The Next Generation of Robo-Advisors

This is a guest blog post by Thomas Brand, management consultant at Accenture.

The traditional defense for human financial advisory boils down to a deep faith in the excellence of human reasoning and intelligence, coupled with more or less positive view on the emotional capacity and intuition of human beings. Most people who believe in human financial advice view it as an indisputable fact. The argument for human advantage is similar to the “god-of-the-gaps” reasoning, for the people familiar with some philosophy of religion. Many public arguments are based on a fallacious view of technological progress; it’s argued that robots and software agents can’t do this or that at the moment, and therefore it can be argued that it’s highly improbable that anything remarkable will happen in the near future. “Robots don’t have gut feelings, so they can’t make ‘soft’ decisions. Sometimes you just need to act even if you can’t immediately justify your view on certain issues. You just… feel that it’s the right thing to do,” some advisors might argue.

It’s true that for a long time, portfolio management, asset management, wealth management and financial planning have been exclusively done by humans, aided by software and mathematical modeling, and these different financial services have been offered as standard products (the product-centric view) and more or less personalized solutions (the manufacturing-centric view) for the clients. [1] This status quo has been challenged by the changing customer behavior and needs, transformation created by the new leading digital incumbents (FATBAG), the continuing blurring of industry boundaries, the transition from value chains to value constellations, the emergence of financial technology, and especially, an increasing number of robo-advisory services, perhaps redefining the concept of financial advisory altogether. Key changes have created a truly challenging playing field for the financial advisory industry, with a bunch of new and demanding imperatives when rotating to the new brave world. Multiple challenges posed by external and internal changes are forcing financial advisors to transform into something very different to remain competitive, efficient, and successful businesses.

With the emergence of simple unlinked portfolio management tools (with Mickey Mouse money) and robo-advisory, clients can now directly access semi-advanced and advanced investment and analysis tools on themselves without introducing themselves with all the nuanced details of optimal portfolio selection, factor models, diversification, hedging, and risk management. The well-known cost, time, and quality constraints that plague human advisors have shifted both advisors’ and clients’ attention towards better, more advanced alternatives. From the sales point of view, robo-advisors can serve as a tool for better sales support, increased sales performance understanding, and improved sales force effectiveness and productivity. For clients, though, robo-advisors serve can serve multiple difference purposes as for example many low-income individuals it can be very hard to meet the criteria and minimums imposed on customer profile and investable assets.

For example, Nordea Bank, a Nordic financial services company, has recently established 34 Premium branches in Finland for affluent customers, who have at least 100 000 euros in investible assets. Someone could point out that 100 000 euros isn’t actually very high threshold but at least in Finland, it actually is. For small investors, this kind of thresholds might not be so repelling aut for the robo-advisor these kinds of boundaries and constraints create real potential for growth in terms of customers and assets under management (whether we talk about challenger’s or incumbent’s digital wealth management offering, e.g. robo-advisors). If a robo-advisor has an attractive value proposition, coupled with some kind of human advisors (so-called hybrid advice model), the probability of adoption could rise even faster. Furthermore, robo-advisors are embraced by semi-DIY investors because they could now primarily focus on formulating more high-level strategy, and they might not actually be interested so much in tax planning, financial advisory, and estate planning. If these semi-DIY investors need some extra services, they most probably will focus on finding best-of-breed services from a wide variety of potential service providers. [2]

While it is relatively easy to point out that robo-advisors will (eventually) replace human financial advisors, Accenture’s recent report argues how in the alternative scenario, based on cognitive computing and smart machine interaction with humans, there is “a way to get customers and financial advisors acclimated to working with machines that can enhance and extend human performance.” This scenario posed by Accenture is not based on a bit erroneous either/or thinking but restates the fact that there probably are areas in the “client-advisor relationship […] that should remain the province of the financial advisor for the foreseeable future.” Accenture states that even though, “competition, innovation and new technology will dramatically increase robo-advisory capabilities in the near future, personal connections will [still] remain essential.” It could be argued that technology-driven robo-advisors are just one phase in the evolution of robo-advisory, and standalone robo-advisory might actually be replaced by different kinds of hybrid advisory models as investors while embracing the new possibilities robo-advisors offer to them, still might need personalized assistance from their service providers for guidance, validation, and more complex financial planning.

In practice, this means that the traditional roles of financial advisors such as “reassuring clients through difficult markets, persuading clients to take action and synthesizing different solution [options – all still human activities – will be preserved].” Therefore, at the moment, robo-advisors can mainly only complement the role, capacity and value of human financial advisors and robo-advisors are not able to eliminate them from the trust equation. The hybrid advisory model holds a great potential, and there are already many U.S.-based financial services companies offering at least some kind of version of this specific service model. The hybrid model is much more imaginative than just going fully robo or fully human, and by eliminating more mundane routines and practices with the help of lean thinking, it’s possible to leverage on human-machine interaction even more. The Senior Vice President of Schwab Wealth Investment Advisory’s Tobin McDaniel, through quite positive on the prospects of robo-advisory, claimed in an interview with Financial Times, that there are those volatile times when people just want to have a chat with a professional in order to avoid “emotional decisions that [investors] regret later.”

