Although personalisation has been a familiar goal in the banking industry for years, most banks still fall short of delivering what today’s customers actually expect—hyper-personalised experiences.
In fact, nearly 94% of banks are unable to meet the demand for deeply tailored services that customers now prefer.
According to Ram Devanarayanan, Head of Business Consulting Europe at Infosys Finacle, banks need to focus on three critical areas to successfully scale hyper-personalisation.
The Changing Face of Banking in a Digital World
As digital technologies rapidly reshape the banking landscape, banks can no longer rely on traditional methods.
The rise of fintech companies and digital-first banks has increased customer expectations for faster, smarter, and more personal banking experiences. Generic services and blanket communications no longer cut it—modern customers want interactions that are relevant, intuitive, and meaningful.
They expect the same level of personal engagement from their bank that they receive from online retailers, streaming services, or social platforms.
A report by Deloitte confirms this shift, revealing that customers now demand real-time, sophisticated and personalised interactions with their banks—comparable to what they get in other industries. Many are even willing to share more personal data if they’re confident it will lead to tailored services and better financial experiences.
Understanding Hyper-Personalisation in Banking
Hyper-personalisation goes beyond traditional personalisation by using advanced data, artificial intelligence (AI), and machine learning (ML) to offer ultra-targeted services. This approach involves gathering and analysing a wide variety of data—from customer behaviour to real-time activity—to deliver highly relevant messages, products, and support at the exact moment a customer needs them.
In simple terms, hyper-personalisation means sending the right message, with the right product or advice, to the right person, at the right time—based on recent activity, preferences, financial goals, and even lifestyle events.
Despite its benefits, making hyper-personalisation work at scale is a major challenge. A joint report by Infosys Finacle and Qorus titled Maximizing Digital Engagement revealed that while 71% of banks run personalised marketing campaigns, fewer than half are using deep customer data to offer proactive advice, segment users effectively, or apply AI-powered recommendations.
This gap highlights the need for banks to move beyond surface-level personalisation and embrace a more robust, data-driven approach.
Three Core Areas for Delivering Hyper-Personalisation
To truly scale hyper-personalisation, banks must invest in three key capabilities:
1. Truly Know Your Customer (KYC 2.0)
Knowing your customer today means far more than collecting basic demographics like age or income. Banks need to create a 360-degree view of each customer, integrating data from various sources including:
- Social media interactions
- Past banking activity
- Lifestyle changes and life stages
- Behavioural and transactional trends
Some progressive banks have started developing what’s called a “customer genome”—a model that builds detailed customer profiles using demographic, behavioural, and even social data. With this model, banks can predict future needs, launch targeted products faster, and provide more relevant offers.
For example, instead of assessing creditworthiness solely based on income or credit scores, banks are now factoring in real-time behavioural data to instantly approve “Buy Now, Pay Later” offers, giving customers faster access to financial solutions.
Achieving this level of insight requires a strong digital architecture, including a unified data platform that eliminates inconsistencies, streamlines product creation, and enables dynamic pricing and bundling of services tailored to individual preferences.
2. Extracting Meaningful Customer Insights
Data is a goldmine—but only if it’s analysed effectively. Banks need to harness customer data to uncover three critical types of insights:
- Descriptive insights – Help banks understand what a customer is doing, such as their spending habits, savings behaviour, or investment choices.
- Diagnostic insights – Answer deeper questions like “Why is this customer saving less?” or “Why did their account balance drop?”
- Predictive insights – Anticipate future financial behaviour, such as when a customer might face a cash flow shortfall, miss a payment, or even be at risk of fraud.
To make these insights actionable, banks must adopt modern tech frameworks. This includes cloud platforms, AI-powered analytics, and asset libraries that bring together all layers of decision-making—from data collection to execution.
With nearly 86% of banks considering cloud-based CRM solutions, there’s a clear move toward building scalable infrastructure that supports personalised banking on a large scale.
3. Acting on Insights in Real-Time
Understanding customers is only the first step—acting on that knowledge is where real hyper-personalisation happens. Banks must use these insights to guide customers through smart financial decisions, with personalised prompts or “nudges” tailored to their specific situation.
These nudges could include:
- Suggesting automated savings options
- Recommending investment tools
- Offering the next best action in their financial journey
Conversational AI tools like chatbots and voice assistants play a key role here. These tools can deliver real-time, 24/7 support and recognise when a customer needs a human touch. By doing so, banks can reduce waiting times, improve satisfaction, and build stronger emotional connections with customers.
Take Erica, Bank of America’s virtual financial assistant, as an example. Erica uses real-time data like account activity, spending patterns, and payment history to hold smart, proactive conversations with users. Another case is Monzo, a UK-based digital bank that uses behavioural analysis to allow support reps to resolve 85% of customer queries without escalating to their data team.
The Road Ahead: Embracing Hyper-Personalisation
There’s no doubt that hyper-personalisation is the future of banking. To get there, banks need to blend deep customer understanding with modern technologies and organisational change. Success depends on three things:
- A culture shift toward true customer centricity
- Investment in AI, ML, cloud computing, and real-time analytics
- A move away from product-first thinking toward needs-based engagement
When done right, hyper-personalisation allows banks to stand out in a crowded market, deliver real value, and become more than just a service provider—they become a trusted financial partner.
In today’s competitive and fast-paced digital economy, banks that embrace this evolution won’t just survive—they’ll thrive by offering smarter, faster, and more human-centric financial experiences.
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