Is AI hype killing the customer experience for financial services?

Last year, 75% of financial firms were already utilising artificial intelligence (AI), with an additional 10% planning to implement AI over the next three years. Much of this is at the front end of the existing customer service request journey and leaves many people cold and disappointed. In the rush to implement and co-brand with AI, many firms are missing the impact of tools to create real value to operations. Just onboarding tools for the sake of tools isn’t enough; AI needs proper, thorough integration into business technology stacks and strategy that is intimately linked to authentic customer journeys, which are currently being overlooked for the sake of cashing in on the hype.  Poorly done, the result can be a thin and shallow implementation.

Businesses are worried about being left behind when it comes to the latest technologies. When you think your competition is already five steps ahead, that’s when you start to get more desperate in decision-making. Unfortunately, when it comes to opportunities with AI, there needs to be proper consideration about what is going to drive great customer interactions, and more understanding of where your business can have the maximum revenue-increasing impact with AI-supported services.

Onboarding and sustaining the right tools takes time; it’s not a simple quick fix or update, and it is rare that organisations adopt them properly. Fintech leaders are currently underestimating the level of embedded technology needed to bring fully functioning advanced technology to their operations, whether that be for ensuring predictive analysis and data availability for personalised experiences, or assuring regulatory compliance associated with the vast amounts of sensitive customer and financial data being utilised.

Additionally, overblown claims about AI’s capabilities can lead fintechs to invest heavily in solutions that often fail to deliver on their promises. Whether this be through wasting resources, or exaggerating AI capabilities with “AI washing” misleading claims, it’s important to ensure that any AI technology rollout is measured and functional, living up to realistic expectations rather than getting caught in industry hype claims.

While AI-powered chatbots and virtual customer assistants have the capabilities to handle routine queries efficiently, often these AI tools struggle with more complex, nuanced or emotionally sensitive customer issues. Frustrated customers feel their unique needs are not being understood or addressed.

Many customers expect highly personalised experiences, but a generic AI-driven solution cannot deliver this. Often chatbots only offer generic responses that can ultimately negatively impact brand loyalty. Modern customers want to be heard and have higher expectations than basic transactions; they want to feel valued for more than just their wallet.

In implementing a tailored, purpose-built AI within fintech CX operations, institutions can transform engagement with their customers. With unified, AI-powered solutions, financial services providers have greater breadth in analysing vast amounts of data in real-time, enabling them to understand customer behaviours, preferences and patterns on a micro and macro level, and roll out more customised interactions and offerings for individual customer needs. However, incorrect predictions, data entry errors and biased automation algorithms have a negative effect on FS new product investment decisions and lending practices, so it remains important that informed and sensitive human oversight is part of the equation for customer interaction design.

Customers’ experiences can be ruined if AI-driven personalisation is presented in an invasive or manipulative way. Fintech brands are particularly at risk, highlighting the importance of treating the technology with ethical sensitivity. Ensuring regulations for data use, transparency and human oversight are important to balancing unique and meaningful CX with data privacy concerns – something that a clumsy rush to implement, open-source LLM or data tool will miss completely.

For any competitive FS firm or fintech, decisions for integrating AI tools must have the customer at their heart, taking into consideration their wants as a user and their data privacy needs, rather than following the hype just because that’s what the industry appears to be doing.

A more practical approach involves defining your business challenges and goals and then seeking the most suitable technological solution, which may or may not involve the most cutting-edge AI, or rather, a more focused or perfected solution that works for your needs. It is only through balancing these aspects that businesses can better navigate competitive landscapes, and onboard tools that give customers a secure but meaningful experience with their brand.