Understanding the Future of Robo-Advice

Understanding the Future of Robo-Advice

For many technology savvy private bankers Robo-Advice is the place to be, for others it’s the worst nightmare. Again others, see in it a hype that will soon disappear. To make up your own opinion, it is key to understand the drivers behind Robo-Advice, that is the business model. In this insight we provide an high-level analysis along four strategy views, i) financials, ii) customers, ii) products and services, as well as iv) capabilities.

When talking with private bankers about the future, the buzzword Robo-Advice is not far away. But what is Robo-Advice? Some argue it is an investment product. Others see it as a service to the less fortunate. Some see it as a distribution support tool. Again others, mainly from the tech side, see it as a disruptive piece of software. Or is it an algorithm based on modern portfolio theory, that amends or replaces human thinking? Or is Robo-Advice no more than a user interface to a portfolio management system for millennial customers? There does not exist a single right answer, and Robo-Advice is little bit of everything. Nevertheless, any Robo-Advice system exhibits four key characteristics:

  • It provides interaction with the customer through a technology driven platform rather than through a human user experience.
  • It delivers some sort of investment advice electronically, to support or substitute customers’ investment decisions.
  • It includes an automated trading mechanism in a portfolio context for implementing transactions and rebalancing portfolios.

Market trends

To better understand Robo-Advice, let’s review current market trends. At the end of 2014, $19 bn. assets were managed by Robo-Advisors, comparing with $25’000 billion retail investable assets in the United States alone. Although small in absolute figures, growth rates of over 65% have be observed, and some analysts consider them sustainable. According to a report by KPMG, about $2’200 bn. will be managed through Robo-Advisors by the end of 2020.

Four different trends towards approaching Robo-Advice can be observed:

  • Banks enter the Robo-Advice market by acquiring or collaborate with pure FinTech players, like Blackrock acquiring FutureAdvisor, Jemstep being acquired by Invesco, or UBS signing a collaboration deal with SigFig, to name some of the most prominent deals.
  • Financial services companies build their own proprietary Robo-Advisors integrating with their existing advisory and / or custody platforms. Most prominent examples are the Personal Advisor from Vanguad, Schwab’s Intelligent Portfolio Solution, or in Switzerland, Swissquote’s ePrivate Banking and Glarner KB’s Investomat.
  • FinTech start-up companies operate as independent financial service firms. They own the client relationship and offer the whole investment value chain in a transparent way to investors. In most cases, these companies outsource some of the backend part of the business, like custody or trade execution and settlement, to traditional players. The most prominent players are Batterment ($3.2 bn.), launched in 2010, and Wealthfront ($2.6 bn.), and in Switzerland, TrueWealth ($28 mn.).
  • Finally, there exist various technology companies that offer Robo-Advice solutions under a while-label framework, like meetinvest for single stocks, or Dufour Capital (both from Switzerland), to name just a few. In addition, there exist many players that offer building blocks aiming at financial service companies building their proprietary Robo-Advisors. They range from traditional portfolio management system providers like Avaloq, Charles River, Latent Zero, Simcorp, or Temenos, to innovative FinTech companies like Additiv, Advice Online, Investify, or Edge Laboratories, to name some of the main Swiss players.

Business models

There exist more than 600 Robo-Advisors worldwide implementing about ten different types of business models. Independent under what trend Robo-Advisors were borne, they try to excel along one of the four strategy views:

  • Financials – primarily competing on price, focusing on being significantly cheaper than human centric investment advisory or discretionary mandate solutions.
  • Customers – focusing on servicing customer segments that cannot be serviced profitably in a human centric world because of the limited asset base.
  • Products and services – focusing on delivering investment performance through an app-based user experience, mainly aiming at millennials, which look for anytime-anywhere solutions.
  • Capabilities – integrating / disintegrating the investment management value chain, focusing on those areas where unique value through unique capabilities can be delivered and outsourcing the remainder to traditional players.


