With capabilities such as autonomous decision making, continuous learning, adaptive workflows, and multi-step problem solving, agentic AI is the next big thing in artificial intelligence. Europe’s enterprise agentic AI market is on a rapid growth trajectory, with revenues, totalling $634 million in 2024, crossing $5.5bn by 2030. Germany, the UK and France lead, accounting for roughly 70% of the market.
Agentic AI adoption among European banks is in the early stages, but progressing well, driven by relatively low-risk but impactful applications, such as back-office automation and fraud detection.
As traditional automation, which is static and rule-based, approaches its limits, agentic AI is opening up new possibilities by handling multi-step workflows, optimising complex, dynamic processes, and autonomously executing sophisticated tasks in real-time. For Europe’s financial services organisations, under pressure from fintech/ big tech rivals and a stringent regulatory environment, the agentic AI opportunity couldn’t have come at a better time. Here are some ways they can take advantage:
Banks can leverage AI agents across the back-office to perform complex, repetitive tasks, such as verifying documents, reconciling accounts, processing invoices, and posting journal entries autonomously to save cost and time, while reducing errors. The benefits are very visible in areas, such as credit operations and trade finance processing, with leading banks reporting 25 to 40 percent improvement in loan approval speed and 45 to 65 percent reduction in manual effort, respectively. When agentic AI-generated mortgages commence sometime next year, the bank’s customers will be able to go through credit checks and other formalities without speaking to a human being.
Monitoring financial transactions in real-time, AI agents not only identify suspicious patterns early, but also automatically trigger actions – for example, freezing the affected account – to arrest losses. They also monitor processes for compliance, keep track of changing regulations, send alerts about potential violations, and create reports without human intervention. Unlike traditional risk models, which mostly rely on historical information, agentic AI systems also consider real-time market trends and other external data to dynamically adjust risk assessment, resulting in better risk prediction and management. This is especially important for complying with Europe’s stringent regulatory mandates, such as GDPR and the EU AI Act: one source says that European banks trialling autonomous agents for MiFID II compliance were able to implement new requirements up to 25 percent faster than those using only human compliance analysts.
