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:
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Automate the back-office for further efficiency gains
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.
Manage rising risks and compliance more effectively
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.
Hyper-personalise customer experience to deliver greater value
Agentic AI-powered chatbots and virtual assistants can understand customer context, retrieve the right information, and perform complex tasks such as resolving disputes. Analysing customer information, such as risk appetite and financial goals, they can recommend highly contextualized financial products and services. AI agents outperform routine personalisation tools by acting as personal financial concierges, autonomously performing tasks such as sweeping funds to better yielding accounts and rebalancing portfolios.
The following example illustrates how European banks can leverage an agentic AI ecosystem to offer a highly efficient, frictionless and personalised mortgage application experience: A customer shopping for a mortgage can ask a market evaluator agent to compare offerings from different banks and shortlist those best meeting their requirements. Separately, a financial health analyser agent reviews the applicant’s credit history, financial position, spending habits etc. to calculate a realistic monthly instalment.
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By GlobalDataA reviewer agent refines the original shortlist for the customer to choose from; finally, another agent submits the application directly to the concerned bank.
Get innovative with the emerging generation of consumers
The gaming industry presents a compelling frontier for banks to engage younger, digitally native audiences with gen AI. With so many gamers interacting in immersive virtual environments, banks can leverage gen AI to create hyper-personalised financial experiences that align with gaming lifestyles and personas. For example, AI-driven insights can enable banks to offer micro-investment products based on in-game spending behaviour, offer dynamic credit options for digital purchases, and design savings plans that reward financial discipline with virtual incentives. By integrating with gaming platforms and analysing behavioural data in real time, banks can deliver contextual financial nudges—such as suggesting a budgeting tool or offering crypto-linked rewards for in-game achievements. The integration of gaming and finance, powered by gen AI, not only enhances customer engagement but also positions banks as lifestyle partners in the digital economy.
Moving ahead
While agentic AI is a clear step up from traditional AI, its implementation is also more complex. European financial institutions should prepare for more than just technical integration challenges, from heightened data privacy and security risks to opaque “black-box” agentic AI systems to ethical concerns and talent shortages.
Banks in Europe, most of whom are still in the early stages of adoption, should proceed thoughtfully on the agentic AI journey. At the highest level, they may need to rethink operating models for agile development and cross-functional collaboration, and create an organisational culture that values rapid experimentation, continuous learning and customer-centricity. Next, they should create a comprehensive roadmap, covering strategic objectives, technical readiness, use-case prioritisation, model explainability and transparency, workforce upskilling, and change management. Banks should take these decisions within a Responsible AI framework to unlock value from agentic AI in a secure, compliant and ethical manner.
Jay Nair, EVP, Industry Head, Financial Service and Public Sector, Infosys
