In an uncertain economy, banking customers want clear guidance and familiarity from their financial institution — and they’re not afraid to move their money if they’re not satisfied. Improved customer service in banking should be your focus, as people have grown to expect easy digital services and personalised support from their bank. AI can help you meet those expectations – anytime, anywhere, and on customers’ preferred channels.
In the last year, we found that 25% of customers switched banks, and 39% of those who switched did so due to poor customer service. Customers want to feel like their needs come first, and banks that can deliver will come out on top.
How can banks offer a more personal touch? This is where AI can help. While you already may use predictive AI in customer churn prediction, ticket routing, credit scoring, and fraud detection, generative AI can help create new content that greatly improves customer service experiences.
Service trends in financial services
Find out how financial service professionals around the world are responding to macro trends such as the shift to automation and omni-channel experience.
Banking use cases for generative AI
You can prompt generative AI to help create emails, service replies in chat, and knowledge articles that make it easier to offer more relevant and personalised service. The technology understands natural language, so customers can use their own words and language to communicate with chatbots that sound human.
Because generative AI can read and understand text, video, and sound, it can identify and summarise action items and insights from conversations, transcripts, and recordings to assist contact centre agents.
Generative AI can help you improve and grow your customer service experiences, from no-touch interactions like self-service help with chatbots to high-touch situations like working through complex issues in a branch visit.
When using this technology, your top priority should be better serving your customers’ needs in order to meet your fiduciary responsibility. Last month, for example, the Securities and Exchange Commission (SEC) in the United States proposed updating rules and regulations requiring wealth management firms to supervise AI technology, such as automated replies produced by generative AI. Future proposed regulations could lie ahead for all of financial services, so banking leaders should proactively think about how to manage the risks associated with using this technology.
By combining your trusted customer data with AI, you can transform customer service in banking to improve the customer experience and boost loyalty.
AI can help you deliver personalised customer service in banking
Our research found 63% of service professionals say generative AI will help them serve their customers faster, saving them over four hours weekly (or nearly one month per year).
Drawing from your trusted customer data, generative AI can automatically generate relevant content, such as action summaries and service replies. It helps agents find answers to known questions and issues, surfacing content from your knowledge base articles so they don’t start from scratch with each new caller. This makes your agents more efficient, allowing them to focus on more complicated cases.
And it’s not just helpful for service inquiries. AI can look at customer data, preferences, transaction history, and customer service logs to generate new offers, recommend next steps, or provide proactive assistance for customers’ specific questions or issues, regardless of how they communicate.
For example, if a customer is getting married and asks about opening a shared account, generative AI can create a suggested reply for an agent that includes details specific to the customer’s finances, while also triggering a followup email to the client with relevant offers for newlyweds. These highly personalised recommendations are possible because AI uses customer data to create content that’s better matched to real-time customer needs, improving customer engagement and loyalty.
Make self-service tools easy to use and effective
We found 81% of people try to solve a problem themselves with self-service tools like chatbots or how-to articles before seeking support. Self-service options save both customers and banks time and effort, making for quick, in-and-out interactions, but bots can be very impersonal if not set up right.
Self-service tools must be easy to use and integrated well with your platform. When customers use these tools for simple banking transactions, you can use that data to better serve them in the future. While you should focus on making these tools intuitive and simple, you also need to make sure these services feel empathetic and personalised, which helps to build trust with your customers.
Unfortunately, 59% of consumers say it often feels like they are dealing with separate departments, not one company. And 52% of customers describe most service interactions as fragmented. Customers want their banks to have a holistic view of their relationship, so they can avoid repeating their story or starting at square one when moving across service teams, channels, and departments.
AI can significantly improve and scale customer service in banking with better self-service tools that handle more of your customers’ questions. AI-powered self-service enables banks to resolve high volumes of inquiries more efficiently, enhancing customer satisfaction and reducing operational costs.
And using AI alongside the trusted data in your CRM system allows you to quickly analyse customer behaviour patterns to anticipate what they’ll need next. For example, if a customer frequently transfers funds between accounts, the system can provide shortcuts to reach the next step. Or at the start of a session, it could automatically offer a short list of the customer’s most frequent tasks to save time.
This helps customers resolve issues and accomplish tasks quickly, providing full access to personalised services, showing them savings opportunities, and proactively recommending services that support their financial wellbeing.
Use your data to offer proactive recommendations
Banking customers want to feel like you know, remember, and value them. But only 37% of customers say their bank anticipates their needs. That’s concerning, because half of those we surveyed said they would switch banks if service felt impersonal. AI algorithms can help you anticipate customer needs and automate outreach — even before customers turn to you.
For example, predictive AI can identify patterns, then alert bank staff to potential customer needs. Maybe it recognises a customer building up their savings account and frequently checking their credit score. This could indicate they are planning to make a purchase that requires lending services. A personal banker then could use generative AI to reach out to the customer with a personalised loan offer tailored to their finances.
Similarly, predictive AI can alert your team to event triggers, such as a customer’s fixed deposit reaching maturity. Then generative AI can help you meet that customer at the right moment, generating a package of reinvestment options for their unique circumstances. That’s what people want from customer service in banking.
Eventually, AI will make personalised financial planning more accessible for all banking customers, no matter their wealth. By analysing the vast amounts of data you already have, the algorithm can offer personalised recommendations tailored to every customer’s financial goals. This will revolutionise the way financial advice is delivered, making it more accessible and relevant to the broadest range of banking customers.
Use AI to take customer service in banking to the next level
Despite improving digital services and capabilities, many banks find it difficult to win the loyalty of their customers. Customer service could make the difference, helping the customer feel known and valued by offering empathetic, personalised care.
Still, you will need to think about how you’ll supervise AI usage. Choosing the right technology platform is key, and you should look for solutions with built-in compliance and transparency features for protection and control. These might include audit trails for record-keeping, automatic hand-off to humans for decision-making, and transparency in data usage for recommendations.
For banks to build trust with their customers, they must get to know them throughout the journey. To do this at scale, AI can help you connect with customers, addressing their needs and showing you care about their needs today and in the future.
What do your customers want most?
We asked thousands of customers what they expect from their financial institutions and what is most important to them. Our latest report can help you take your company to the next level.