ALFI responds to the EC’s targeted consultation on AI in the financial sector

In the response to the consultation, ALFI conveyed the views and most relevant feedback from the investment funds industry perspective, reflecting the consensus view of the Luxembourg Fund Industry Association membership, with regards to the use of AI in the fund industry, the different usecases, the opportunities, impact and risks thereof.

In the response to this consultation, ALFI highlights the following:

ALFI, while responding to this consultation from the perspective of the investment fund industry, confirms that AI solutions, and large language model (LLM) tools in particular, are increasingly used among asset managers.

Investment fund managers (IFM) appreciate AI supported processes, that allow highly qualified people to focus on creative and value-added work, while the repetitive tasks and data accumulation be performed using AI solutions.

The industry presents a large variety of usecases, including investment management support, to prospectus and large deals analysis, legal and compliance support. Automation of routine tasks and enhanced decision making are considered the highest benefits of such AI tools.

Yet, the use of AI-supported applications includes some risks. Such risks can be analysed across three categories:

1. Systemic risks, such as financial stability risks, market risks, liquidity risks and market integrity risks. This first class of risks, impacting the markets globally and to a large scale, have been considered of utmost relevance
2. Risks related to investor protection
3. Risks borne at individual IFM level, such as operational risk and reputational risk

Overall, AI tools are applied as add-ins to existing processes, providing a low-hanging fruit type of solution to a specific requirement within an existing process, without altering the overall operations to the greater extent. To this respect, the risks remain limited.

To further mitigate the risks, ALFI would encourage the industry to foster transparency, explainability and auditability of the data and models, as well as enhanced change management and staff training within IFM.

Read the ALFI response.