Advisor | April 2025
Artificial Intelligence will revolutionize the way banking and financial consulting are done, there are countless rankings of the professions that will be more or less affected, but all believe that the work of the financial advisor will survive AI.
The impact of AI will be different depending on the type of professional – bank manager, financial advisor or private banker – and the type of client, segmented by size of assets (mass market, affluent or private), by generational cohort (age) and by other socio-demographic variables (gender, marital status, residence, profession, etc.).
From an analysis carried out by FINER on the main experts and users of AI in the banking sector and in the networks of financial advisors, it emerges first of all that we must distinguish predictive AI from generative AI: the former uses data to predict or deduce a highly probable event that could occur in the future, the latter uses data to create new content.
In the world of banking, predictive AI finds and will increasingly find application in the field of evaluating the greater or lesser propensity to purchase products/services as well as in the greater or lesser aptitude to use different channels.
predictive AI will therefore be able to direct the offer and the optimal channel to propose an investment product, a policy or a mortgage in a targeted way on the individual potential customer, exponentially increasing the probability of success of the commercial proposition.
This could be done even before AI arrived, the difference lies in the fact that before, data was used in a static way, excluding statistically less relevant phenomena (the so-called data tails), while today, thanks to AI, every digital trace is analyzed in a dynamic and – indeed – predictive way.
In other words, with predictive AI it is much more likely to identify a possible trend from a weak and hidden signal than what happened in the past.
Predictive AI will have a significant impact on the implementation of traditional banking activities (transactions, e-money), in credit activities (risk analysis on mortgages, loans and financing): it is and will be increasingly widely used by bank managers dedicated to segments of medium-capitalized customers (mass market and low affluent), with more basic needs, on average younger and more oriented towards the use of digital channels.
Predictive AI can be likened to a sort of virtual assistant to which routine and medium-low added value operations can be delegated: with it, the professional – whether bank manager or financial advisor – will therefore be able to manage many more clients than in the past with the same amount of time and energy.
On the other hand, generative AI, starting from data to generate new content, will be able to create new narratives to be used with more advanced, demanding and well-capitalized clients (upper affluent and private), each one different from the other, as many as the types of clients.
Generative AI will be a real co-pilot who will sit in the cockpit alongside the commander impersonated by the financial advisor and the private banker, whose role is difficult to replace by the autopilot, especially during take-off and landing.
The optimal adoption of AI in banks and networks depends a lot on the vision of top management, just look at who recruits the best talents to discover who is short-sighted and who is far-sighted.
Nicola Ronchetti