Banking Personalization: Redefining Customer Experience Through AI and Data

Customers want more than just quality financial services—they demand personalized banking experiences that go beyond the basic “being addressed by their names.” Research indicates that 50% of customers consider personalized services a key factor in building trust with their banks. Another survey shows that 66% of respondents are comfortable with financial institutions using their data to tailor services to their needs.

This isn’t surprising. With personalization, customers get relevant financial products and meaningful interactions. Yet, from a bank’s perspective, it raises some critical questions. Does banking personalization truly drive business value? What technological solutions can be implemented to achieve it? And what challenges should be anticipated?

This article explores these issues. It explores advantages banks can get as they tailor their offerings to individual customer preferences, personalized banking strategies to choose from, and the potential pitfalls to avoid. Our insights come from hands-on experience working with leading financial institutions where we’ve witnessed firsthand how tailored banking experiences can transform customer relationships.

Key takeaways 

• Implementing personalized banking services brings many benefits to a financial institution. Improved customer acquisition, loyalty, financial product adoption, revenue, and cost-efficiency are just some of them.
• As many as 65% of consumers believe banks should simplify discovering financial products, which can be achieved with dynamic content personalization.
• Other personalization strategies include tailoring products and services to individual needs, offering advanced support with smart virtual assistants, and using predictive analytics for hyper-personalization.
• Banks using “next-best action” models in their personalization efforts have experienced an average sales increase of about 30%.

Why deliver personalized banking experiences: Key benefits

Personalized banking involves adapting financial services and experiences to a customer’s unique needs and behaviors. While the concept is straightforward, implementing it requires some effort. According to McKinsey, banks have to do more than simply invest in technology. Successful software implementation and unified vision across the entire organization are equally important. 

When executed properly, banking personalization creates measurable advantages that positively impact both customer satisfaction and the bank’s bottom line. Here’s what a bank gains from it:

• Enhanced customer loyalty. Banks can boost customer satisfaction by consistently delivering services tailored to each customer’s preferences. For example, personalized messages delivered through selected digital channels simplify the client’s financial journey, making every interaction more relevant and convenient. With this approach, customers feel more valued, which encourages them to stay loyal to the bank.
• Simplified customer acquisition. Personalization in banking significantly improves ROI from marketing efforts. Tailored email campaigns, targeted ads showcasing relevant services, and precise prospect segmentation help banks acquire new customers and increase conversion rates. 
• Higher product and service adoption. Personalization allows banks to refine their offerings to match the customers’ financial goals and needs. As a result, clients are more likely to adopt the products and services promoted to them, enhancing the bank’s cross-selling and upselling success.
• Revenue growth. Stronger customer relationships, effective marketing strategies, and tailored services driven by personalization help banks maximize revenue opportunities. Implementing personalization in digital banking requires upfront investment, but it pays off in the long run.
• Cost efficiency. Banking personalization reduces marketing waste and improves the output of customer interactions, leading to greater cost efficiency. 

Key strategies of personalization in banking 

Delivering personalization requires a solid strategy to achieve specific results. But before moving to the implementation stage, it’s essential to define two things: how banking personalization should be incorporated into the existing processes and at which touchpoints of the customer’s unique financial journey it should be applied. Below are some of the most popular personalization strategies.

Content personalization

Dynamic content personalization uses data-driven insights to tailor a bank’s messaging based on customer preferences, financial situations, and life events. It typically appears in real time, adapting to the person’s immediate needs or recent behaviors. This can take several forms:

• Dynamic website content. When registered customers visit the bank’s website, the content (e.g., product recommendations or blog articles) updates based on their transactional data, location, or browsing history. For example, a customer who frequently checks mortgage rates will see mortgage-related offers and insights.
• Personalized emails. Banks can send tailored messages that resonate with a specific customer’s interests. This covers everything, from exclusive offers and timely payment reminders to customized loyalty rewards that align with individual digital banking habits.
• Educational content. To nurture robust customer relationships, banks can also provide personalized learning resources. For instance, a customer nearing a certain age may receive a customized guide on retirement savings.

Dynamic content personalization makes banking services feel more personal, significantly enhancing customer experience. The numbers back this up: 65% of consumers agree that a bank should simplify discovering and comparing financial products. On the business side, 55% of email marketing professionals ranked personalization as a top priority.

Tailored services and pricing

Traditionally, banks have relied on a one-size-fits-all approach, providing the same financial solutions with identical terms to broad client groups. However, advancements in technology, particularly artificial intelligence (AI), machine learning (ML), and big data, have transformed this model, enabling financial institutions to offer personalized services adapted to each customer’s needs. 

