ROBO ADVICE

Robo advisors are programmed algorithms that provide financial advice and portfolio management to investors. Launched to the public in 2008, this technology is growingly popular, with the perspective of surpassing 34 million users in 20281 . Automatized investment advisory is more cost-effective than the manual (human) one, thus allowing those offering this service to lower their fees and reach un- and underserved investors. These entrants can encroach in incumbents’ market participation, but most probably what will be observed is a growth in the share of investors with access to advisory and portfolio management. Additionally, there is empirical evidence to support the theorized positive net effect of robo advice on competition and consumer welfare: it brings benefits to small and medium sized banks without loss of stability2 and it improves the performance of both portfolios that are either under-diversified3 or belong to individuals with low education or income4. The authority should pay attention to how platforms assess the risk aversion of investors, so as to manage their investments in an adequate and suitable way to their conditions and preferences.

Authorities should pay attention to how platforms assess the risk aversion of investors, so as to manage their investments in an adequate and suitable way to their conditions and preferences. Additionally, the emerging nature of robo advice means it has not yet been fully tested under financial market crisis. An understanding of how consumers are protected from acute asset price variation or company failure remains to be seen. In this sense, authorities must take steps to assure proper financial consumer protection, algorithm auditing, internal controls and overall transparency, so that consumers are sufficiently informed and safeguarded from robo advisory risks.

Notes:

1. Statista (2025), Robo-Advisors - Worldwide | Statista Market Forecast, https://www.statista.com/outlook/fmo/wealth-management/digital-investment/robo-advisors/worldwide?currency=USD (accessed on 19 August 2025).

2. Deng, L. et al. (2021), “Impact of Fintech on Bank Risk-Taking: Evidence from China”, Risks, Vol. 9/5, p. 99, https://doi.org/10.3390/RISKS9050099.

3. D’Acunto, F., N. Prabhala and A. Rossi (2019), “The Promises and Pitfalls of Robo-Advising”, The Review of Financial Studies, Vol. 32/5, pp. 1983-2020, https://doi.org/10.1093/RFS/HHZ014.

4. D’Hondt, C. et al. (2020), “Artificial Intelligence Alter Egos: Who might benefit from robo-investing?”, Journal of Empirical Finance, Vol. 59, pp. 278-299, https://doi.org/10.1016/J.JEMPFIN.2020.10.002.