Personalized banking & AI: How to build a loyal customer base

More than 7 out of 10 consumers expect businesses to provide personalized interactions. And nearly 4 out of 5 get frustrated when this doesn’t happen.

Users crave banking experiences that are extremely tailored to their needs. At this point, default “Hello, [NAME]” homepage message is no longer enough. In the months to come, the key hot topics to shape the banking industry will be AI-fueled hyper-personalization that relies on anticipation of customers’ intent and real-time data capture & analysis.

In this article, I explain what to expect from personalized banking in the future, what forms it might take, and how to implement it in your banking app.

Before we continue, check our mobile banking development services.

What is personalization?

Personalization is about tailoring an experience to a specific person or group of people. The goal of personalization is to make things more relevant and interesting for customers.

Or, we can put it differently: personalization means giving people exactly what they want, how and where they want it, and at the exact time they need it.

(Hyper)-personalization in banking

Recently, a new term has been coined: hyper-personalization. It’s defined as the use of real-time data and advanced technologies like AI and machine learning to provide a highly relevant and personalized experience to each user.

Whether you want to use it or stick to old good personalization is up to you. It’s important to note, though, that what is currently going on in the financial industry, and what I’m referring to in this article, has much more to do with the concept of hyper-personalization (that implies high real-time data analysis and really, really relevant and context-specific experiences) than with “standard” personalization (that often comes down to simple user segmentation or customizing an app’s homepage).

Learn more: What is hyper-personalization?

What do people want from banks?

Before we move on to discuss the benefits of personalization or how to use it in your product, let’s stop for a second to think: What do people actually want from their banking apps? and What should a hyper-personalized bank do?

If you want to successfully implement personalization in a banking app, you first need to understand what it’s really about – and it’s not about sales.

Take a look at the table above. It shows what people would want their banks to provide them with based on Accenture’s research.

Most of them are alerts, tips, updates, advice and are based on… – spending this month, shopping history, etc.

You can clearly see – even though the word “personalized” or “custom” didn’t appear at least once – that customers crave helpful services tailored to their needs with data about their past behavior.

In other words, they want a bank that knows them well-enough it can offer them assistance whenever they need it.

What should a hyper-personalized bank do? Personalized banking characteristics

Let’s go deeper. What personalization really is – and what it’s not? What should personalized banking services be like?

I’ve got three insights that answer just that.

1. An insight from an expertise by Boston Consulting Group:To be sure, personalization in banking is not primarily about selling. It’s about providing service, information, and advice, often on a daily basis or even several times a day. 
2. Kavin Mistry, head of digital marketing and personalization at TSB Bank says in an interview for ZDNET:We want to use AI and ML to identify key events in the customer’s life that might necessitate financial support and use that response to help customers ultimately achieve their life ambitions.
3. Samantha Searle, director analyst at Gartner, in a video-conference for ZDNET, explains that personalized banking initiatives should do two things:
   1. Firstly, a hyper-personalized banking service should assist customers in achieving their financial objectives, such as saving for a down payment on a house or managing their budget more effectively.
   2. Secondly, such a service should focus on a customer’s life stages and provide support during major life events, such as marriage. This might include providing information on relevant financial products like mortgage options or home and life insurance.

Again, the unifying factor is help, support, and advice. Personalized banking helps customers achieve their goals, whatever they are. It’s not about selling; it’s about creating a banking experience so custom and farseeing, and thus so good, users simply want to keep using it (and then – they want to buy what banks sell). A win-win scenario.

To sum up, personalized banking solutions are:

• Predictive – they anticipate the needs and intents customers have or might have in the near future based on their previous and current actions.
• Relevant – non-generic, closely relating to a customer’s individual context.
• Useful – they help users achieve their goals.
• Timely – they address the current situation of a user.

Benefits of personalized banking

The benefits that come with customization – for both users and bank business owners – are numerous. Let’s start with a few personalization statistics.

• 80% of survey participants mentioned they are more inclined to engage with a company that provides personalized experiences, while 90% stated they find personalization attractive. (Epsilon)
• 76% of customers are more likely to choose a bank that offers personalization in financial services, and 71% already expect it as a standard. (TSB)
• For every $100 billion in assets a bank possesses, personalizing customer interactions can lead to an increase in revenue of as much as $300 million. (BSG)
• Companies experiencing faster growth generate 40 percent more of their revenue from personalization compared to those with slower growth rates. (McKinsey)
• 64% of Gen Z express a desire for personalized banking experiences that include product and service recommendations tailored to their specific financial situation. (W1TTY)

Research proves there is a real need for personalized customer experiences, and this trend will continue with future generations, catering to Gen Z’s banking needs.

