In what ways is AI currently integrated into financial research activities?
AI is already a reality for us. In particular it enables us to automate and simplify data collection on the companies and sectors we cover. We have also created a chatbot to query our research archives, enabling us to cross-reference current analyses with our previous publications.
This is obviously just the beginning. Further developments are on the horizon, and we are focusing on a flexible platform in this regard, as evolution is occurring very rapidly.
What are the limits of AI in your field? Is there not a risk that it will eventually replace the financial analyst altogether?
We are convinced that the purpose of AI is to streamline certain processes, but not to replace the analyst and their historical knowledge of the sectors they follow. AI is an aid, but the analyst's personal touch remains essential. This is why I frequently speak of the "augmented analyst."
The analyst provides a dynamic vision that AI lacks and also serves as the guarantor of high-quality client interaction. Furthermore, I have observed that the human relationship remains important to clients, including the younger ones who grew up with digital tools. While they often use AI, they read less and prefer the oral insights of an analyst over the tedious consultation of written documents.
What are the current or future effects of these developments on the profession's workforce?
The productivity gains offered by AI will enable analysts to cover more stocks with the same level of rigor. From about twelve companies today, coverage could increase to around fifteen, representing an increase of approximately 25% to 30%.
In parallel, the automation of tasks will have an impact on the number of junior analysts in research departments. We will continue to recruit, particularly to ensure succession, but we will necessarily be more selective regarding young profiles.
For many years, the economic model of financial research has been a concern for the profession. Can AI be the solution to this problem?
Even if the presence of a research desk within an institution is a major asset in client relations, it is true that financial analysis is traditionally seen as a cost center. Moreover, the MiFID II directive has put the sector under pressure by forcing it to find new revenue streams, such as through sponsored research contracts for small caps.
AI is naturally a source of potential savings, but like all major shifts, it also opens up new revenue perspectives. We are considering the best way to monetize the work produced by our tools. For example, thanks to AI, we possess a large quantity of proprietary data that is easily searchable and customizable, which could serve as useful databases for many economic agents.
