Chatting with a computer through a company’s website is not really a new technology. The first chatbot was developed at MIT back in 1966. It was called ELIZA and is considered the mother of all chatbots. The tool used a decision tree to answer simple questions for users without human assistance. Eventually, the technology was adapted for use in automated telephone systems, where it quickly became universally hated by consumers.
But it also saved companies a great deal of money by taking the job of routing calls away from human receptionists and handing it off to automated systems.
Today, simple chatbots can be deployed on a company’s website quite easily, but they still can only answer simple questions that have answers in the computer’s memory – unless, that is, the chatbot is equipped with artificial intelligence (AI).
The rising need for conversational interfaces
In 2013, Xtensifi was tracking 15 important banking initiatives, ranging from opening new accounts via mobile interface to photo bill pay to new loyalty programs. By 2019, the number of critical banking initiatives had been reduced to five.
- Driving new deposits and loan growth
- Integration and open banking
- Security and member authentication
- Data, AI and machine learning
- Conversational interfaces
Why is it important that the bank’s automated systems be capable of serving bank customers without human assistance? Because according to Accenture’s North American Consumer Digital Banking Survey, 47% of consumers are willing to bank using robo-advice. Nearly half of the customers the bank serves are happy talking to a computer.
This is an incredible opportunity for banks, which is why conversational interfaces made it onto this year’s list of top banking initiatives. But there is a caveat. Survey respondents said they would be willing to accept robo-advice. That’s not the same thing as receiving answers to a list of pre-prepared questions.
Consumers want to talk to the computer and have it understand what they say. That goes beyond the capabilities of the traditional chatbot, which brings us back to AI.
Adding artificial intelligence to conversational interfaces
When AI and machine learning are added to a traditional chatbot, it becomes something more. It becomes conversational AI and is capable of actually carrying on a conversation with the user. This means a bank customer can begin soliciting advice from an automated system and take the conversation off topic without the computer losing the customer’s train of thought. These systems can be programmed to deliver information in nearly any format, from printable downloads to website redirects to videos and virtual agents.
Last year, reporters at American Banker predicted that the chatbots in use at the time would evolve into more powerful user interfaces.
Today’s simple question-and-answer programs will evolve, experts say, to become sophisticated conversational agents, which will help customers transact and may even be capable of understanding emotional cues. As that happens, banks expect more and more consumers will turn to chat platforms, such as Facebook Messenger and WhatsApp, to conduct their financial affairs.
They were right and we’re seeing tools in the market now that deliver on these promises, bringing a transformation in customer experience and significantly enhancing their experience by offering anytime support.
But getting these new technologies connected to the bank’s existing platforms and maintaining them is still hard work. You are effectively deploying and maintaining yet another user interface, and not a visual one like the mobile enablement of web banking. It needs to have an understanding of the products and services you offer to handle sales inquiries and general support, access to back office systems to retrieve transactional information such as balances and history, multilingual if your visual offering is multilingual, meet compliance requirements if discussing and/or quoting products, and probably more. Product’s like Alkira’s are a good place to start by ingesting existing content rather than developing new scripts, “skills” and/or integrations.