Using only data you add to a dataset to train an AI-powered chatbot increases the chances a customer service chatbot will offer accurate and helpful answers.
For many, financial transactions, even just paying routine bills, are stressful. Service providers in the electronic bill payment and presentment (EBPP) space are well acquainted with this tension; optimizing and streamlining customer service to mitigate that stress is our constant focus. The truth is, better, more efficient, and more intuitive customer service options benefit both users and those of us serving them: They allow issues to be quickly addressed, alleviating user anxiety while also giving customer support teams increased time and resources to assist with more complicated or time-consuming inquiries.
Artificial Intelligence (AI) offers a host of potential solutions for this problem space. While there has been plenty of speculation about the plethora of proposed use cases for AI across industries, chatbots are already a well-established application. Now, with shrewd, legally compliant applications in EBPP, chatbots could help people pay their bills more quickly—and with less stress—than ever before.
Simplifying responses to biller inquiries
Any new technology can overwhelm users unfamiliar with its features, and EBPP platforms are no different. While the purpose of EBPP technology is to significantly streamline and simplify organizations’ billing processes, their features may initially intimidate those who are implementing them for the first time. Many organizations in the tax, insurance, and utilities sectors have had specific standard operating procedures for so long that change can make them anxious—even if that change is towards something easier. Introducing new tools and approaches to business problems or processes can be intimidating, even if those tools are set to ultimately lighten team members’ workloads and increase customer satisfaction.
The reality is that even some of the most apparently vexing biller conundrums are quite common and have relatively simple solutions that can be easily described by customer service chatbots augmented with AI. With the right keywords, chatbots can even be trained to understand what kind of issue a biller is having, even if the biller doesn’t necessarily understand themselves. In these situations, AI can do what would have taken an hour or more of a human customer service representative’s time in the blink of an eye.
See also: State of AI in the Financial Services Industry Going into 2024
Increasing self-service
When it comes to customer service, people’s preferences vary. While some people prefer to be helped along every step of the way by a human rep, others prefer to navigate things for themselves as much as possible. Self-service customer interactions can increase convenience and simplify responses to biller inquiries. According to Gartner, self-service options are becoming increasingly valuable as technology evolves and customers’ expectations of digital options rise. Implementing a chatbot powered by AI can help offer customers a tailored experience that can range from completely self-service to conversation-based, depending on individual taste.
When self-service options are expanded and improved via AI augmentation, it’s also possible that the number of customers defaulting to these options will increase, especially as the interaction becomes more human-like. This means they can address issues on their own timelines when it’s convenient for them rather than having to align their schedules with that of an organization’s customer service department. Because AI can iterate in real time based on customer data, these tools can also personalize the service offered, which is shown to boost the user experience when executed well, based on research by McKinsey.
See also: Financials Ramp Up Services with Hybrid Real-Time Apps
Private data sets
Some of the most significant concerns of AI use in the EBPP space are, understandably, that of security and privacy. Luckily, there are steps that can help protect consumer information while still allowing generative AI to provide customer service benefits. Publicly available tools pull from datasets consisting of unfathomable amounts of information gleaned from all over the internet. Any time you interact with one of these tools, you may be adding information to its training dataset, from which it draws indiscriminately. If people are going to have conversations with a chatbot that involve sensitive information like credit card and bank account numbers, a proprietary, privately managed database can help prevent that information from being made available to the wider internet.
Fortunately, as described in the Harvard Business Review, companies can build their own databases with which to train their AI tools and improve the model. This is also helpful in ensuring that the guidance offered by these bots is accurate and effective. Just as you might worry about your customers’ sensitive information being absorbed into an AI chatbot’s database, you may also be concerned about the other information in its database with which it might present your consumer. By creating a proprietary AI-powered chatbot that is trained on only the information you add to its dataset, you can increase the chances that a customer service bot will offer accurate and helpful answers based on your organization’s existing literature. As customers and businesses explore AI, including chatbots, privacy principles should be paramount. Exploring best practices regarding using personal information is a starting place for implementation and usage.
Understanding AI’s limitations
It’s important to remember that while there are many promising opportunities for AI use when it comes to customer service, there are also other helpful technologies organizations can consider implementing, either on their own or in concert with AI-powered solutions. Many automations can streamline customer service and run without AI, such as a chatbot delivering links to specific articles in an organization’s help center, in response to answers from a short survey. However, if a company would rather have a customer service bot that can summarize the relevant portions of the article in a way that makes it easy for the customer to understand, then AI can be a potent choice.
If an organization does choose to implement AI-augmented customer service, offering clear labeling to make customers aware they’re interacting with artificial intelligence can prevent confusion. It can also help those seeking assistance understand when it may be time to escalate their query to a human representative. While AI advancements continue to impress, and chatbots are already streamlining customer service, there will always be a need for a human touch.
