Robo-advisers are a relatively new approach to wealth management that attempts to disintermediate the classical distribution model of personalized advice. Robo-advisers help clients identify goals and risk tolerances through questionnaires. They then propose diversified portfolios through passive investments—for example, exchange-traded funds. The authors point out the benefits and drawbacks of this new advisory service.
How Is This Research Useful to Practitioners?
Automated asset management advice, through so-called robo-advisers, has been growing in popularity as web-based platforms challenge traditional investment advisory models. Practitioners need to ask whether this growing trend is the way of the future and, more importantly, whether this approach is good for those seeking investment advice.
Robo-advisers disintermediate the classical distribution model. The authors state that the traditional model is expensive, difficult to scale, and highly dependent on the individual adviser’s skill. The solution seems to be the use of a nonpersonalized web-based model that gives investors access to diversified beta. These models try to understand the needs and risk tolerances of specific investors through the use of questionnaires. Once the questionnaire is completed, the investor is then given a proposed investment that consists of a portfolio of exchange-traded funds—that is, passive investments.
The authors’ criticism of the robo-adviser questionnaires is primarily that the advice provided is canned advice. Personalized information about the individual investor is not incorporated. Yet, investors—even if they share the same age, net income, and savings rate—differ materially in their ability to take risks.
In the authors’ opinion, in short, neither model meets the economic criteria of clients, and neither represents advice that is in the best interests of clients.
How Did the Authors Conduct This Research?
The authors research the questionnaire process to determine whether the robo-adviser’s advice is worthwhile and, ultimately, meets the goals and needs of the clients. They build a generic questionnaire that represents the general questionnaire used by most robo-advisers and find that robo-advisers use one of two methods to determine the goals and risk tolerances of clients.
The first type of model is ad hoc and driven more by lawyers trying to anticipate court rulings (that is, based on case law) than by modeling client economics. Such models’ weights are based on the risks of the client and the ultimate liability of the investment firm. The weightings have been invented rather than derived from an academically cross-validated decision-making model. Those creating the weights have the ultimate say in the final portfolio, and this portfolio might be created with a tendency more to protect the investment firm from legal issues than to meet the client’s needs and achieve her goals.
The second method of questioning is in line with decision theory models on portfolio choice. These models include household assets and liabilities. They use the investor’s age, net income, and savings to calculate the present value of a lifetime of savings—that is, human capital. The model then assumes that the individual will need 80% of his preretirement income for consumption upon retirement. The present value of this needed income is considered a liability, and the portfolio is designed to meet this liability, called the “pension gap.” Although this type of modeling attempts to create a portfolio that meets the investor’s needs and goals, the information used, other than the client’s age and after-tax income, is generic.
Abstractor’s Viewpoint
Robo-advisers present a new method of helping individuals build diversified portfolios without paying large advisory fees. In that respect, they are a welcome trend in the investment management profession, especially as a solution for those investors who are starting out, do not have a large amount of assets, and cannot withstand the headwinds of high fees. The questionnaires used by most robo-advisers have proved inadequate, however, at providing a solution for the client’s true risk tolerance or even ability to take on risk. At worst, questionnaires are simply a method to reduce the legal liability of the financial firm providing the mechanical advice. So, robo-advisers offer a good starting point to help guide investors, but the approach still needs much work for robo-advisers to truly understand a client’s goals and risk tolerance.