The Charge of RoboAdvisories

The benefits of Artificial Intelligence (AI) affect all sectors of the financial industry, from insurance to payments, from asset management to savings services (Verma, 2023). For example, thanks to AI it is possible to develop ad hoc recommendations to help consumers better manage their capital and achieve their savings goals (Aboelmaged et al., 2013). Even opening a mortgage can become a much more efficient procedure thanks to AI, eliminating the need to go to a physical branch, as well as improving risk assessment for lenders. Finally, automation represents the new frontier in the field of investments, thanks to the possibility of obtaining more information about customers and offering them ad hoc services, by considering their preferences in terms of asset allocation and the level of risk aversion (Goncharenko, 2019). In addition, the use of robo-advisories offers banks the possibility of speeding up contacts with customers, for example by sending alerts in response to changes in the markets with almost instantaneous speed (Jaksic et al., 2019). Furthermore, the ability to develop accurate analyses in terms of risk profile and market forecasts, together with more efficient portfolio management, allows for improved rates of return. Finally, AI makes it possible to reduce manual intervention in banking processes, so as to decrease the costs of advisory services and reach a wider audience, allowing financial companies to lower commissions on individual investments.
All these elements offer a crucial competitive advantage, namely the possibility of attracting younger consumers, the so-called Generation Z, who attach great importance to technological innovation (Kaur et al., 2020). The development of personalized banking services, which manags to achieve a deep understanding of consumers' needs and preferences, would offer a win-win scenario for both banks and consumers themselves, who would end up being offered perfectly customized products and services (Gigante, 2022). To conquer this target market, it is essential for the bank to invest in new technologies to improve its digital services and pay attention to aspects such as human contact and reputation. The former represents a fundamental component to attract older consumers, for whom it is a priority to be able to easily contact their financial advisors. In this regard, some banks have introduced a "voice analyzer", which allows the automatic transition from robo-advisor to human assistant.

As far as the reputational aspect is concerned, another advantage of AI is transparency, as robo-advisors employ algorithms based on financial theory (for example, they build portfolios based on Markowitz's optimization theory). In this regard, the study by D'Acunto et al. (2019) analyzed the use of the Markowitz model by a robo-advisor in the selection of investment portfolios. What has emerged is that the adoption of robo-advisors has differential effects on investors based on their levels of experience: less specialized investors have greatly improved their performance in terms of portfolio returns, thanks to greater diversification. On the other hand, institutional (and therefore already diversified) investors underperformed. This study therefore suggests that every bank must know how to use automated systems in light of the level of the financial knowledge of individual customers.

In conclusion, the growth prospects for this sector are really interesting: McKinsey has estimated that the use of AI in the banking sector can globally generate up to $1 trillion in value added every year. Similarly, Bloomberg has projected annual growth rates of 39.9% for the robo-advisory market until 2028. The use of automated systems therefore represents a necessary investment for banking institutions, and an absolute priority in a country, such as Italy, where the push for innovation has so far been sacrificed. In fact, compared to the European average, investments in deep tech by venture capital funds are very low in Italy, and the country in general ranks behind countries such as Ireland, Denmark and Spain in terms of research contributions. It is therefore a priority to build an efficient cooperation system between universities, private industry and the state, in such a way as to direct more capital towards innovation and implement the transformation of our ecosystem to facilitate the creation of spin offs and communities of high tech entrepreneurs, as well as the funding of start-ups in their initial stage of development (seed investors).