Community Banking: Wealth Management and the Rise of Robo-Advisors

In what has become a much more competitive and broadly undifferentiated financial services marketplace in recent years, community banks often see wealth management as a way to capitalize local knowledge to increase their value to customers and so find new sources of revenue.

But new firms, known as robo-advisors, are entering the wealth management sector and growing quickly. Nearly a third of millennials or generation Y (those born between the early 1980s and early 2000s) and 16% of generation X (mid 60s to early 80s) either already use or are planning to use a robo-advisor for their wealth management needs (see chart 1).

If community banks are to succeed in their wealth management ambitions, they’ll need to understand robo-advisors and make sure they position themselves against – or alongside of – them.

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Chart 1: How likely are you to use a robo-advisor?  n=94 (gen Y); 160 (gen X); 208 (others)  Source: CEB 2016 HNW Client Experience Survey

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More Advisor, Less Robot

Many traditional advisors seem unclear about what robo-advisors offer. And it’s easy to understand why: “Robo-advisor” is an unfortunate term, as it suggests the main aim of technologies is to displace human advisors with algorithmic “robots.” It isn’t (chart 2 provides more clarification).

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Chart 2: Technology-enabled advice in financial services  Illustrative  Source: CEB analysis

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If you think of the traditional interaction between customers, financial advisors, and institutions, there is a clear sequence of steps: The customer shares their information and aspirations with the advisor. The advisor then takes the output of that conversation and uses certain institution-provided tools to produce results for the client (a risk-optimized model or target portfolio, etc.). The advisor then delivers that to the client.

In theory, the conversation then continues, with the advisor adding value by extending beyond the simple output of the tools to speed the customer’s progress towards their goals (in practice, it is not clear how many advisors and clients have the energy to continue beyond these initial steps, given all of the back-and-forth).

The robo-advisor model doesn’t suggest the traditional model has the wrong components, instead, it suggests that the steps are in the wrong order.

Rather than the customer’s initial interaction being with the advisor, the customer first interacts directly with (traditionally institution-provided) tools, and the creation of a model portfolio that optimizes for risk and return is automatic.

Customers and providers can stop there and be confident they have captured some value, and some robo-advisors indeed do stop there. But robo-advice platforms also allow for advisors to contact customers after this first interaction, and begin the advisory process after all of the commoditized early steps are completed. That’s more efficient for providers, certainly. But it is also much more efficient for customers.

How to React, Now and in the Future

The rise of robo-advisors, their broad appeal to the majority of customers, and the strong value of their offer (to both providers and to customers) means that as community banks consider their wealth management strategy they should think across three different time frames.

1. In the near term: Community banks should consider the comparative merits of their offer and pricing (especially in non-fiduciary platform brokerage) as compared to the major robo-advisors, to ensure that both employees and customers see a meaningful reason to choose the bank.

2. In the medium term: Community banks should consider a partnership with a third party provider (this time a robo-advisor) in order to provide capabilities it would be difficult to build internally.

3. In the long term: Community banks should prepare for a competitive environment in which robo-advisor-style tools and approaches are considered a fundamental part of the wealth management offer.