A majority of all Robo-Advisors compete primarily on price. The most prominent pricing model is all-in fee, with prices in the United States around 0.25% (Vanguard, 0.3%; Schwab, 0.0%; Beterment, 0.15%-0.25%; Wealthfront, 0.25%; SigFig, 0.25%) and in Switzerland around 0.5% (Truewewalth, 0.5%; Investomat.ch, 0.6%, Swissquote, 0.95%-1.25%; Pritle, 0.5%).

Some Robo-Advisors differentiate themselves through special pricing model features. For example, Schwab does not charge an explicit fee for its Robo-Advice, revenues being incurred through implicit management fees of the used investment vehicles. WiseBanyan also offers its service for free, recouping costs through add-on services. WealthFront and SigFig try to attract investors by offering a 0% fee on the first $10’000 invested. Pritle takes a different approach by not charging a fee for any investment above $250’000. Motif Investing implements a transaction cost model where, rather than to charge for individual transactions, customers pay a fixed fee of $9.95 for a basket of trades. In contrast with traditional investment services, it is uncommon to have staggered all-in fees.

Investors prefer all-in pricing models, similar to paying the cable bill, that are, simple, transparent, and predictable. Customers are price sensitive, but look at the value received for the price paid (and compare with the prices of competitors’ offering similar value) rather than going for the cheapest offering.


Two different types of customer centric business models can be observed, i) those that focus on technology savvy customers, namely millennials, and ii) those that focus on customers that cannot be serviced profitably through the traditional business model based on human interaction.

For technology savvy customers the trust factor is initially high as they feel comfortable relying on technology rather than human judgments. It remains nevertheless an open question to what point their needs can be satisfied through Robo-Advisors. FinTech start-up companies mostly focus on this customer segment.

On the other side, there exists an ever increasing segment of customers that can no longer be serviced profitably under the traditional human centric business model, amongst others due to increasing regulatory costs. It seems legitimate to service these customers using technology. Large banks and asset managers predominantly focus on this customer segment to reduce their cost base and increase profitability.

Focus on servicing customer segments for which you can provide value through Robo-Advice. Avoid segmenting customers according to the costs incurred by servicing them, or you will be trapped in the cost spiral. And don’t forget to take into account customer acquisition costs!

Products and services

Robo-Advisors trying to position themselves through superior products and services are rare. Although many provide investment performance track records and back-testing simulators as part of their service, most fail to sell their investment capabilities as part of their value proposition. They rather focus on the techology platform form delivering the Robo-Advice.

Define / review you Robo-Advice offering through the eyes of an investor who is primarily interested in investment performance, but is unwilling to blindly trust technology.


Most technology companies, whether start-ups or big players, compete through their technology capabilities. They either differentiate themselves through

  • offering superior user interface technologies leading to a superior customer experience,
  • providing modules allowing their customers to build customized Robo-Advisors in an agile way, or
  • making available models solving specific challenges faced when building Robo-Advisors.
When deciding to build a Robo-Advisor yourself, rely on off-the-shelf components from technology providers for any capabilities that are not key for differentiating your solution. Only invest in developing those technology components yourself that will support your value proposition and expected competitive advantage.

Four steps to success

Based on our experience we recommend the following four step process for introducing Robo-Advice:

  • Start by defining what you want to achieve and whom you want to serve. Focus is key!
  • Identify the components of the value chain you want to outsource to your customers through the use of technology. Validate your assumptions!
  • Design the interaction with your customers, including the channels to be used, along the customer journey. Ensure that your customers never feel left alone!
  • Price your offering taking a customer standpoint. Focus on offering value for money rather than effort for money!

If you fail at any of these steps, chances are very high that you will fail overall, or at least end being average! Don’t be afraid to seek help, if and when needed, to get a fresh view and allow for a closer examination!

Success will be defined by the success of the implemented Robo-Advice business model rather than the technology used.

If you’re interested in learning more or want to discuss potential opportunities for your business resulting from these challenges, please don’t hesitate to contact me!

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