Fintech Still Needs a Soul: Could AI Alone Handle Customer Support?

While generative AI is transforming customer service, human support remains critical, especially in the fintech industry, where nuanced, complex and emotional situations often require more than an algorithmic response.

When chatting online, half of the customers prefer communicating with real people rather than with AI chatbots, which are widespread nowadays. Meanwhile, according to other statistics, 34% of consumers find AI chatbots helpful in customer service.

Taking into account this minor contradiction in users’ views, it seems that hybrid support models are on the rise — AI handles routine tasks, while humans step in where the stakes are much higher. So, let’s break down where AI excels, where it falls short, and why the AI-human synergy could be fintech’s smartest move.

The Bright Side of AI in Fintech Support

At first glance, it may seem that fintech is rapidly embracing AI only because it is a current trend everywhere. But that is slightly far from reality. Companies are also doing it because it simply works. In today’s digital world, customers expect support to be fast, personalized and always available. AI is helping fintech companies deliver real-time, quick and efficient support as a full-fledged, practical tool.

Take the basics: password resets, balance checks, transaction tracking — all these routine inquiries flood customer support every day. AI excels here, as it is always on, never overloaded, and capable of handling thousands of requests in parallel. For instance, according to the report, AI resolves customer issues 44% faster and increases the quality and consistency of support by 35%. And it is an expected result as it has no business hours or wait time — it is an instant, automated service.

But is there something more about how AI helps optimize processes? Yes. These tools do not just respond to queries, they also feed human client support representatives with real-time data, transaction histories, and predictive prompts. Therefore, human agents provide more accurate responses to the complex issues they deal with.

Security is another factor that should not be written off when it comes to automation, especially when talking about fintech. AI can easily detect behavioural anomalies and flag potential threats right when they appear, letting companies intervene before fraud occurs.

Imagine that a user is logging in to the banking app from a new device in a place where he has never been before. After that, they want to make a high-value transaction to an account that is not on the usual list of recipients. In that case, AI detects the pattern instantly, freezes the transfer, and alerts the user about suspicious activity. False alarm, you say? I disagree; it is far better to prevent than to apologize.

Obviously, AI brings scale, speed and intelligence to customer service in the fintech industry. No one argues that it is imperfect and it still can not be a full replacement for human agents, but it definitely enhances customer support quality without burning out the people.

Where AI Falls Short — Human Steps in

Apart from the strengths AI has, it is still not a silver bullet. AI does not feel or reassure. It shows its limit when deeper understanding, empathy, or human judgment is required, making the role of human agents indispensable. So, when customers face fraud or financial stress, they want someone who listens and can say, “I can relate and help sort things out.” 

A survey by Callvu shows that some of the interviewed people would prefer talking to human agents due to “uniquely human abilities such as empathy.”

The same is true for the lack of structure in customer service. Financial conversations often bring emotional weight, and users do not always speak with clean, structured and predictable prompts. They could use sarcasm, ask superficial questions, or even jump between topics. Of course, a human can read the tone, catch the wave, and adapt on the fly. AI? Not yet.

Then, it is about a shortage of trust in AI and its responses. CX Dive’s survey highlights that nearly half of consumers say that they do not fully trust information from chatbots. And indeed, who would when a bot sends vague messages like “There is an issue with your account” without proper clarification? So, in moments of panic or confusion, a competent human voice sounds way more compelling and trustworthy.

Another Achilles’ heel of AI that is crucial for today in customer service is that it still makes mistakes. It is fast but not always right, as algorithms can misclassify urgent issues or make up a problem because it does not match the expected patterns. AI sees data points — humans see people.

For instance, if a user is disputing a suspicious charge, AI could automatically deny the claim. Once, it correlates with past spending patterns, omitting the fact that the card was not used by him. This would have never happened if the problem had been solved by a trained customer support representative. They can look beyond the transaction and into the situation and help to settle it.

The Best of Both Worlds: Smart Tech, Human Touch

Everything stated in the previous chapter draws us to a simple point: AI alone in client support is definitely not enough. At the same time, this does not mean there is no place for AI in the future of client service in the fintech industry.

Quite the opposite — when paired thoroughly with human expertise, AI turns into a force multiplier. This is why a growing number of fintech companies are embracing a hybrid support model. A vivid example here is the Swedish fintech company Klarna, which launched an AI-powered chatbot a year ago. As a result, it handles two-thirds of customer inquiries, while the rest go to human agents. Well, is synergy possible? Absolutely.

And in fact, it is already happening. Some of the most progressive fintech firms, especially those serving freelancers or digital creators, are opting for human-first, tech-enhanced support. Their customers have to navigate inconsistent income, niche platforms, and complex financial questions, so it is definitely not about just resetting passwords or checking the balance.

In the end, it is not about choosing between AI and humans — it is about combining their strengths. While human oversight reduces errors, helps to deal with unstructured conversations and restores trust, AI easily handles FAQs, improves security, and provides real-time information to agents. 

So, the real advantage lies in the blend: AI ensures the scale, and humans bring the soul.