European banking adjusts its workforce due to artificial intelligence
A profound and constant change is sweeping through the financial sector in Europe. Artificial intelligence acts as the main driver of this evolution, which according to McKinsey & Company analyses, could lead to reducing nearly 200,000 jobs by the end of the decade. This process does not imply abrupt layoffs, but a gradual adaptation where repetitive tasks give way to algorithms. Banks need to optimize costs and be more efficient in a market with low interest profitability and high competition. 🤖
Automation redefines jobs
The most impacted areas are basic customer service, data processing, and managing internal operations. Automated systems can execute transactions, assess credit risks, and resolve routine queries faster and more accurately than a human. This allows freeing up employees to focus on functions that require creativity, critical judgment, or more complex personal interaction. However, this transition demands professional retraining for a considerable portion of the current workforce.
Key areas of transformation:- Customer service: Chatbots and virtual assistants handle frequent queries, referring complex cases to people.
- Back-office and operations: AI processes documents, reconciles accounts, and detects anomalies in transactions automatically.
- Analysis and risk: Algorithms examine large volumes of data to predict trends and assess solvency in real time.
The challenge is not to replace people, but to reorganize talent around technology. The banking that succeeds will be the one that knows how to combine both.
The future combines technology and human talent
The European financial sector is not disappearing, but reinventing itself. The strategy consists of implementing AI tools to gain competitiveness, while developing new skills in workers. Specialized positions are expected to emerge in managing artificial intelligence systems, protecting cybersecurity, and analyzing complex datasets. For banks and regulators, the challenge is to organize this change in a way that mitigates the social impact and leverages the full potential of innovation to improve financial services. ⚙️
Emerging new roles:- AI systems manager: Supervises, trains, and maintains machine learning algorithms in production.
- Financial cybersecurity analyst: Protects digital infrastructure against frauds and sophisticated cyberattacks.
- Specialized data scientist: Interprets complex data to create new products or improve the customer experience.
A transition with a human face
The final landscape is a hybrid environment. While systems learn to identify fraud patterns, employees must adapt to a reality where their "boss" may be software that updates, not one that drinks coffee. The key to a successful transition lies in continuous training and policies that facilitate internal mobility. The ultimate goal is to build a more agile, secure, and customer-focused bank, where technology enhances human capabilities rather than simply replacing them. 👥