The banking industry is transitioning from traditional segmentation and micro-segmentation to hyper-personalisation. Artificial intelligence (AI) and data strategies can now deliver tailored experiences and make stronger connections with customers. Global banks have embraced this trend to understand and adapt to the customer’s changing preferences across various life stages. Banks are adopting customer-focused values, investing in technology, and forging strategic collaborations for next-level hyper-personalisation.

Targeting customers with personalised products

Take for instance Singapore’s UOB, a bank that promotes wealth services to customers according to their net worth in a ‘network-net-worth’ model. Over the past three years, UOB has developed about 70 machine learning (ML) models to spot potential wealth customers.

In 2022, Taiwan’s Cathay United Bank (CUB) launched its CUB mobile banking app. It was upgraded into the CUBE app with better product planning, customer experience and services, and platform design. In the same year, the bank saw increased customer growth. With the second-highest customer base in Taiwan, the bank has maintained a compound annual growth rate of 44% of active users, while also developing new features and functions in its digital channels to provide a more inclusive service.

Banks harness data and technologies to anticipate customer preferences and demands for personalised experiences. Hyper-personalisation encompasses segment-level customisation where organisations align with customer aspirations, so every interaction leads to personalised products and services.

Banks cultivate digitally-minded culture

Banks, in response to globalisation and socio-demographic shifts, are compelled to adopt hyper-personalisation strategies as a means to engag...

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Keywords:AI, Big Data, Hyper-personalisation, Banking Industry, Customer Preferences, Digital Culture, Secure Operations, Partnerships, Customer-centricity, UOB, Cathay United Bank (cub), Data Strategies, Digital Channels, Financial Institutions (fis), Ai-driven Auto-savings Products, Third-party Data, Virtual Banking Assistant, Natural Language Processing, Predictive Abilities, Customer-centricity In Banking And Finance