Tailored solutions in the banking sector can be implemented in several ways, including:

• Adaptable service offerings. This involves customizing credit card terms, personal loans, or savings plans to suit individual circumstances. Example: offering a lower downpayment option for a first-time homebuyer with a stable income and a reliable employment status.
• Personalized financial advice. This is when a bank delivers debt management, retirement, and investment advice that aligns with the customer’s risk tolerance and long-term financial goals. Example: recommending a low-risk bond fund for a conservative investor or a diversified equity portfolio for someone with a higher risk appetite and long-term goals.

Offering tailored services and pricing is one of the most effective banking personalization strategies that helps build stronger customer relationships and attract new clients. According to 71% of consumers, businesses should personalize their services, and 76% get frustrated when this isn’t the case. Additionally, around 32% of UK consumers say they would be open to switching banks if they received personalized financial assistance. 

Dynamic pricing

Dynamic pricing in banking leverages customer data and behavioral analytics to offer personalized rates and fees tailored to each account holder’s financial profile. Unlike traditional one-size-fits-all pricing models, this personalization strategy adjusts financial terms based on factors like credit history, relationship value, usage patterns, and risk assessment. In practice, personalized pricing allows banks to offer:

• Interest rates on loans that reflect individual creditworthiness rather than broad risk categories
• Account maintenance fees that adjust based on customer relationship depth and activity levels
• Foreign exchange rates that improve with transaction frequency or account tenure
• Credit card APRs that adapt to changing customer financial behaviors
• Deposit rates that reward specific customer behaviors, like maintaining minimum balances or using multiple products.

Personalized customer support

Personalized banking services extend to tailored support, where banks use customer data to resolve issues more efficiently. Key elements of this practice include:

• Personalized communication. Instead of generic messages, banks can send tailored information that addresses specific customer financial situations or inquiries.
• Assistance in issue resolution. Banks can proactively address issues when they identify unusual account activity and offer assistance before problems escalate.
• Omnichannel experience. This means ensuring consistent communication across all channels (e.g., phone, chat, email, mobile apps) so customers don’t need to repeat requests when switching between them.

By combining these elements, banks can create a truly seamless and relevant experience. A J.D. Power survey reveals that 78% of respondents would stay with their bank if offered personalized support.

Predicting customer needs

Predictive analytics, which anticipates customer needs before they explicitly express them, is a key element of hyper-personalization—the highest level of digital banking personalization. This approach leverages extensive data to identify signals that indicate what a customer is likely to be interested in the future.

For example, if a customer frequently searches for properties, increases their savings, and inquires about mortgage rates, the bank can predict they are planning to buy a home. If they also make payments to real estate agencies, the bank can step in with personalized mortgage options, competitive interest rates, or down payment assistance.

By harnessing predictive analysis, banks can meet and exceed customer expectations, leading to increased engagement and, ultimately, higher revenue. According to Deloitte, banks that implement “next-best action” models—proactively offering financial services based on predicted customer needs—experience an average sales increase of approximately 30%. 

Technology solutions for personalized banking

The concept of banking personalization has been around for a while, but it used to be limited to basic tactics like addressing customers by name or offering location-based services. Today, however, the digital and financial landscapes have evolved significantly. A recent survey reveals that 86% of financial institutions consider personalization a priority, with 92% planning to further invest in it. There’s no time to waste—banks that hesitate may find themselves struggling to catch up. 

Still, establishing the technological foundation for personalization solutions may seem lengthy and resource-heavy. However, by leveraging tech advancements, banks can implement solutions that transform their personalization strategies into real value for customers and positive business outcomes. Below, we highlight the ones used most often in the financial sector.

• Big data allows banks to aggregate massive amounts of customer data from multiple sources, including browsing habits, transaction histories, and social media activity.
• Open banking integration enables secure and compliant data sharing between banks and third-party providers, such as fintech and insurance companies.
• AI and ML drive data analytics, allowing banks to extract valuable insights from the information gathered.
• Cloud computing offers the scalability needed to store and process large volumes of data and deploy intelligent software for personalized experiences.

Let’s take a closer look at the top technologies powering personalization in banking.

Behavioral analytics systems

These systems analyze user behavior across multiple touchpoints to create more personalized financial experiences. They process customer locations, website visits, mobile app usage, transaction history, responses to promotions, and support interactions, to name a few. Relying on AI-driven advanced analytics, they can enhance both the bank’s backend processes and customer interactions. For instance:

• Financial health dashboards give customers an in-depth view of their financial activity and personalized recommendations to enhance their economic well-being.
• Credit-scoring platforms enhance a bank’s ability to assess creditworthiness by analyzing customer financial behavior like late payments or spending tendencies.
• In-app smart spending alerts send customers messages when their transactions don’t fit individual patterns (e.g., notifying customers when they’re nearing their monthly spending limit for dining out).

Example

The “Engage” platform demonstrates the successful application of personalization in retail banking. It is the result of a collaboration between KBC Bank of Ireland and Personetics, a fintech provider. The platform analyzes customer financial behavior and sends them tailored recommendations. By using this solution to offer students personalized rewards based on their transaction patterns and preferences, KBC achieved a 30% increase in conversions. 

