As seen in the chart above, the first three benefits of transformation are internal, but they all add up to better customer service and speedier resolutions.
3. Banks Are Understanding the Benefits of Chatbots
A chatbot is the best channel for answering customers’ simple and routine requests (knowing account balance, when a credit card bill is due, how to change an address, etc.). When bots are used wisely, they reduce support requests and improve team efficiency.
Here are a few benefits of chatbots:
- 24×7 availability.
- Interactions that are like a conversation.
- In-app chatbots can access user account details
The AI assistant applied by Swedbank, known as Nina, delivers an intuitive, automated experience using voice or text. As reported by the bank, Nina bot directly resolves 81% of the 40,000 conversations it handles each month.
4. A Strong Banking CX Strategy Must Be Omnichannel
Superior customer service is about delivering the same quality of service across all channels, both online and offline. Omnichannel banking platforms allow real-time data synchronization between different channels. For instance, customers can start the onboarding process with one channel and finish it with another, without the need to provide the same data repeatedly.
5. Improving the Banking Customer Journey
Journey mapping will help answer these key questions:
- To what extent is the current customer experience meeting customer expectations?
- Which areas need improvement?
- What new and inventive experiences could set my bank apart?
Customer needs, motivations, actions, and barriers to action should be considered at each stage of the customer journey. What motivated that person to perform that action for instance? What would motivate them to move to the next stage of the journey? What obstacles might they face?
Understanding your customer journey is essential to delivering an excellent experience in banking.
6. Improved Banking CX Requires Making Use of Data and Analytics
Data is undoubtedly the basis for any personalized experience—not only within the financial services industry. The better the quality and the higher the quantity of relevant data, the more personalized the communication and the more targeted a service can be offered.
One important analytics use case is the experience provided by Personal Financial Management (PFM) solutions. By classifying account transactions into buckets, PFM solutions use consumer history, attitude, and behavioral data to provide personalized financial advice. But collecting, retrieving and keeping data reliable and useful is a continuous challenge.