After the fence of the Summit on the AI, she was opposed 2 visions which seem irreconcilable. However, Europe continues to apply its agenda with the 1st implementation of the AI Act
Only a few days after the fence of the Paris summit on artificial intelligence, the AI was mainly opposed to two visions which seem irreconcilable: that of the United States which preaches for an “open” AI to “not kill an booming industry and that of Europe calling for greater regulation. The tension even rose from a large notch when a consortium led by Elon Musk proposed $ 97.4 billion, to buy Openai accusing Sam Altman for wanting to develop a “reasoned” AI.
However, Europe continues to apply its agenda with the first major implementation of the European Union law (EU) on artificial intelligence (AI ACT), focusing on prohibited AI systems. Its ambition remains intact: establishing the international standard concerning the functioning of AI in the field of financial services – and that is exactly what the sector needs.
The reality of AI in finance: a targeted approach to generalist AI
The AI had Act is not simply a new regulatory tool intended to increase the workload of compliance of companies. This is a framework that promotes the design of more efficient AI systems, in particular for financial services. By classifying certain financial applications, such as Credit Scoring or insurance pricing, among high -risk AI systems, law recognizes that AI systems intended for financial services must be both relevant, exact and transparent.
This is also verified on the market. While some allow themselves to be seduced by general AI, the leaders of the finance sector adopt “well -sized” AI, focusing their efforts on “targeted automation” using AI agents or thanks to the deployment of smaller models – all framed by rigorous governance.
The importance of “well -sized” AIs in today’s world
The provisions of the AI Act in matters of explanability, human supervision and risk management should not be perceived as obstacles. On the contrary, these are essential criteria which make it possible to determine whether an AI is able to manage financial operations.
In the field of financial services, many essential AI applications are classified among high -risk systems due to their potential impact on business decisions and results for their customers. This is why it is particularly crucial that these systems are the subject of strict human supervision.
Experience shows that to benefit from an effective AI in the financial sector, it is not a question of creating all-powerful systems. Intelligent agents must be conceived that fulfill a specific role and perform clearly defined tasks. In addition, each of these agents must operate within an adapted framework and have limited permissions. This implies setting up a rise in clear information for boundaries, while maintaining complete audit avenues for AI -assured decisions and guaranteeing the capacity of human experts to revise and call into question the recommendations of the system when it is necessary.
When it comes to analyzing trends in the company’s expenditure, monitoring compliance with compliance with spending policies or detecting fraud, it is essential to be able to rest on clearly explainable and effective AI systems as soon as they are deployed – which do not require intensive training and comply with strict data protection standards. Unexplained decisions and unpredictable results simply do not have their place in financial operations.
An opportunity for Europe to take a step ahead
While the United States and China compete in order to build the largest model of AI, Europe is positioned among the leaders when it comes to designing the most reliable systems. The EU AI requirements on AI in terms of biases, regular risk assessment and human supervision are not an obstacle for innovation. On the contrary, they help to forge the definition of an efficient AI in the field of financial services.
This regulatory framework provides European companies with a considerable advantage. As international markets require increasingly transparent and responsible AI systems, the European approach is about to become the de facto standard for financial services worldwide.
The success of companies will be determined by their ability to deploy intelligent agents that fulfill well -defined roles, with clear limits and strict governance standards. The potential of such an approach does not reside within its limits, but in its precision.
The future of financial services is clear: success will not result from ambitious statements on AI, but targeted and concrete deployments that make the safety and reliability of priorities.
