In today’s highly competitive landscape, banks must navigate technological disruption, evolving customer expectations, and regulatory pressures. One emerging differentiator has the potential to transform client engagement and redefine success in the financial sector—hyper-personalization.
As a Client Partner at Apexon, I’ve observed how hyper-personalization is no longer just a buzzword; it’s becoming a strategic priority for banks striving to remain relevant. Let’s explore how hyper-personalization is transforming client engagement and what it means for both the industry and client relationship managers.
Clients expect more from their financial institutions than ever before. A study by Deloitte found that 80% of banking customers are more likely to engage with an organization that offers personalized experiences tailored to their needs and preferences (Deloitte, “Digital Banking Reimagined”). Gone are the days when generic product offerings sufficed. Today’s clients seek tailored advice, relevant recommendations, and proactive solutions that align with their financial goals.
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Many of us have already experienced a version of personalization-think about how Amazon or Netflix recommends products or shows based on past behavior. But hyper-personalization goes deeper. It’s not just about what clients did—it’s about predicting what they’ll need in the future. For banks, this means leveraging real-time data analytics, AI, and machine learning to understand individual client behaviors on a granular level and offering tailored solutions before clients even realize they need them.
Hyper-personalization hinges on the effective use of data. Banks sit on a wealth of customer data, yet many still struggle to unlock its full potential. Every transaction, click, and inquiry provides insights into client priorities, but how many banks truly harness this data to deliver unique, personalized experiences?
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With advancements in big data analytics and AI, banks can now analyze data in real-time to build rich, 360-degree views of their clients. This enables everything from personalized investment recommendations to custom mortgage solutions. Imagine a bank that automatically adjusts your portfolio based on market fluctuations or recommends a savings product when it detects a change in your spending patterns. This is hyper-personalization at its finest.
Boston Consulting Group highlights that banks aiming for successful hyper-personalization need a robust infrastructure integrating data analytics, AI capabilities, and a cross-functional mission. For example, banks deploying an “analytics factory” with reusable algorithms and a centralized data library can quickly scale personalization across campaigns. This library comprises multiple client insights and consistently refines recommendations and predictions, leading to a higher customer lifetime value (CLV) as banks retain and deepen relationships with their most valuable clients.
NatWest
NatWest, through its partnership with open banking platform Tink, integrates hyper-personalization into its mobile app, providing real-time, highly relevant insights to users. By analyzing spending habits and individual financial behaviors, NatWest curates a personalized newsfeed for each customer, offering timely advice, financial tips, and tailored offers. Within the first few months, this feature resulted in over 1.3 million interactions, underscoring the value of hyper-personalized communication in boosting client engagement and satisfaction.
Publicis Sapient, Global Banking | Finance
BBVA
BBVA has been at the forefront of hyper-personalization. They launched a program that uses AI to analyze customers’ financial habits and offer tailored recommendations for saving, spending, and investing. For instance, their mobile app sends personalized notifications to clients nearing their monthly budget, along with tips on staying on track. The result? A 37% increase in client satisfaction and a significant boost in cross-selling of financial products (BBVA, “AI and Hyper-Personalization in Banking”).
Goldman Sachs
Goldman Sachs’s wealth management division also embraces hyper-personalization. Through their AI-powered CRM platform, Goldman Sachs identifies key insights from clients’ portfolios, transaction histories, and investment behavior. Their Marcus by Goldman Sachs platform goes beyond traditional banking by personalizing financial advice and lending options based on user behavior and real-time financial changes. This approach has not only improved client satisfaction but also strengthened loyalty, with clients feeling that their financial needs are proactively addressed at every stage of their investment journey.
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Challenges in Implementing Hyper-Personalization
Despite its benefits, hyper-personalization presents significant challenges. The most pressing concern is data privacy. Clients are increasingly sensitive to how their data is used and shared, especially with regulations like GDPR and PSD2. Banks must balance personalized experiences with maintaining client trust; failure to do so can lead to reputational damage or regulatory penalties.
Implementing hyper-personalization also requires significant investment in technology infrastructure, talent, and data management capabilities. Many banks are still playing catch-up, and smaller institutions may find it challenging to compete with larger banks or fintech disruptors that have already embraced AI and data analytics.
Deloitte emphasizes that true hyper-personalization requires financial institutions to shift from product-centric to client-centric models. This involves integrating data insights across client journeys, identifying a customer’s need for specific products or services based on life events and behaviors. Such alignment with real-time client needs fosters trust, providing a competitive edge by making clients feel understood and valued.
Deloitte United States, Blog | Finotta
For IT consultants, hyper-personalization represents an opportunity to add tremendous value to our banking clients. Beyond simply providing technology solutions, our role is to guide clients in transforming their business models to prioritize client-centric approaches. From CRM implementations and data analytics solutions to AI integrations, we can play a critical role in helping banks navigate this transformation.
This requires more than just offering tools; it involves helping banks understand their data, select the right technologies, and embed hyper-personalization at the core of their client engagement strategies. At Apexon, we are positioned to support these changes with end-to-end consulting services that align closely with the needs of modern banking institutions.
Hyper-personalization is here to stay. Banks that embrace it will be the ones who thrive in the digital age. Those that don’t may find themselves left behind in a world where clients expect nothing less than personalized experiences. The question is no longer whether hyper-personalization is worth the effort—it’s about how quickly banks can implement it to stay ahead.
Let’s continue the conversation. How do you see hyper-personalization evolving? What are the biggest opportunities or challenges in this space?
Also read: Hyper-Personalization in Banking – The Future of Client Engagement