Echoing the ideas put forward by David H. Maister, Charles H. Green and Robert M. Galford in their book The Trusted Advisor (2001), trust is defined as an equation:

Credibility + Reliability + Intimacy
------------------------------------ = Trustworthiness

What I predict robo-advisors will do, though, is that if the traditional financial advisors do not embrace the new by being more honest and open (credibility), demonstrate dependency and consistency (reliability), try to be more empathic and discreet (intimacy), and reduce their transactional mindset and change from “I” to “we”, they will simply become obsolete. Robo-advisors will allow human financial advisors to craft more credible value propositions and cut down unnecessary and often baseless sales pitches. Robo-advisors will allow sales force to substantiate their claims, display multiple backtested scenarios and present alternative courses of action, and face the cost competition and demands for transparency and openness more proactively.

There is no magic bullet to make this happen but the customer has to come first, always. Robo-advisors can help financial advisors to better understand, recognize and respond to their customers but in the end, everything boils down to individual behaviors and attitudes towards the clientele. For example, a Finnish startup company based in Oulu, Taviq, has come up with a tool for private bankers to understand their customers better so that they can communicate the clients in a way they prefer, address what is important to them, etc. before private bankers meet them. These kind of tools, although not robo-advisory as such, are a great example of incremental continuous improvement in some aspects of the customer operations. Taviq’s solution is a great statement of the need to understand, and to be trustworthy in the eyes of the consumers and other relevant stakeholders (the trusted advisor).

Just think for a moment about the possibilities when robo-advisory is combined with personalized communication, enhanced with advanced personality analysis and investor profiling, and a human financial advisor assisting the clients throughout their individual investment journeys. As Deloitte’s recent report on the evolution of robo-advisory capabilities points out, “The trick is to choose the best approach to integrate this technology. Comparing, evaluating, and analyzing Robo-Advisory companies and their different business models is a complex task.” According to Advicent Solutions’ Patrick W. Hannon, “Robo-advisors will force advisors to use technology to add value to their services. I see a gap forming between advisors who don’t offer digital engagement/value to consumers with those that do offer tech.”

At the moment, the capabilities and implementations of robo-advisors are still its infancy (although their impact is also being felt). As for today, a typical robo-advisor employs a relatively simple questionnaire-based client profiling, goals assessment, and suggests an investment strategy follow through. When this is done, an asset allocation is proposed, adjusted and implemented for the customer. Robo-advisors can take make reactive or proactive changes to the allocation and rebalance the portfolio based on the customer’s individual investment and risk preferences as well as the return on the investment they desire. Although robo-advisors have the technical and functional ability to create a mixed portfolio consisting of equities, bonds, mutual funds, derivatives, etc., most of the current service providers are relying on cost-efficient ETF and index fund portfolios.

With the help of a robo-advisor, customers have the freedom of choosing between different offerings with different investment styles, e.g. passive, active or semi-active (enhanced index). But the major advantage of robo-advisors is not their advanced user interfaces, portfolio simulation tools, productized portfolios, etc. as people have had these at their disposal for a very long time already. The major advantage is that the advice is distributed through digital channels, and there is no need for time-consuming human interaction to manage the portfolio. Wealthfront’s past CEO Adam Nash said in February 2016 to Financial Times that automated service shines in the times of volatile markets. “The beauty of the computer is that it doesn’t care, it’s open for business every day”, Nash stated.

In a report published by Deloitte last year, robo-advisors are classified into four broad and highly simplified categories (see the picture below). Deloitte also describes different service providers at the high level; what kind of service they provide, what are their capabilities in terms of specific class and what is their offering. In another report, Deloitte has also strongly emphasized the way investments into the robo-advisory capabilities and resources can, in addition to their innovative potential, actually cut down costs and bring efficiency gains. It’s not totally clear to me, how these different generations of robo-advisors (and other digital wealth management solutions) are actually linked with the cost-income ratios and operating expenses but it can be relatively safely assumed that there is no one-size-fits-all way of calculating this as business models and operating models can be very different between the players (and therefore, e.g. efficiency gains, can be hard to estimate in the beginning of the journey).

Robo-advisor 1.0 is the most simple species of robo-advisory in Deloitte’s robo-typology. The client is served with a “single-product proposals or portfolio allocations based on listed investment products”. Wealth managers or broker-APIs are not involved in the end-to-end process so basically there is no real-world transactions taking place through the robo-advisors as clients have to buy and manage their real portfolios through their brokers. Product universe is fairly limited in terms of objectives and scope.

