Thursday, 23 May 2024

AI and big data-based apps provide strong potential to drive hyper-personalisation

5 min read

By Chris Kapfer & Jeff Villapando

The banking industry is using AI and data strategies to meet customer preferences, focusing on digital culture, secure operations, and partnerships to overcome challenges and cultivate customer-centricity

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 engage, retain, and fortify customer relationships. Nonetheless, the journey to implement hyper-personalisation is fraught with challenges. To surmount these obstacles, banks cultivate a digitally-minded organisational culture that fosters experimentation and innovation. There is a focus on ensuring the convenience, reliability, and security of banking operations. Additionally, forming strategic partnerships to access third-party data while safeguarding trust and privacy becomes imperative.

Hyper-personalisation, at its core, seeks to alleviate customer pain points by providing value through AI-driven auto-savings products and collaborations with ecosystem players. Financial institutions (FIs) keen on achieving this goal champion innovation and agility, spearheading digital transformations by decentralising decision-making processes and actively involving tech-savvy professionals in shaping a resolutely customer-centric culture within the organisation.

AI, big data-based apps drive personalisation

The pursuit of hyper-personalisation in the industry has reached new heights, driven by a potent combination of AI and big data-based applications. These technological advancements hold the potential to revolutionise the way FIs interact with their customers, offering tailor-made experiences that adapt to individual needs and preferences at different life stages.

One notable example of hyper-personalisation is ila Bank’s ila Rewards credit card programme, supported by Mastercard’s Pay with Rewards (PwR) platform. This digital mobile-only bank in Bahrain allows customers to instantly redeem rewards through the bank’s app. 

Singapore bank OCBC has embraced a hyper-personalisation strategy around total wealth integration based on life goals. With data aggregated from multiple sources, OCBC has been providing customers with a comprehensive financial planning journey since 2018, addressing the demand for consolidated data at both the bank and product levels. Real-time information from third parties, exemplified by its significant market share in Singapore Financial Data Exchange (SGFinDex) sign-ups, further enhances the bank’s hyper-personalised financial services. Partnership opportunities, like application programming interface integration for tax payments with the Inland Revenue Authority of Singapore, the government agency responsible for the administration of taxes and enterprise disbursement schemes, illustrate OCBC’s commitment to delivering personalised solutions to its customers.

In the global landscape, Klarna, a global retail bank and payments service, leverages its in-house AI product recommendation engine to offer a personalised shopping feed to its users. This feed continuously adapts and improves as it learns about the user’s preferences, redefining the shopping experience. Users can snap a photo, and AI instantly translates the image into a searchable term, and suggests places to shop for the items in the photo. Additionally, the app’s search and compare tool goes the extra mile, scouring the internet for the best online deals, ensuring users get the most personalised and cost-effective shopping recommendations. 

Meanwhile, Commbank in Australia uses AI through its customer engagement engine to provide personalised and relevant digital experiences to its vast customer base. Features such as Bill Sense and Benefits Finder enhance customer control over their finances and elevate the overall customer experience.

In 2018, Erica debuted as a virtual banking assistant, swiftly serving 32 million customers with over one billion interactions. Bank of America (BoA) is now elevating Erica with hyper-personalisation. Starting in early 2023, Erica users gain the option to seamlessly switch to a human agent for extra support. The agent continues the conversation where Erica left off, and after resolution, clients seamlessly resume their interaction with Erica. Erica employs natural language processing and predictive abilities to anticipate customer needs. Agents harness Erica’s data to suggest tailored products. The convergence of AI and big data-based applications is driving a wave of hyper-personalisation in the financial services industry. These advancements empower customers, streamline processes, and enhance overall experiences, setting new standards for customer-centricity in banking and finance.  

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
Institution: Ila Bank, OCBC, Klarna, Commbank, Erica, Bank Of America
Country: Singapore, Bahrain, Australia, Taiwan, US
People: Piyush Gupta
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