The advice gap is a problem our industry discusses frequently, yet it is still increasing.

In my earlier article, A Look Around the Technology Corner at SIFMA Ops, I shared data that FNZ published recently with Boston Consulting Group (BCG) in our report Scalable Tech and Operations in Wealth and Asset Management.

If you read that article, you’ll see a review of challenges in cost to serve and return on investment for technology spend. Why should this matter so much to wealth management firms? Two words….

Advice Gap

The advice gap is a problem our industry discusses frequently, yet it is still increasing.

In the US right now, there are 330K financial advisors and 160 million potential investors. That’s almost 485 end-investor clients per advisor who need help. The average advisor today services between 50 -100 end-investors. Only about 35 percent of Americans claim to work with a financial advisor.¹

That’s a big gap. It’s a major issue.

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Not only is there a major gap right now, but the average age of a financial advisor is early 50s, and many are starting to retire. Too few new advisors are coming into the field, which means this gap will only accelerate.

This growing challenge is central to any discussion we have about our industry’s future. Advisors rely on institutions to provide technology and systems that can help them, but many are inhibited by old technology. I’d argue this is stifling innovation. Advisors and other key associates end up spending too much time on low-value tasks, instead of serving client needs with more personalized service.

And speaking of personalized service… End-investors are needing more - asking for more - from their advisors. Institutions need to invest in technology that can help more advisors serve more end-investors and grow their business. It’s a common refrain: “We need to serve more with less.”

What Happens When End-Investors Go It Alone?

We know that end-investors feel more confident, more comfortable when working with an advisor. Some studies put the actual returns on portfolios at 1.5-4 percent higher for people working with an advisor.

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But what this chart shows might be more important. This is recent global data from our FNZ platform. What we see here is a significant difference between end-investors who are self-serving versus those who are advised.

I notice two key differences:

  1. It’s clear that non-professionals have a difficult time acting rationally during times of market distress. Look at the last three market shocks – the direct, self-serve clients ended up “dashing to cash,” likely acting against their own best interests. Those investors probably sold low to move to cash (when interest rates were low so their cash was not working hard for them), and then re-purchased when assets were more expensive.

  2. On the other hand, over any time period, end-investors working with advisors have consistently kept more money in the market, holding lower amounts of cash. There might be a variety of reasons for that, but I suspect that means their savings are being put to better use. Cash is typically a drag on portfolio performance.

This highlights the importance of a sound financial plan structured and managed by a financial advisor.

So how do we fix this? The only way to achieve this is continued investment in technology that enables firms and financial advisors to do more with less.

Can AI Help Bridge the Gap?

Increasingly, the industry is looking at artificial intelligence (AI).

Artificial intelligence is going to be deployed across our industry, without question in my mind. It’s already happening. We need to embrace it, but with caution. We are still in early stages here. And financial institutions don’t know everything about how this can help or hurt growth. This is illustrated by the wide range of institutional firm reactions to ChatGPT’s launch.

Some financial institutions immediately started looking at ways to help advisors be more effective, using generative AI. They are looking at how to provide better service to more clients, more efficiently. On the flip side, others decided to restrict usage, at least for now, until we understand all the details around generative AI. This is also understandable – the power of these tools is still unknown, and then there are questions around who owns the IP.

Whichever end of the spectrum you’re on, assume AI is going to happen. It’s incredibly powerful. And potentially horrifying.

This is a fascinating area. I’ve been reading “Scary Smart” by Mo Gawdat, former chief business officer at Google. In his book, Gawdat says that by 2029, machine intelligence will break out of specific tasks into general intelligence. By then machines will be smarter than humans because they will have access to the entire internet. By 2049, AI is predicted to be a billion times smarter than the average human. This moment is when we reach the singularity.

So, what do we do right now to make sure we harness this power to determine how it will help – and try to work out how to prevent the potential harm? Ignoring it is the wrong approach.

Near-Term AI Applications

There are already near-term ways we’re harnessing AI, helping close portions of the advice gap right now.

We already have a terrific amount of intelligence and computing power to produce the most optimal portfolios for clients, on a consistent basis. This is an obvious way AI is helping advisors focus less on investment management and more on strengthening client relationships, ultimately growing their practices. For example: We already have algorithms that can scan millions of accounts and find opportunities to optimize investments across all those accounts, in seconds.

The other obvious use case is in operations. AI in operations – machine learning using big data - will free up time. Is already freeing up time.

An example is reconciliations. As a business grows, there will always be exceptions. Exception management has always been challenging. Now AI can learn to handle those exceptions. This can now be solved in real time with access to the right data sets. We can write intelligent algorithms and queries and can start to solve these types of exceptions automatically in real time.

I urge you to explore these current AI applications, if you aren’t already, while also looking around the corner at what generative algorithms might mean to your business in the future. A shrinking advisor population is being challenged to deliver more personalized service and solutions to more end-investors; I believe technology and the use of AI, if deployed responsibly, will be critical to helping close the advice gap.

By Tom Chard, CEO of North America

In collaboration with B. Blake Howard, Global Head of Solutions Marketing

1. SmartAsset, The Latest Financial Advisor Statics, 2023

The information contained within this publication is not intended as and shall not be understood or construed as financial advice. The information provided is intended for educational purposes only and you should not construe any such information or other material as legal, tax, investment, regulatory, financial or other advice. Nothing in this publication constitutes investment advice, performance data or any recommendation that any security, portfolio of securities, investment product, transaction or investment strategy is suitable for any specific person. FNZ Group and any of its affiliates are not financial advisors and strongly advise you to seek the services of qualified, competent professionals prior to engaging in any investment.

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