Furthermore, the use of risk-based optimization engines requires a new set of skills in order to understand the approach and results generated by the optimization engines. Automation of the advisory process requires a certain affinity for IT, business rules management and process automation.  

Consequences for the client-advisor relationship

The "out-of-the-box" risk-based portfolio approach has many advantages. However, automated investment advice also poses many challenges. First, there is the switch from sell-side single stock-based advisory to portfolio based advisory. Second, the focus is set on "compliance" by generating target portfolios that meet the risk profiles of clients. Consequently, this limits the freedom for the investment advisor of how to advise clients which is explained in the following.

Less freedom for investment advisors

The limitations of the relationship manager or investment advisors are:

• The initial investment proposal is effectively produced by a robot, the advisor has no or only limited influence on the proposed portfolio.
• There is a rigid process that needs to be adhered to in order to be compliant.
• The asset shelf is more restricted with the risk-based portfolio approach than it was with the sell-side single stock advice.
• Finally, the target portfolio must meet the risk profile of the client.

As the portfolio construction is delegated to a robot or to a portfolio construction engine, the client and the advisor are left with a "black box" to explain how the target portfolio has been constructed. To them, neither the optimization model nor the decisions taken by the machine nor the results produced by the engine are transparent or easily understandable.

Limited traceability of calculated investment proposals

The client and the advisor remain in a "recipient" role; they are not constructing the portfolio. Therefore, it is difficult to understand the result of the portfolio construction and the effects of a manual change in the target portfolio followed by another automated iteration of portfolio construction. Depending on the implementation of the automated portfolio construction, one change in the target portfolio can change the entire investment proposal. A direct connection between produced result to clients’ preferences and the selected instruments is often difficult to make.

In other words, the parameters, construction constraints and data that are driving the construction of the portfolio are not visible. The SAA-based optimization with large asset shelves might cause big changes in the portfolio, even for small amendments to it. The reasons for these changes remain unclear; neither the investment advisor nor the client can trace the result. This makes it nearly impossible to explain to clients how and why the implanted algorithms have generated the target portfolio. Overall, it is fair to say that it is very hard to explain the risk-based portfolios and investment proposals to clients.

The low-touch and “emotion-free” technical approach leads to lower client engagement

Besides the challenges directly connected with the "out-of-the-box" approach of risk-based portfolio advice, there a couple of challenges related to the communication between the advisor and the client.

Overall, the risk-based portfolio approach is a very methodological and technical approach which, on the one hand,  has clear advantages. On the other hand, it creates difficulties in the communication between the advisor and the client, i.e. the robot-based approach is regarded as low-touch technology. The main factors of the approach are risk-oriented measures like tracking error to show the efficiency of a portfolio and risk measures to explain whether a portfolio is within the risk bandwidth or not.

Besides the fact that these measures are hard to explain, an investment proposal generated in a risk-based portfolio setting is normally "emotion-free." For the client, it is hard to see the direct relation between his or her interests and the investment proposal. It is natural for people to distrust what they do not fully understand, even more so for financial decision-making. If no justification and no clear visibility of what is driving decisions is available, establishing a relationship of trust with clients will become very difficult.