AI-powered personalisation: How is it transforming everyday banking?

We are entering a transformative era in banking, driven by artificial intelligence (AI), which is profoundly impacting financial entities’ ability to hyper-personalise their customer offering. Banks are harnessing AI to deliver meticulously tailored experiences that meet the unique needs and preferences of their customers, with the opportunity presented by AI in this sector immense; forecasts suggest the possible creation of up to US$1 trillion in yearly value.

The impact of generative AI, in particular, is expected to revolutionise banking, with projected spending anticipated to increase an incredible 1,430% from $5.6 billion in 2024 to a staggering $85.7 billion by 2030. This highlights the essential function of AI-driven hyper-personalisation in the swiftly evolving financial environment, and the crucial need to fully embrace the technology in order to stay ahead of the curve.

Hyper-personalisation means using advanced technologies, like AI, to deliver highly individualised products and services. As consumer expectations rise, banks must offer experiences similar to those found in leading digital platforms. Research reveals that more than half of consumers expect banks to demonstrate a deep understanding of their needs and respond with meticulously tailored financial offers, making hyper-personalisation crucial in developing trust, the cornerstone of the customer-bank relationship.

By creating solutions that reflect evolving individual needs, banks can nurture stronger trust and foster lasting loyalty. In a competitive arena, bespoke banking services such as individualised loan options or credit card rewards set banks apart from the competition, forging deeper customer connections and establishing a clear advantage over simple, uniform offerings.

AI plays many roles in transforming personalisation into hyper-personalisation. It allows banks to leverage data for insights, enabling the analysis of extensive data sets to uncover trends which can then assist in creating tailored offerings. By using genuine user data, banks can develop products that truly align with customers’ needs, resulting in increased satisfaction and engagement.

Machine Learning has been part of banking for years. It allows banks to examine past customer behavior and use models to protect customers through fraud detection and to anticipate future demands, enabling banks to offer hyper-personalised services which often proactively meet customer needs.

Generative AI can write, explain, summarise, and converse. It powers chatbots and virtual assistants, enhancing customer engagement through smooth, conversational interactions. These tools can manage complex inquiries and provide swift, precise responses. Some AI chatbots can manage over 100,000 chat sessions each month in the UAE. The AI powered chatbot boosts service availability, and reduces call centre traffic, in turn enabling staff to turn their attention to more complex customer enquiries, that benefit from greater human involvement.

Agentic AI takes the next step: it acts. It can act on a suspicious activity and automatically block a card or execute a transaction on behalf of a customer — all within defined compliance and risk parameters. It enhances banking processes, and therefore operational efficiency, through intelligent automation of repetitive tasks such as KYC and data entry. This not only cuts costs but also frees up employees for higher-value activities, optimising efficiency across the organisation. Automation also bolsters security; AI systems monitor real-time data to assess customer behaviour and device integrity, enabling early detection and prevention of fraud.

Innovations in customer service, fraud detection, and compliance are among the key factors propelling the rise of AI in the banking industry, enhancing operational efficiency, lowering costs, and disrupting traditional business models. Generative AI has the potential to enhance bank revenues by up to 6%. By streamlining routine tasks and enhancing personalised offerings, banks can reduce costs while improving their value proposition. It can also boost operational productivity by 22-30%, helping banks optimise critical areas such as risk management and compliance. This adaptability enables institutions to quickly react to market changes without compromising quality. By enabling customised products and services that meet the unique needs of individual customers, banks can also reduce churn rates and improve customer retention. AI-driven solutions provide personalised experiences that both attract new clients and strengthen relationships with existing ones.

Looking ahead, the different types of AI will work together. We see systems where Generative AI manages customer interaction, Agentic AI executes actions, while Machine Learning models predict intent and identify risk in the background.

AI is becoming increasingly interwoven into the growth trajectory of banking, with systems set to continue – and further expand – proactive anticipation of customer needs and the delivery of hyper-personalised financial insights. We move from reactive to anticipatory banking – with customers’ consent, banks can predict cash flows, events, or risks — and act before problems arise. Banks that invest in AI-driven hyper-personalisation today will be best positioned to meet rising customer expectations, foster long-lasting loyalty, and drive sustainable growth.

As banks embrace AI, it is essential to do so responsibly. Growth must occur within frameworks that prioritise explainability, security, and transparency—building trust and keeping the customer at the centre of every innovation.

Radu Topliceanu is EVP, Head of NEO and Personal Banking at Mashreq