Personalised offers for products and services and timely advice for financial and wealth management, especially with the cost-of-living crisis, are all examples of banks offering tailored services to their customers. Traditionally, financial institutions have delivered this level of service through face-to-face interactions in physical bank branches. However, as 1,378 branches have been closed since May 2022, banks must pivot their personalisation strategies to create personalised experiences for customers via digital means. The branch had traditionally always been the largest source of sales, but this has rapidly shifted to a majority online for many products like cards, with the more complex or high value such as mortgages or investments still getting face to face time.

With select employees of banks only spending one third of their time on customer-facing interactions, and customers believing that digital channels are impersonal, financial services institutions are under an immense amount of pressure to get their customer service right in these new circumstances. 

Creating personalised experiences

One of the ways banks can create tailored experiences and have frequent and highly personalised conversations with their customers is through deploying AI in their operations, specifically predictive and process AI and generative AI.

Financial services institutions already collect and store large amounts of customer data, but now they can use AI-driven tools to gain significant insights into each customer even as they interact with them. By integrating AI with existing banking systems, vast amounts of customer data can be combed through in seconds to find patterns in behaviour and understand customer preferences. The AI tool can offer real-time updates and recommendations of next best steps to the agent when interacting with customers through digital means or over the phone / video link.

This level of personalisation goes towards understanding customers on a granular level and being able to offer banking products and services which better meet their needs. This not only applies to self-service but how customers interact with bank staff. They can be supported in calls or chat sessions with AI-powered assistance that ensures customer service agents are taking the best possible action at the right moment and in the right context on the channel the customer prefers to be contacted on. For example, taking into account a customer has just looked online on the website for savings and mortgage offset products may indicate a likelihood of saving for a home. Once agents have an in-depth understanding of customer behaviour, they are more likely to recognise and predict what customers need or want next, boosting both experience and personalisation.

With the recent announcement of GPT-4o, AI is fast evolving to offer more natural and human-like interactions. Increasingly the talk is of ‘multi-modal’, simply meaning interaction and interpolation from different formats like video, handwritten notes, pictures, text etc. For example, generative AI has the potential to create assistants which remember what they have been told in the past and can interact beyond only voice or text. With GPT-4o, these chatbots can adapt the sound of their voice from one which sounds like a robot to one which is much more human-like and recognise emotional signals. As such, banks can leverage this technology to create much more tailored experiences for the customers based on past interactions and current emotional states.

Leverage AI to protect customers

One of the top priorities for all financial services institutions is to protect their customers and carefully manage risk. And with the proper integration of AI into backend operations, customers, and banks themselves can be safeguarded against fraud. As AI learns from data, it can automatically adjust to stop new and existing threats, providing real-time detection, which only gets more accurate over time as it continues to learn. This goes even further to highlight just how important it is to have personalised services in banking operations to be able to predict customer behaviour with accuracy and protect them. 

Filling in the customer service gap with AI is the way forward for financial services institutions. Customer service differentiation and efficiency is a real way that banks can differentiate, once a customer has moved beyond the simple (but still dominant) factors of price and product features. The role of AI is growing across banks' backend and frontend operations, and importantly this is benefitting customer service. It is key for financial institutions to properly integrate AI into their operations to see its full benefit, which can be passed onto customers in the form of personalised services across the channel which suits them the best. There is no longer such a thing as ‘personal enough’, customer service must be tailored to each individual and flex as their situation changes. Clearly the appropriate technology applied correctly can differentiate and fill the gaps left by branch closures.