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Personalization Is Broken: How data maturity and Agentic AI can fix it
Despite high digital engagement, banks struggle to move beyond the transactional when it comes to the customer relationship. This disconnect stems not from a lack of digital tools, but from an under-leveraged asset: data. Get this right and there’s a huge opportunity to reset the customer relationship for a more profitable future
Ongoing digital disruption has brought the major banks to an unusual position. Customer engagement has never been higher, with many customers logging into their mobile banking app multiple times a week[1], typically to check balances and transfer money. Yet the frequency of these interactions has not translated into emotional engagement, with one survey finding 40 per cent of consumers find it hard to distinguish between financial service brands[2].
This is an uncomfortable place for banks to sit, risking churn, limiting growth and vulnerable to disruption. With 68% of customers using multiple providers, traditional banks risk becoming commoditized, diluting opportunities to earn trust, cross sell and build value over a lifetime. Research shows that emotionally connected customers are more valuable – advocates use 17 per cent more products and contribute 1.7x more in revenue growth[3]. Converting consumers into brand cheerleaders really does pay.
The personalization gap: high expectations, low delivery
This conversion doesn’t happen by accident. Advocates are born when banks nurture experiences that are personal, authentic and add value. Consumers want personalization – 72% say it influences their banking decisions – but only 3% use the tools banks provide. Customers feel bombarded with offers, and personalization often feels more like sales than service while the need to repeat key information at every hand-off is the opposite of feeling seen and understood. This mismatch erodes trust and reduces the impact of digital tools.
‘There’s a clear disconnect between what customers want and what banks think they want,’ says Alex Fan, data and AI lead, FSI at Avanade.
Data matters - but not just any data
Personalization requires more than knowing a customer’s name or balance. It’s about making a customer feel known and understood – a throwback to the personal touch of branch banking where the bank manager knew customers by sight. Recreating this for the digital age means context, continuity and real-time insights to deliver products and experiences that meet each customer’s needs – rather than those of the bank.
It’s one thing to conceptualize personalization, however, quite another to deliver it, especially for organization’s that are subject to high degrees of regulatory scrutiny. Use cases must be grounded within the realms of what is practically possible given the challenges of data silos, regulatory compliance and customer attitudes. It’s essential, says Alex Fan, that banks get the data foundations right before deciding which use cases to pursue.
‘You have to understand and evaluate from a governance perspective what data you have, where it resides, how it’s secured and how it’s accessed, and this work then goes into the decisioning and execution of the use cases,’ he says.
Banks can’t afford to get this wrong when it comes to customer-facing propositions. ‘Bad data is not a pick and mix issue,’ cautions Harry Wang, director of analytics at Fifth Third. ‘It’s a customer loyalty issue.’
Get the foundations right, and good data starts to flow. ‘When you can demonstrate you understand the customer, they will trust you and be willing to share more data, which enriches your data set more,’ says Wang.
Data: commoditized and ready to go
Data isn’t just foundational – it is increasingly a product itself. Many customers have a clear appetite for analytics based on their own personal data to give them useful and unique insights into their own financial habits so they can make smarter decisions. The more data banks can convert into insights, the better the outcome for customers.
‘Banks already have a wealth of data but there are still a lot of signals that are untapped, whether it’s the core banking system or payment system,’ said Fan. ‘Bringing those additional sources, such as social media or geolocation, which are already used by other industries, will be where we will see hyper-personalization in the future.’
Commoditize to transform at speed
Data-driven personalized experiences require companies to overcome legacy issues, whether it’s systems, processes or people, with data literacy increasingly a core banking skill. ‘You really need a data-driven culture,’ says Fan.
This whole-enterprise transformation may not eliminate data silos, but it should embrace new ways of ingesting, integrating and generating insights from disparate data sets.
‘In reality, data silos might not ever truly go away because there will be different products and different niches that are doing well,’ says Alex Fan. ‘What’s more important is commoditizing that data ingestion component, so you can get the data unified and make that piece really easy and move at the speed of the business.’
Agentic AI: unlocking personalization
And that speed is accelerating all the time. The emergence of Agentic AI – generative AI agents that autonomously manage tasks – promises to transform banking. These agents can act as real-time, always on advisors, combining remembered context with live data to deliver truly personalized interactions.
The result will be service that feels faster, smarter and more human. Churn will be reduced as AI agents flag at-risk customers so banks can take proactive steps to retain them through personalized offers, discounts and services. Marketing segmentation can be far more finely calibrated, and customers can expect more personalized recommendations and advice, such as investment opportunities, loan products, or budgeting tools that are based on individual financial habits. Access to credit can be fast-tracked, where appropriate, as Agentic AI systems analyze spending habits, social media behavior, and even real-time income data, to offer more accurate and personalized loan approvals.
A built-in audit trail
Beyond productivity gains, Agentic AI improves trust and compliance by embedding audit trails and transparency into every action.
This technology also helps with the growing compliance demands being placed on users of AI models. ‘Agentic frameworks have responsible AI built into them, creating audit logs of every step so from a regulatory standpoint, it makes everything more transparent and explainable,’ says Alex Fan.
This matters. Because if data is the foundation, then trust is the cement. Start with trust, build with relevance, and the loyalty that builds competitive edge will follow.
Want to know more? Check out:
[1] Users typical average 130 interactions a year, almost 11 a month. Consumer Survey – Where is the Love?
[2] Accenture 2025 Top Trends report in banking
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