by Thomas Bosshard
The trend towards digital advice is sweeping across all sectors. In the investment management business, Robo-advisors, online platforms that use algorithms to recommend investment portfolios, are already widely in use, gaining acceptance and growing rapidly. According to a study by BI Intelligence, close to 50% of high net-worth individuals would consider using a Robo-advisor to manage their wealth.
Some of the main advantages of these platforms are that they are easy to use, fast, accurate and consistent. Companies that offer them are able to lower labor and back-office costs and create new distribution channels, even reach new markets, e.g. millennials that are used to this type of “self-service”. Furthermore, they take “human fallibility” out of the equation and thus promise more objective portfolio selection and management.
Robo-advisors automate many established financial advisory processes. Therefore, observers of the world of investment are worried that major disruption may be lying ahead that will likely revolutionize investing and kill jobs. Obvious parallels are drawn to the technology-driven transformation of the music business or “Uberization”. Therefore, it is worthwhile to look more closely at which processes can be automatized and which are better left to the human brain.
The functions Robo-advisors offer are limited. They involve asking routine questions on an investor’s current financial status, risk tolerance, time horizon and financial goals. Based on this information they then select a personalized portfolio. Human advisors also need answers to these questions, for example in order to assess a client’s tolerance for risk. They often even give clients the same risk assessment questionnaires that Robo-advisors use.
However, as most financial advisors know, many clients struggle to fill in the questionnaire. Not all of them understand their own risk tolerance, especially if they have limited experience with investing. In a face-to-face conversation a human advisor can sense this and ask related questions to gauge the client’s expectations, e.g. to which extent a client would tolerate losses in the pursuit of long-term financial goals. Furthermore, there are various broader risks to consider before a suitable portfolio investment should be recommended such as: Does the client fear entrance into a higher tax bracket? Is there a liquidity risk, if a client wants to draw cash from his or her investment in the future?
Client advisors can set themselves apart from Robo-advisors by giving clients the opportunity to express themselves. The traditional advisory process allows them to gain a deeper understanding of the client’s fears, personal goals, long-term and short-term, and values. They can show clients when fear can lead to irrational behavior by educating them on what can go wrong and how it is best to behave. Therefore, concerns about the rise of Robo-advisors may even result in a helpful discussion of what a financial advisor’s job really should be.
Some experts like to use the «doctor analogy» to justify the value financial advisors create for clients. They reportedly even suggest asking clients whether they would ever go to a “Robo-doctor” if they were ill, and hardly any client would say yes.
However, unlike financial advisors, doctors have been subjected to years of rigorous schooling and training, which is clearly justified as patients put their lives into their physician’s hands. Also, there are many other advisory professions, for example in the fields of law or accounting, where employers require advanced degrees as attorneys or CPAs before they would let them interact with clients.
Patients cannot self-diagnose themselves and pick their own treatment. They lack the knowledge and the experience needed to make sound medical decisions. In a similar vein, retail clients and unexperienced investors with little knowledge of finance require professional advice if they do not want to harm their financial health due to bad decisions.
The main difference, however, between the client relationship in both professions boils down to trust: Ever since the outbreak of the financial market crisis and the other very public scandals such as Libor, more and more of financial clients have lost trust in their advisor’s advice or suspect ulterior motives such as them pushing their own products. On the other hand, aggressive marketing from the pharmaceutical industry is also known to have an influence on a physician’s medical decisions to the extent that patients also fear that they are pushing drugs or unnecessary surgery, driving some of the less trusting of them to require a second opinion. But financial advisors were never required to take a Hippocratic oath that binds them to act in their clients’ best interests.
Regarding risk assessment and behavior, there are some noteworthy parallels between the professions. Patients don’t always take their doctor’s advice, e.g. to lose weight, because the short-term pains weigh more than the long-term health benefits of weight loss. Similarly, financial advisors cannot prevent nervous investors acting on impulse at the first signs of a down market, thus hurting their returns in the long-run, a behavioral phenomenon known as loss aversion.
Furthermore, there are also many routine medical procedures that can be automatized. A particular field in which artificial intelligence (AI) or the infamous “robo-doctors” are currently creating a buzz among players in the world of healthcare is the assessment of cardio-vascular risk. A recent paper in the medical journal PLOS One shows that algorithms have already beat doctors in predicting heart attacks by 7.6 percent, compared to the standard method, which involves doctors carefully considering a patient’s demographics, blood pressure, cholesterol levels, and other potential risk factors. Algorithms drew data from the medical records of over 300,000 patients and applied advanced analytic methods which would be impossible for the human brain to process.
However, as Dr. Stephen Weng, one of the researchers that developed the algorithm, explains to NBC News MACH: “An AI algorithm won’t be able to tell you that the patient was nervous because they had a big job interview in the afternoon and was caught in a traffic jam on the way to the appointment and thus their blood pressure was high on the day.” As a result, Robo-doctors will perhaps in future not be able to replace doctors but assist them in doing their jobs. So just like financial advisors, a doctor’s job is evolving due to new technology, and discussions on what the added value of human doctors could be in the age of AI would seem very helpful.
Essentially, the main advantages of algorithm-based “medical care” lie in the amount of data available for interpretation and the sensitivity of the analysis. Here machines (or big data and advanced analytics) have clear advantage over the human brain. Therefore, empathy, integrity and trust seem to be the path forward for any advisory profession in an age of robots and artificial intelligence.