That’s because tailored financial services have 4 main benefits:

• Enhanced loyalty and satisfaction: Personalized experiences allow banks to cater to specific needs and preferences, and customer service is improved. Better experiences equal happy customers, and happy customers equal loyal customers.
• Increased revenue: Highly relevant recommendations translate to more sales. 78% of consumers that get personalized messages are more likely to buy from a brand again. (McKinsey)
• Improved customer retention: Customers with personalized banking experiences are more likely to stick with their bank.
• New market opportunities: Personalized offerings can attract traditionally underserved communities (financial inclusion.) Let’s take the US communities of people of color, for example. McKinsey’s research shows they often face more challenges in accessing financial services than other Americans, including less access to banks and lower approval rates for financial products. By using broader data sets and personalizing financial products to serve these minority groups, banks can not only include more people in the economy, but also enter new (less competitive) markets.

Personalized banking strategies. How to implement personalized finance

We’ve established what personalization in digital banking is and why it’s beneficial. Now let’s move on to discuss what forms it might take in your banking app.

Examples of personalization in banking

Here are two practical examples of how personalized banking can address specific customer pain points.

Scenario 1: Overdraft fees

• Pain point: Sarah, a college student, keeps accidentally incurring overdraft fees due to forgetting about upcoming bills and keeping a low balance.
• Personalized banking solution: Sarah’s bank analyzes her spending habits and notices a pattern of overdrafts around the time her phone bill is due. The bank can:
  • Proactively send Sarah a notification a few days before the due date reminding her about the upcoming bill and her current balance.
  • Offer a small, personalized overdraft buffer (say, $10-$20) to cover the bill if her balance falls short, avoiding the overdraft fee.
  • Recommend a budgeting tool to help Sarah better track her finances and avoid future overdrafts.

Scenario 2: Saving for a goal

• Pain point: John wants to save up for a down payment on a house but finds it difficult to stay motivated and on track.
• Personalized banking solution: John’s bank uses his financial data to see he has a consistent income but struggles with saving. The bank can:
  • Develop a personalized savings plan with John, recommending a specific amount to save each month based on his income and house price goals.
  • Set up automatic transfers from John’s checking to his savings account, ensuring he reaches his goals.
  • Track John’s progress visually through the banking app, showing him how much closer he gets to his target each month. (BTW, progress bars are a one of the most prominent examples of gamification in banking apps).

Banking personalization. Types and real-life use cases

That’s for the theory. But how are actual banks implementing personalization in their products? What are industry insiders saying about future trends?

Personalized recommendations & product offers

Personalized messages within a banking app can serve as a great way of product or service suggestion. Personalization paid off for TSB – it resulted with a 300% increase in leads:

We were on a mission to prove the concept and the value of the product. So, we focused on meeting customer needs. The first personalised communication that we did was around loans. Instead of generic information in a banner in an email around the amount a customer could borrow, we provided a realistic amount each individual customer could have. (source)

TSB also launched a credit card communication to help customers avoid unnecessary interest rate payments:

We’re giving them guided experiences to set up a direct debit to pay off their balance regularly. So, we’ve not only launched the communication and data that sits behind it, but also a personalized experience. And one in 10 customers that we’ve sent the communication to have now set up a direct debit. (source)

Personalized marketing in-app communication

Interestingly, the communication can get really personal – to the point when you banks group customers by interests to enable more human-like experience with their banking apps. William Trout, director of securities and investment at the consultancy Datos Insights, said for The Financial Brand:

It’s becoming more like a service concierge based on customer profiles and grouping customers as part of an affinity groups, like health enthusiasts or sports fans, and marketing to them appropriately,” […] “It’s gotten really tactical.” […] The secret sauce is to enable AI to have the capability to find the insights, and for that, you need robust data integrations.

Customer service

Banks are embracing AI to transform customer service. Take Erica, Bank of America’s virtual assistant, for example (as highlighted by The Banker). Erica analyzes your account information, past transactions, spending habits, and even alerts you to potential issues. This allows for personalized conversations, proactive assistance, and even predictive insights to help you manage your finances better.

Monzo, a UK challenger bank, takes a different approach. They analyze user behavior to identify frequently encountered issues. This data empowers their customer service team with the knowledge and tools to directly resolve over 85% of daily inquiries, streamlining the process for everyone.

Another example might be the use of conversational AI (AI-fueled chatbots) during digital customer onboarding. Here an example would be Lemonade Insurance. The digital onboarding process is all about answering Maya AI’s questions one by one, which makes the process feel more personalized and human-like (see screenshots above).

