Financial advisory, robo-advisors and AI: is the consultant’s “disintermediation” close at hand?

Studies in behavioral finance show that investors, left to their own devices, are penalized by emotional decisions and by the lower performance of their investable assets.

In recent years roboadvisors and AI have gained ground in financial advisory activities, offering automated asset allocation services based on algorithms and artificial intelligence. This is thanks to their low costs and ease of access. The limit, however, is that an algorithm cannot understand personal goals, family dynamics or complex tax needs. Despite this limitation, online trading platforms and direct access to markets push many savers to manage their savings on their own, with the promise of freedom, direct control and lower costs.

When it comes to the use of algorithms, among the most significant innovations are digital platforms that offer portfolio solutions thanks to optimization algorithms and, increasingly, artificial intelligence models (AI). These tools have been successful for their ability to combine accessibility, efficiency and lower costs, allowing even retail investors to access services once reserved for a more sophisticated clientele (Sironi, 2016). However, the question remains whether the human advisor can truly be replaced by an automated system, especially in the qualitative and relational dimensions that characterize the advisory process.

In detail, roboadvisors are based on algorithms capable of determining optimal portfolio combinations according to the risk profile and the goals declared by the investor. The underlying logic is that of algorithmic rationality, which eliminates cognitive distortions and the emotions that often negatively influence human decisions (Lo, 2019). However, quantitative efficiency does not necessarily mean complete advisory service. Automated platforms are not able to incorporate qualitative elements into the decision-making process, such as family dynamics, tax planning or intergenerational wealth management, which require interdisciplinary skills and a deep understanding of individual needs (Cocca, 2016). From this perspective, the value of the financial advisor lies not only in building the portfolio, but in the ability to interpret the client’s personal and psychological context, guiding them along a path consistent with their life goals and not just with market variables.

The spread of online trading platforms and growing digital literacy have encouraged the autonomous management of savings, a phenomenon that fuels the perception of a possible “disintermediation” of the advisor. However, numerous studies in behavioral finance show that individual investors, left without professional guidance, tend to systematically underperform the markets. Barber and Odean (2000), in a now classic study, showed that excessive portfolio turnover, driven by overconfidence and impulsive behavior, significantly reduces average returns compared with benchmark indices. Similarly, Kahneman and Tversky (1979) highlight how loss aversion leads investors to sell winning securities too early and hold on to losing ones for too long.

These findings suggest that disintermediation, far from being an advantage for most savers, can turn into a high implicit cost, represented by the loss of returns stemming from irrational choices and inefficient planning. In light of this evidence, the hypothesis of a total replacement of the advisor with AI appears technologically premature and conceptually inadequate. More realistic is a scenario of complementarity between human and machine, in which technology becomes a support tool for advisory activity. AI can, in fact, help improve the quality of service through predictive analysis, risk optimization and the automation of administrative processes, freeing up time and resources for higher-value activities: client relationships, financial education and strategic wealth planning (Jung et al., 2018).

In this perspective, the financial advisor evolves into a hybrid role, in which relational skills and interpretive ability merge with the conscious use of digital technologies. Therefore, the gradual digitalization of financial services does not necessarily imply the disintermediation of the advisor, but profoundly changes its nature and operating methods. AI and roboadvisors represent an opportunity for the evolution of the advisory model, not a threat to its survival. For a small minority of investors with solid technical expertise and a high degree of behavioral discipline, independent management can be effective. However, for most savers, the role of the financial and wealth advisor remains essential to mitigate cognitive biases, build long-term strategies and integrate tax, legal and wealth dimensions that an algorithm is unable to grasp.

References
Barber, B. M., & Odean, T. (2000). Trading is hazardous to your wealth: The common stock investment performance of individual investors. Journal of Finance, 55(2), 773–806.
Cocca, T. D. (2016). Potential and limitations of virtual advice in wealth management. Journal of Financial Transformation, 43, 65–72.
Jung, D., Dorner, V., Glaser, F., & Morana, S. (2018). Robo-advisory: Digitalization and automation of financial advice. Business & Information Systems Engineering, 60(1), 81–86.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–292.
Lo, A. W. (2019). Adaptive Markets: Financial Evolution at the Speed of Thought. Princeton University Press.
Sironi, P. (2016). FinTech Innovation: From Robo-Advisors to Goal Based Investing and Gamification. Wiley Finance Series.