November 18, 2022
Customer experience

Successful CX Strategies: Scaling Customer Service With Conversational AI

How chatbots are helping Nordic banks lead the way in customer engagement

As customer service increasingly becomes a key differentiator for businesses, more and more organizations are looking to use artificial intelligence (AI) to scale their customer service operations. 

At the recent Customer Engagement Summit in London,’s Chief Delivery Officer, Håvard Dhal-Olsen, sat down with Jan Thomas Lerstein, Head of Emerging Technologies at DNB to discuss what separates the customer engagement of Nordic banks from that of UK or European banks. He also highlighted some of the challenges that banks face and how conversational AI can help to overcome them. Here are some key takeaways from their conversation.

What sets Nordic banks apart?

Nordic banks, including DNB, are ahead of the curve when it comes to customer engagement. This is primarily due to the fact that they have a largely digital customer base. According to Lerstein, 95% of DNB's customers are self-service. This allows the bank to focus its resources on providing a high level of customer service, rather than on handling simple inquiries that could be easily automated.

Another factor that sets Nordic banks apart is their use of chat as a customer service channel. In the Nordics, chat is more widely used than phone & e-mail channels. This is due in part to the fact that customers expect 24/7 access to their bank. By using chat, banks are able to provide this access without having to staff their call center 24 hours a day. 

Lerstein also cites the low turnover in service centers as a key difference between Nordic and UK/European banks. Service center employees in the Nordics tend to be more highly skilled and have a higher level of competence than those in other parts of Europe. However, this comes at a cost; the high level of competence required by service center employees means that they are more expensive to hire and train.

What challenges do banks face?

One of the most common challenges banks face when it comes to customer engagement is increasing traffic levels. As more and more people turn to online banking, banks are struggling to keep up with customer demand. This often leads to long queues and extended wait times for customers trying to reach customer service representatives. 

Similarly, today's consumers expect around-the-clock access to their bank, regardless of time zone differences. This poses a challenge for banks, which must either staff their call center 24 hours a day or find another way to provide this level of service. 

The final challenge Lerstein discussed is the dominance of FAQs in customer inquiries. Due to the large number of online banking options available, customers often have general questions that, while easy to solve, still take time to do so. As a result, FAQs make up a large proportion of incoming inquiries at many banks, leading to congested phone lines and live chat queues.

How conversational AI can help

Conversational AI has the potential to solve many of the customer service challenges faced by banks today. By automating FAQs, conversational AI can help reduce wait times for customers trying to reach a human representative.

Additionally, conversational AI can provide 24/7 access to customer service, regardless of a bank’s opening hours. Finally, conversational AI can help free up resources so that banks can focus on providing high-quality customer service rather than on handling simple inquiries.

DNB’s conversational AI journey

Lerstein noted that when DNB initially launched its customer-facing chatbot, Aino, it operated at a 90% automation rate after just a few months. This turned out to be too much of a good thing, and the bank dialed it back in order to find the right balance between CSAT and automation.

Chatbots are most effective when used in conjunction with human customer service representatives, rather than as a replacement for them. If you look at the most successful implementations of conversational AI, they all have humans in the loop at some stage.

DNB employs a chat-first approach with conversational AI, placing Aino as the primary point of contact for customers interacting with the bank but still makes it easy for customers to speak to a human when necessary. This has resulted in the chatbot automating 20% of total customer service traffic across all channels including phone and e-mail.

Additionally, DNB also has four other virtual agents deployed to assist employees with everything from HR to legal queries, effectively scaling conversational AI within its own organization to increase operational efficiency. Starting with a chatbot as 2nd-line support is often a great entry in introducing conversational AI into the wider organization, particularly in markets where the technology is not yet mainstream.

Banks (and businesses in general) are under constant pressure to improve customer service while reducing costs. Concierge-style customer service is simply not sustainable in today’s digital world without the help of technology. By using conversational AI, companies across industries can provide better customer service at a lower cost than traditional call center operations. And as chatbots become more intelligent over time, they will only become more valuable as they take on an increasingly larger number of tasks within customer service.

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