Robo-advisor 2.0 is a bit more advanced as “investment portfolios are created as a fund of funds” and the range of additional brokerage services is wider. Portfolio allocations are realized on a manual basis by investment managers. As discussed above, the focus Robo-advisor 1.0 and Robo-advisor 2.0 is mainly on the reduction of fees and margins, while increasing transparency and scalability of these robo-solutions.

Robo-advisor 3.0 is an advanced version of Robo-advisor 2.0 as now the “investment decisions and portfolio rebalancing proposals are based on algorithms” so that portfolio allocation is more in tune with the personal preferences of the customer. Although pre-screening and investor profiling is still based on more or less time-consuming static questionnaires, there are service providers which base their profiling on more advanced tools and processes. The investment process of Robo-advisor 3.0 is not fully automatic as the key decisions are still made by professional portfolio managers but there is more space for engagement between the robo-advisor, the human financial advisor, and the client. Some service providers will allow the investor to accept or reject investment proposals based on pre-defined investment rule sets.

Robo-advisor 4.0 is currently the most advanced form of robo-advisor as they utilized sophisticated risk management and advanced data gathering methods. Clients have the possibility to empower the robo-advisor to take the lead and make dynamic shifts between different asset classes according to changing market circumstances. In the context of Robo-advisor 4.0, the client can provide feedback to the robo-advisor based on “profit, risk appetite, and liquidity aspects” and the robo-advisor can also provide valuable insights to individual investor behavior, e.g. how to avoid losses in the volatile market conditions and leverage investments with the help of more complex financial products.

So what about those miraculous human capacities, which include the design of an optimal, profit-maximizing portfolio and sustaining trusted client relationships? I think that there will always be a place for human-based financial advice and wealth management services. However, even in the case of human-first advice, there is still a room for improvement via embedding robo-advisory and other digital tools as part of the financial services offering.

As Accenture’s report from 2015 argues, in the short term, an increasing pace of innovation and competition, mainly driven by the emergence of new digital technologies, will result in increased capacities and improved functionalities of robo-advisors. In the future, new generations of cognitive robo-advisors will be able to make more accurate decisions in much more complicated situations by proactively learning appropriate responses based both on how things went in the past (e.g. market behavior, client actions) and on their enhanced abilities to “learn on the run” (i.e. backtesting, expanding/contracting the universe of the securities ad hoc). At the moment, some robo-advisors are able to translate certain behavioral characteristics into investment plan and assimilate more complex goals into concrete action plans, e.g. adjusting the investment plans in the case of significant changes in the account balance and/or the value of the portfolio. As Accenture’s report points out, in the future, robo-advisors could potentially even help with complex tax planning and provide client’s more nuanced information about their financial behavior and actions. Although not stated in the Accenture’s report, it’s quite probable that we will witness the rise of the more sophisticated generation of integrated financial robos, which can provide a holistic overview of multiple portfolios, composed of very different asset classes, held at multiple financial institutions all around the globe.

One thing that I personally like about automatic services in general, and in robo-advisory in particular, is cleverly highlighted in the Accenture’s report mentioned above. I am very eager to “investhack” myself, i.e. I want to be a better investor today than yesterday, and the only way to be better is to better at learning. I hope that in the future robo-advisors will allow me to learn more about myself (both as a person and as an investor), and “to chart [my] own path [and to collaborate with other investors as well].” The growth path of an investor will become much more personalized, and due to new digital tools, investing will hopefully become less intimidating and more interactive with the help of new technology and digital solutions. Hopefully, wealth managers and financial advisors, will catch up with the ongoing changes and will be able to tune their value propositions accordingly.

What’s your take on the evolution of robo-advisory and its current capabilities? Can incumbents and challengers cooperate or will there be fierce competition between the two? Do you believe that the hybrid advice is a desirable goal at the moment? Do you see certain players already knocking at the frontier? I’d be happy to hear your ideas and thoughts in the comments.

To be continued…

[1] Many financial advisors and planners around the globe have already embarked their transformative journeys in order to move from the pure product-centricity towards more customer-centric models, adopting industrialization-led mindset. Their journeys to the new are and will be very different as the scope, pace, and nature of their transformation are based on diverse scenarios.

[2] A service logic and service marketing researcher working in Finland, Mr. Gustav Medberg, is currently pursuing very interesting research on the client mindsets in the context of financial services industry. As I understand his research, there are roughly two kinds of mindsets that clients have, the centralize mindset (i.e. acquire all products and services (preferably from a single provider) and the decentralize mindset(i.e. acquire different products and services from the best of breed providers).

Disclaimer: This article is based on the authors observations, thoughts, discussions and readings. Any views, opinions or conclusions expressed in this article are strictly personal. This article does not necessarily reflect the views or positions of Accenture or affiliated/related companies. The author has not received any financial or any other compensation for mentioning specific firms, services and/or individuals in this article (and mentioning these does not imply that they endorse the content of this article).

Photo Credit (Header): 174695 / CC0 Public Domain

Leave a Reply

Your email address will not be published. Required fields are marked *