Banks have long sought to leverage artificial intelligence to automate certain elements of the user journeys taking place across their platforms–perhaps most notably, using chatbots assistants to field customer service requests.
But while this automation has driven cost savings for banks, the functionality of such tools has been spotty at best. Based on clunky technology and inefficient usage of static, unstructured data, these chatbots all too often are unable to provide effective assistance or resolutions, leaving customers more frustrated than when they started–a negative user experience that can significantly erode customer satisfaction and loyalty over the long term.
But recent dramatic advances in conversational AI technology, embodied by the much-ballyhooed ChatGPT, hold the promise to drastically improve the functionality of chatbot experiences. By applying cutting-edge machine learning, generative AI and natural language processing, these next-generation chatbots are capable of providing meaningful assistance and contextual, tailored experiences that lead to happier customers who are more deeply and positively engaged with their bank.
In a recent podcast, Galileo Chief Product Officer David Feuer spoke with the Financial Brand’s Jim Marous about three key ways in which advances in AI chatbot technology are enabling banks to solve users’ problems in smarter, more human ways, providing differentiated, next-generation experiences that bolster customer relationships and drive significant long-term value.
Natural language processing for more human interactions.
The evolution of natural language processing (NLP), which has enhanced the ability of AI to understand, interpret and respond to human speech, enables next-generation chatbots to better understand what problem a customer is trying to solve–and, crucially, to glean finer contextual details about that particular customer’s unique situation to provide a more targeted response.
Advanced NLP enables chatbots to “figure out what exactly the customer is trying to figure out, find that out for them, and then tailor the response to where that customer is and who that customer is,” said Feuer.
Such tailored responses are key to engendering a sense of empathy and indicating that customers’ issues are being understood and prioritized–something previous generations of chatbots, marked by impersonal, robotic interactions, often failed to fully convey, leaving customers feeling devalued and under-appreciated, Feuer noted.
Advances in NLP have enabled banks to significantly improve those chatbot experiences by offering insights that can be leveraged to bring a sense of empathy and humanity to those automated interactions, said Feuer. Such positive experiences go a long way toward increasing customer happiness with their bank and driving deeper long-term engagement.
Large language models to generate actionable conversation summaries.
Beyond improving the chatbot-customer interaction itself, advanced AI also can be used after the fact to generate automated summaries of those conversations, which banks subsequently can mine for actionable insights into customers’ needs and sentiments.
“There is an opportunity to use large language models to do the analysis and really figure out how to drive new value (in the form of) conversation summaries which help both the customer and the bank itself.” noted Feuer.
Galileo’s Cyberbank Konecta, an intelligent digital assistant that leverages AI to enable conversational banking interactions, features the capability to generate such automated conversation summaries for banks, Feuer added.
FIs can leverage the valuable data and information contained in these summaries to help improve servicing, address common issues and problems and enhance and deepen customer relationships.
AI for automated insights into customer ‘micro-moments’.
A customer’s pattern of interactions with their bank–including customer service requests–reveals a trove of insight into the current context of that particular user’s financial life–for instance, by identifying if a customer is getting ready to buy a car or make another major purchase.
Identifying those “micro-moments” enables a bank to offer highly relevant products and services tailored to that customer’s unique needs at that specific point in time–and AI can optimize that process via intelligent automation, said Feuer.
In this way, AI can be used to determine “what are the key things to offer that customer based on where that customer is in their micro-moment,” Feuer noted. “If a bank knows, based on two or three interactions, that that customer is getting ready for a specific life event… the bank can then create a customer-sensitive, relevant set of offers.”
In the case of a customer getting ready to buy a car, for example, banks can offer AI-powered recommendations for services–including financing, but also extending to discounts or other offers based on relationships the bank may have with car dealerships or manufacturers, Feuer said.
“We’re using AI to create relevant connections and identify the micro-moments customers are in so that we can… offer those customers relevant products, versus just putting them into a generic experience,” the Galileo CPO added.
And for more insights into how banking’s digital transformation is helping financial institutions enhance customer relationships, stay tuned for future editions, coming soon.
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