Beyond tailoring interactions, personalization fosters seamless user journeys across all touchpoints – from intelligent devices and mobile apps to web banking and even physical branches. This omnichannel experience is one of the 5 key traits of an AI-first bank. Imagine this: you encounter an issue in the app. Switching to the call center for help becomes effortless. The representatives, empowered by real-time data, are already aware of the problem you’re facing, ensuring a smooth and efficient resolution.

Banking personalization features

Going further in detail, let’s list a few personalization features you might want to have in your banking app.

• Personalized offers
• Personal management tools (expense trackers that show spending and savings patterns)
• Offers/perks based on shopping history
• Upcoming direct debits or overdraft alerts
• Saving tips based on spending patterns
• Budgeting information or educational materials based on spending this month
• Account balance updates
• Personalized advice for sustainable shopping, traveling
• Chatbot to explain financial terms in plain language
• Gamification features (saving progress bards, badges, etc.)

Learn more: The most sought-after mobile banking app features for 2024

Technologies for personalized banking

That’s for what you can do in your banking app. But HOW will you do it? What do you need to provide customers with personalized experiences?

The three core technology elements banks need to deliver personalized financial services are: AI (machine learning + deep learning), Big Data, and cloud computing. You can learn more about how to implement them into your solution from our guide on building AI software.

Artificial intelligence

AI allows banks to analyze vast amounts of customer data, identify patterns and predict customer needs. Now, whether you want to use deep learning or machine learning for that depends on the data you have, as explained in this whitepaper by McKinsey.

Deep learning

Unlike traditional methods, deep learning can handle complex, unorganized data like photos, articles, and even handwriting. With enough data, it can outperform older approaches in tasks like recognizing objects in images. Once trained, the network can apply its knowledge to analyze new data. For instance, after learning what a cat looks like, it can identify a cat regardless of its position in a new picture.

While traditional machine learning needs perfect data, deep learning is much more versatile. It can handle raw information, whether it’s organized or not, and even improve its predictions as it’s used by more people and applied to more things. This makes deep learning particularly useful for suggesting the next product a customer might buy, with a level of accuracy that surpasses other methods.

Deep learning vs. machine learning

However, it doesn’t make deep learning a perfect solution. It shines when there’s a lot of data, especially unstructured data, because it can handle the complexity without a lot of manual prep work. In these situations, it often outperforms machine learning. However, when data is scarce, machine learning can be more effective.

While machine learning might require building individual models for each product, which isn’t always feasible, it can sometimes provide more accurate results, especially for specific analyses. The key is to choose the right tool for the job.

Big Data

The massive datasets that banks collect about their customers. Big data provides the raw material for AI to work its magic. It might include everything from account balances and spending habits to savings goals and investment preferences.

Cloud

Cloud computing allows banks to source data from multiple places, and store and process it efficiently. Cloud-based systems can also scale up or down as needed, making it easier for banks to handle the ever-growing volume of customer data.

Challenges

Data privacy, instances of data theft and breaches, and data silos – these are typical challenges associated with processing big amounts of personal data. I’ve talked more about the most common threats that prevent banks from deploying AI technologies in my article about AI as the future of banking. If you’d like to know how AI technologies are used to solve these challenges, check out our guide to RegTech.

Now, let’s focus on two less obvious problems you might encounter when implementing personalization in your banking app.

Access to data

Dealing with banking information is one thing, but to analyze customer data, you first need to get it. And to get it, you need consent. Leslie Gillin, ex-CMO at JPMorgan and current CGO at Pagaya shared her insight with The Financial Brand.

She estimates that around 35% to 40% of Americans are willing to share their financial data. This trend is expected to grow, with companies likely asking for customer consent to share data during regular transactions. Some leading companies, like American Express, are already following this approach.

UX

Personalizing banking apps can be tricky. While users crave relevant information, overloading them with options or irrelevant personalized details can clutter the interface.

The key is to strike a balance between customization and a clean, simple design that highlights the most useful features for each user at the right time.

Incorporating personalization into a mobile app that makes sense from the UX perspective is a tough task – and I’m not even touching the subject of omnichannel, physical-digital customer journey.

Personalization in banking. Conclusions

In the future, banking is expected to become hyper-personalized, using real-time data and AI to anticipate customer needs and provide custom advice.

This will be a major shift from the current one-size-fits-all approach. I hope this article helped you better understand this important trend.

Personalized banking apps. Development services

Need help developing a hyper-personalized banking app? Or, maybe you want to design and implement personalization features into an existing product?

We can help with both. Check our mobile banking development services or reach out to us right now.