Smart virtual assistants

Virtual assistants have become commonplace in the financial industry, with even traditional banks implementing basic chatbots for answering frequently asked questions. The adoption is widespread: in 2022 alone, 98 million US customers engaged with banking chatbots, generating an estimated $8 billion in annual savings compared to human agent costs.

However, there’s a significant distinction between basic chatbots and advanced AI-powered assistants. While traditional chatbots follow rigid scripts with limited functionality, smart virtual assistants leverage artificial intelligence to provide truly personalized financial support. They can guide customers through account setup, initiate transfers, recommend personalized investment opportunities, and resolve common issues—all without human intervention.

Example

Erica, Bank of America’s virtual assistant, is an excellent example of mobile banking personalization. Seamlessly integrated into the BofA app, this virtual assistant helps customers track spending, manage payments, and receive financial guidance, making financial management as intuitive as chatting with a friend.

Robotic process automation (RPA)

While traditionally used for back-office automation, RPA solutions can also play a critical role in creating personalized experiences. By handling high-volume, data-driven tasks with precision and speed, they can streamline processes and tailor customer interactions. Examples of banking personalization enabled by RPA include: 

• Automated customer onboarding—customizes the onboarding process based on customer data, ensuring a smoother, more relevant experience.
• Know your customer (KYC)—adapts verification and compliance checks based on customer risk profiles, requiring more details from high-risk individuals.
• Automated loan processing—speeds up approvals by analyzing a wide range of customer data points and offering tailored loan terms.
• Proactive fraud prevention—detects suspicious activity on the account, such as unusual international purchases, and suggests relevant security measures.

Example

Upstart, an AI-driven RPA solution for loan underwriting, assesses creditworthiness using non-traditional factors like employment history, education, and financial behavior. This results in faster approvals and better financial inclusion for borrowers with limited credit histories.

Key challenges of personalization in banking 

Using AI for customer personalization in banking offers unprecedented adaptability to individual needs. However, financial institutions must be ready to face several challenges along the way. The table below provides a brief look at them, along with potential solutions.

Along with technical challenges, there can be adoption issues. Some customers may fear their data is being misused, and some stakeholders within the financial institution may resist personalization strategies due to a lack of understanding. So, it’s essential to take a holistic approach to personalization—implementing the right technology while ensuring clear communication both within and outside the organization.

Neontri: Your partner for banking transformation

At Neontri, we combine deep financial industry knowledge with cutting-edge AI expertise to deliver personalization solutions that drive measurable business outcomes. We have worked with notable Polish banks, including PKO Bank Polski, KIR, and Bank Pekao, creating applications that achieve high customer satisfaction ratings and global recognition. Our team has implemented innovative solutions that have helped our clients increase customer engagement, boost cross-selling opportunities, and streamline operations.

Our banking software development services include:

• Customer data management solutions
• Analytics platforms
• Omnichannel personalization solutions
• Predictive banking capabilities
• Legacy systems modernization 

Contact us today to discover how our AI-powered solutions can help you create meaningful, personalized banking experiences that deliver real business results.

Final thoughts

Banking personalization enables financial institutions to build trust, loyalty, and satisfaction by offering tailored experiences. This leads to a range of benefits, including easier customer retention, improved acquisition, revenue growth, and cost savings.

The first step toward personalization is selecting the right strategy. Banks can tailor offerings to individual needs, provide personalized support and dynamic content, or take it further with predictive analytics for “next-best-action models.” Each strategy requires innovative solutions, including behavioral analytics systems, smart virtual assistants, and RPA software. Naturally, this demands relevant AI expertise.

Ready to transform your bank’s personalization capabilities? Reach out to us for a free discovery call.

Resources

• https://www.upstart.com/
• https://www2.deloitte.com/content/dam/Deloitte/us/Documents/process-and-operations/us-ai-transforming-future-of-banking.pdf
• https://www.emarketer.com/content/banking-customers-want-more-personalization-understand-ai
• https://www.statista.com/statistics/1395183/top-email-marketing-priorities/
• https://www.dynamicyield.com/article/personalizations-exponential-value-financial-services/
• https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/getting-personal-how-banks-can-win-with-consumers
• https://tink.com/banking-report/
• https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-value-of-getting-personalization-right-or-wrong-is-multiplying
• https://engagehub.com/case-study/kbc-bank-ireland/
• https://www.businesswire.com/news/home/20211004005972/en/KBC-Partners-with-Personetics-to-Boost-Digital-Customer-Engagement-and-Financial-Wellness
• https://www.consumerfinance.gov/data-research/research-reports/chatbots-in-consumer-finance/chatbots-in-consumer-finance/
• https://promotions.bankofamerica.com/digitalbanking/mobilebanking/erica