Bluerating | November 2024
Having always been accustomed to operating out of office and without being able to count on a branch or a physical presence in the area, financial advisors have always been the first to adopt every new thing and innovation that could facilitate their work.
Today the news is represented by generative Artificial Intelligence and many are wondering how this will impact the work of financial consultancy professionals.
Artificial Intelligence will allow financial advisors to optimize their time and dedicate it mainly to activities with greater added value, i.e. client management.
If it is true that at least 50% of the time of professionals who work in banks is dedicated to bureaucratic and administrative activities, the same activities require just under 30% of the time of financial consultants, therefore a significant difference which partly explains the greater proactivity of consultants financial in customer management.
Having to invest half or even just a third of your time in activities that divert attention from the customer is increasingly less acceptable, especially for front office figures.
Artificial Intelligence, if well-known and applied, can produce beneficial effects in terms of efficiency and effectiveness in the management of back office activities.
Let’s think about the management activities of repetitive and recurring procedures, the monitoring of risk management activities and in general all the operations which, if appropriately classified and ordered, can be systematized and resolved with Artificial Intelligence.
However, the real added value of Artificial Intelligence could also be something else. Let’s imagine we could segment financial advisors based on their aptitudes, into attackers, defenders and midfielders.
Likewise, let’s imagine being able to segment a bank’s customers based on the level of delegation, knowledge and interest in the issues that concern the management of their savings and assets and to classify customers into four categories: delegating, controllers, protagonists and partner.
Each of these four types of customers wants to be able to interface with a financial advisor with a different approach.
The combinations between the types of customers and professionals can then also be cross-referenced with socio-demographic variables (gender, age, geographical area, marital status, profession), amount of assets to which the data held by the bank could be added, in terms of products subscribed and assets managed.
Furthermore, the same information could be enriched with variables relating to the greater or lesser satisfaction of customers with respect to the bank, its services and the manager himself.
This is a mass of data and information that not only needs to be processed but which, if appropriately used, can increase the chances of success of any initiative.
It would be a matter of finding the perfect client-consultant combination, fundamental not only for the success of commercial proposition activities but also for the reassignment of dormant clients to individual professionals or individual team members characterized by different aptitudes.
If all this has not been done to date it is also because there was a lack of a tool capable of transforming theory into practice, today this tool exists and it is called Artificial Intelligence.
Nicola Ronchetti