI is nothing: It doesn’t take long for anyone using AI for the first time to immediately see the value in the technology. The usefulness is not the hard sell in wealth management. It’s the trust. An advisor will not be able to use AI if investors cannot trust that those advisors are using it well, so it’s really incumbent upon firms and technology companies to not only build reliable, accurate solutions, but also to educate end-users on how, when, and in what contexts they should be using it.
2. Think bigger: It’s still very early days in the evolution of AI in wealth management. Right now, we have technology that lets you ask a question and immediately get an answer. But, what’s to stop you from creating a massive dashboard of potential questions and answers and running detailed analytics every time those answers change to get insights on market sentiment, client challenges and pain points, or make strategic business decisions? It’s important that we develop technology within the confines of what’s possible today but also keep the agility and vision to keep growing and scaling those capabilities into the future.
Joseph

“Whatever numbers you see out there about the level of AI adoption among advisors, they are under-represented. Everyone is using AI. They may not be using it on their work desktops and it may not be built into enterprise workflows, but they are using ChatGPT on their phones and in their personal lives. And that presents a big challenge for the industry. The number one impediment to AI adoption right now among advisors is balancing this whole new spectrum of dos and don’ts, in many cases without a lot of guidance from their firms. There’s a huge opportunity for firms right now to help bridge that gap.”

Joseph Lo, Head of Enterprise Platforms

Client Engagement
Alicia Rich
Head of Client and Advisor Digital Enablement

Key takeaways for advisors

1. It’s still early in the AI maturation curve: Some of the largest wealth management firms have already made huge strides integrating all of their proprietary research into AI models to create research tools for advisors. From there, we’ve seen many firms start to make progress using AI in marketing to help create more precise, personalized client segmentations. Those are great steps, but they are not revolutionary.
2. Devil is in the details on client-facing AI: The revolution will come when AI starts making inroads toward more direct interaction with clients. How and when firms deploy those types of technologies will really shape the next phase of AI evolution.
Alicia

“The real test of firms’ and advisors’ comfort levels with AI is coming. So far, for the most part, we’ve seen AI being used to summarize – capturing key research insights, analyzing customer segments, etc. – in scenarios where human advisors are still the intermediaries between the technology and the client. As we get to a point where the AI-derived research and client analytics can be used to lead conversations with clients, advisors will need to be very comfortable with the technology.”

Alicia Rich, Head of Client and Advisor Digital Enablement

AI Maturity
Alok Gupta
Managing Director, Wealth Management
and Asset Management Practice Lead

Key takeaways for technology leaders

1. Think beyond today’s bright, shiny thing: Although the last two years of innovation in this space has conditioned many of us to think that AI innovation is all about the bright new shiny thing – the new fine-tuned LLM or the most accurate agentic reflection model – but for wealth firms, the real value in AI is not in the tools themselves, but in how they are deploying them.
2. The business case should drive the tech focus: The real question wealth firms need to ask themselves right now is: How can I take this AI and make a new business capability? The answer to that will fundamentally shape future business strategy.
Alok

“Total firm spending on AI only tells part of the story. Many firms have spent a ton on technology over the past few years, but they have not yet figured out how to extract value from those investments, while others have invested far less, and they are already seeing transformative results in pockets of their business. There is no one-size-fits-all solution when it comes to AI in wealth. The real measure of success is around AI maturity – how are firms defining their goals and what are they doing to get there.”

Alok Gupta, Managing Director, Wealth Management and Asset Management Practice Lead

A Solid Data Foundation
James Connell
Vice President, Strategy and Business Development

Key takeaways for Wealth Management operations and tech teams

1. Get your data house in order: One of the biggest challenges confronting firms who are lagging in their AI adoption is that they cannot simply buy a plug-and-play solution for many of their desired use cases. Let’s say, for example, a firm wants to use AI to quickly identify all clients who have a specific value that is important to them (e.g., ESG), and then provide recommendations to incorporate this value into an investment strategy or a targeted marketing campaign. To receive truly personalized AI recommendations for each client, the model will need access to vast amounts of client and market information, requiring firms to have an orchestrated system for their data, much of which remains in silos today.
2. Don’t go it alone: There is a tremendous amount of complexity in implementing data standardization, migrating to cloud systems, and deploying AI models. Establishing the foundation for success will require substantial resources but offer firms limited immediate return on investment. Where they will realize the benefits of their investments is in the revenue-generating and cost-savings initiatives they can pursue once their foundational, next-generation technology is in place. The ability to work with technology and solution specialists who can help facilitate the necessary transformation and back-end support will be critical to the success of firms in the race towards an AI-empowered future.
James Connell

“As AI evolves from point solutions and proof of concepts to more fully integrated research, client management, and workflow optimization tools, wealth management firms are realizing that selecting the right predictive or generative AI model is just part of the equation. For many of the more innovative, high-impact use cases, the bigger and more challenging component of execution is developing more centralized and accessible data systems. This is an area where technology partners and service providers can play a key role in helping firms accelerate AI adoption.”

James Connell, Vice President, Strategy and Business Development

Want to learn what others in financial services are doing on their digital transformation journey?

Read the results of the Broadridge 2024 Digital Transformation & Next-Gen Technology Study. 

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