Globally, IDC expects more than €101.3 billion Euros to be spent on AI use cases across financial services in 2026. With a three-year CAGR of 35.5%, that figure is projected to climb to €251.9 billion by 2029.¹
In my role as EMEA labs manager at Arrow, I'm seeing genuine curiosity around a wide range of AI use cases. Some are clearly tied to banking and insurance, others apply across any industry — but they all keep showing up near the top of the priority list in this sector. Below is a closer look at use cases, and why it might be worth a conversation with your customers.
So let's go through the four that are getting most of the attention — and why your financial services customers might want to put them into practice.
Augmented claims processing
Worldwide AI spending on augmented claims processing is growing at a 39% CAGR between 2026 and 2029. Insurers and banks like this one because it genuinely helps adjusters and investigators get through claims faster, using smart data capture and analysis rather than guesswork. This isn't a chatbot bolted onto a website — done properly, it slots into the existing claims workflow, which is exactly why it takes a bit of expertise to get right. That's also where the real value sits.
Smart legal
AI spend on smart legal use cases is growing at a 37.4% CAGR over three years. Anyone working with legal data knows the headache: years of contracts and documentation, strict privacy rules (GDPR being the obvious one for us in Europe), and the constant need to strip out personally identifiable information. AI takes a lot of the grind out of this — drafting, reviewing and comparing documents — so in-house legal teams can spend their time on work that actually requires a lawyer. And because these tools can run on-premises, sensitive data stays where it should.
The upside goes beyond saving time. With AI, you get repeatable, explainable processes — things like standardised templates and clean extraction of insights from legal text. That means lower costs on expensive legal resources, fewer mistakes, and faster turnaround. With several vendor tools now available and maturing quickly, AI-driven legal assistants are becoming a practical answer for teams drowning in documents.
Augmented fraud analysis and investigation
This one has a 36.1% CAGR in worldwide AI spend from 2026 to 2029, and it works on similar principles to claims processing. It's a strong fit for banks and insurers, and our technical team runs demos for several of the vendors on our line card. A good example: an insurer we're working with is putting this in as their very first AI initiative — a sensible place to start, because the business case more or less writes itself.
AI-enabled customer service and self-service
Spending on AI for customer service and self-service is growing at a 32.7% CAGR worldwide in financial services. Our team runs plenty of vendor demos here — tools designed to make customer interactions smoother, whether that's a human-in-the-loop setup or full self-service.
Better customer service obviously isn't unique to banking, but we have some genuinely interesting use cases tailored to the sector. One example: a loan-advice agent that customers can ask straightforward questions to and get a useful answer back — something like "I'd like to borrow €50,000 over five years, what kind of monthly repayment should I be looking at?" The agent walks them through indicative repayments, interest costs and what affects the rate. It's the kind of thing that takes pressure off the contact centre while giving customers a faster, more transparent experience.
Want to take a closer look?
Our technical team at Arrow can help with any of the use cases above — or work with you to identify ones we haven't covered yet. Contact us to request a meeting with our technical team or learn more about our AI capabilities.
¹ Source: IDC Worldwide AI and Generative AI Spending Guide — Forecast 2026 | Mar (V1 2026)
