Lynda Clarke, Chief Operating Officer at Tribe Payments – a leading digital payments and infrastructure orchestrator specialising in issuer and acquirer processing, explores how hyper-personalisation is transforming banking and redefining customer experiences.
Today’s customers no longer settle for generic banking services – and small and medium-sized enterprises (SMEs) are no different. SMEs, which account for 99.8% of all businesses in the UK and contribute £2.8 trillion to the economy, increasingly expect highly tailored experiences that meet their specific business needs in real time.
Thanks to advancements in AI, big data, and behavioural analytics, banks now have the tools to move beyond standard personalisation and embrace hyper-personalisation. This evolution isn’t just about improving customer experience, it’s transforming SME banking by enabling financial institutions to deliver more relevant, actionable, and proactive support to small businesses.
The power of hyper-personalisation for SMEs
Personalisation has long been part of banking, but traditional approaches typically rely on historical data to predict future customer needs. While this has allowed banks to tailor products and services to some degree, hyper-personalisation takes things a step further. By integrating live data, AI-driven insights, and predictive analytics, banks can better anticipate SME needs – sometimes before the business owner is even aware of them.
For SMEs, this could mean more tailored financial products and services that better meet their specific business needs. For example, by personalising lending amounts or cashflow advances based not just on their credit scores but also on future order pipelines, rental and lease payments.
So, when can SMEs expect to be offered the full swathe of hyper-personalised banking services? Well, despite the clear advantages, many banks struggle to implement these strategies effectively. Legacy infrastructure, regulatory complexities, and risk-averse cultures have slowed progress. But with 76% of people expressing frustration at the lack of tailored banking experiences, more financial institutions are starting to pay attention.
Implementing hyper-personalisation
To shift from offering generic products to delivering deeply personalised services for SMEs, banks must rethink their approach across several dimensions. First, they need strong data infrastructure. High quality data is the foundation of hyper-personalisation, and financial institutions must ensure they have the right tools and expertise in place to collect, analyse, and act on real-time insights. Skilled data scientists are essential to extracting meaningful patterns and using predictive analytics effectively.
Second, banks should clearly define their personalisation goals and expected offering. Identifying the areas where hyper-personalisation can have the most impact, whether in lending, payments or cash flow management, ensures that efforts are focused and measurable.
Third, AI-powered recommendation engines and advanced analytics tools must be integrated into the bank’s customer journey. Real-time targeting enables banks to deliver proactive financial guidance, personalised product offerings, and seamless user experiences. However, technology alone isn’t enough. Cross-functional collaboration between marketing, product teams, analytics, and IT is crucial for success.
Fourth, transparency is key. Customers are typically more willing to share data when they understand how it will be used to enhance their experience. By communicating data privacy policies and security measures, banks can build trust while offering tailored solutions.
Finally, hyper-personalisation should be treated as an evolving process. Implementing A/B testing and continuously refining strategies ensures that banks remain adaptive to their customers’ expectations and emerging market trends.
While many financial institutions have automated front-end and back-end processes, true hyper-personalisation remains underdeveloped in much of the industry. However, there are clear success stories that demonstrate its potential impact when implemented effectively.
Real-world successes
The Bank of Ireland has successfully integrated customer data from both online and offline channels to create highly personalised banking experiences. This approach has led to a dramatic increase in digital applications and customer satisfaction.
HSBC has implemented AI-driven personalisation in its credit card rewards programme, tailoring offers to individual spending habits. This strategy has resulted in higher engagement and increased customer loyalty.
Meanwhile, digital bank Nubank has adopted AI-based predictive analytics through its Precog system. By using machine learning (ML) to anticipate customer needs in real time, the bank has improved its ability to predict customer intent during service interactions by more than 50%, allowing for more proactive and personalised support.
The future of SME banking
Hyper-personalisation is no longer optional – it is an imperative for staying competitive in the fast-evolving world of SME banking. By embracing AI-driven personalisation strategies, banks can unlock new revenue opportunities while deepening relationships with small business clients.
For SMEs, the benefits are clear: more relevant financial products, better access to credit, and proactive guidance that helps them navigate challenges and seize growth opportunities. As digital adoption continues to reshape the way SMEs interact with financial institutions, banks must rise to meet these expectations or risk losing relevance.
Financial institutions that invest in hyper-personalisation today will not only enhance satisfaction but also secure long-term loyalty from one of the most vital segments of the economy – SMEs.