Artificial intelligence (AI) is everywhere right now. Almost every vendor claims its product is "AI-powered," promising revolutionary innovations and exponential efficiency gains. But in the financial services sector, bold claims can quickly become liabilities. When it comes to people’s money, there’s no room for mistakes - and little appetite for hype.
One major reason is that financial services is the most heavily regulated industry, and it is taken to the next level in the most tightly regulated region: Europe. Banks can’t adopt a "move fast and break things" mentality when even small errors can have serious consequences. And that’s precisely why their approach to AI must be thoughtful, responsible and, above all, human-centric.
A recent Dentons report shows that paradoxically, in a landscape where 74 percent of business leaders believe AI is an important mechanism to protect their organization's revenue, 63 percent currently don’t have a formalized AI roadmap. For the financial services sector, the primary concern of implementing AI is the lack of human oversight. That’s not surprising. Banks are acutely aware of the reputational, regulatory and financial risks that can come from opaque systems making unsupervised decisions.
But this doesn’t mean AI is completely off the table. Instead, banks must take an incremental approach toward its adoption, building in fail-safes, human-in-the-loop safeguards and full transparency from the start.
That’s where conversational AI becomes a smart and safe entry point.
The case for conversational AI in banking
Conversational AI, when done in low-risk, high-value use cases, can provide measurable wins for digitally focused banks. Conversational interfaces resonate because they mirror the way people naturally communicate, whether through Messenger, WhatsApp, RCS, web chat or voice assistants.
At its best, conversational banking empowers real-time, two-way communication between customers and their financial institutions that complement and funnel clients into using safe platforms like the banking app. It reduces friction in service interactions, long call center wait times, and delivers 24/7 availability through the channels customers prefer.
A real-world example is how the Belgian bank Belfius created a conversational AI called myBo to streamline its insurance claims process. Customers now enjoy a fast, personalized and always-available chat experience. The results speak for themselves: over 2,000 claims processed each month, 600 working hours saved for customer care teams, and an 87.5 percent increase in conversion rates compared to traditional online forms. The chatbot now answers 5,000 questions monthly.
This type of use case is not happening in isolation. A recent Sinch report on customer communications reveals that AI chatbot adoption is accelerating, with 50 percent of financial services firms already using them to deliver automated responses, signaling a broader shift toward AI-driven customer engagement.
Start internally, then scale
Because conversational AI can be tailored to specific use cases and source inputs, it is controllable. Hence, many banks are wisely starting with internal use cases, such as automating employee help desks or streamlining HR requests, before extending to customer-facing interactions. This allows institutions to experiment, learn and build confidence in the technology before scaling it.
This kind of measured approach acknowledges an important truth: Transformational change in financial services doesn’t happen overnight. It’s to lay strong, responsible foundations for long-term innovation.
That means designing systems that are auditable, explainable and always have a path to human oversight. It means investing in omnichannel strategies that create seamless transitions between digital and human support. And it means recognizing that AI should augment, not replace, human interactions, especially in complex or emotionally charged financial moments.
Delivering real value, not just shiny tech
It’s easy to get caught up in the novelty of AI. But ultimately, customers don’t care whether their support experience uses generative models or large language transformers. They care that their issue gets resolved quickly, securely and with empathy. They want real solutions to everyday problems.
That’s why conversational banking has emerged as such a compelling use case. It’s not the loudest or flashiest form of AI, but it’s one of the most impactful. It offers immediacy and context, yet retains the human touch where it matters most. And because it’s grounded in real behavior and regulatory compliance, it’s a use case that builds confidence across both customer and compliance teams.
James Doherty is head of business development EMEA - Financial Services at Sinch.