The idea of a credit card came from someone being embarrassed that they had forgotten their wallet at a restaurant in Manhattan. In 1950, a fellow named Frank McNamara had to wait for hours for his wife to drive from the suburbs to hand him some cash to pay for his meal. He shared the incident with his friend, Ralph Schneider, and the lightbulb then went off about a way for people to pay for their meals at a later time. The two then created a cardboard “credit identification card” that people could use to charge meals eaten at participating restaurants, to be settled up at the end of the month. Payments have been evolving ever since the world’s first credit card, and now, with generative AI, the payments ecosystem will get a whole new boost.Financial institutions have leveraged AI for years, mainly in the form of machine learning — using algorithms to discern patterns within vast amounts of historical data to then make sense of new data. But with the advent of generative AI and “large language models,” financial institutions can move from just predicting tasks to be done to creating entirely new content.“The payments industry evolves in waves,” and with generative AI, “it is going to be a bigger wave than we’ve seen before,” says Tony Craddock, director general of the EU trade group, the Payments Association.
AI-Driven Enhancements in Banking ServicesGenerative AI is revolutionizing customer interactions in banking. From personalized insights to proactive spending alerts and enhanced ecommerce experiences, these technologies are transforming how financial institutions engage with their customers. Here are three ways that you can leverage generative AI for payments with your customers:
AI-Driven Enhancements in Banking ServicesGenerative AI is revolutionizing customer interactions in banking. From personalized insights to proactive spending alerts and enhanced ecommerce experiences, these technologies are transforming how financial institutions engage with their customers. Here are three ways that you can leverage generative AI for payments with your customers:
- Chat-based payment trend insights for customers. Institutions can infuse generative AI within their virtual assistants to provide customers with more personalized, conversational interactions for better customer service — including providing them with more insights about their payment data. Customers could ask chatbots about which categories they are spending more money on compared to the year before, and the chatbot could then answer in more everyday language and provide details beyond the pre-set data analysis features of most mobile financial apps today.
- AI-powered spending alerts. Such chatbots could also be more proactive and alert customers when they are going over their budget — using natural language in a manner that would be more receptive to the customer. “Intelligent spending advice could remind consumers how much of their budget they’ve spent in areas such as dining or retail, so they can adjust their spending habits accordingly,” says Manuela Veloso, head of AI research at JPMorgan Chase & Co.
- AI for ecommerce. Retailers and other brands are now using generative AI-powered chatbots to let customers know when items within their wish lists are in stock or on sale. The chatbot sends them secure payment links in the WhatsApp chat to purchase the items on the brand’s site. Now brands are allowing customers to save payment details from their financial institution within the chatbot, using card tokenization so that customers can pay directly in WhatsApp. For example, the generative AI-powered chatbot could ask: “Hi, you have left an item in your shopping cart. Would you like to pay for it now using your card ending in 1395, YES OR NO?” If they answer YES, their card will be charged automatically.
Enhancing Internal Operations with Generative AIGenerative AI can also be leveraged internally across your organization. The new tool can help not only with workplace efficiency, but also help alleviate your staff’s stress in challenging customer service situations. Here are two examples of how you might use generative AI for back-office purposes:
- A copilot for staffers. Inside the organization, generative AI can be deployed as a co-pilot to aid staffers in the kinds of tasks typically delegated to a personal assistant, like summarizing meetings about extremely technical subjects that the staffer couldn’t attend.
- Helping call center employees solve difficult problems. Generative AI can quickly summarize the FI’s policies and procedures and provide answers in natural language, to take off unnecessary stress for the call center employee. Some FIs are also using generative AI to detect when an employee is beginning to “lose it” with an overly irate customer, and then send the employee a relaxing video montage of photos of their family set to music to help them “reset” so they can better handle the customer’s issues.
The payments industry is undergoing a significant transformation with the advent of generative AI, surpassing the innovations brought by traditional machine learning. Generative AI allows financial institutions to provide more personalized and conversational customer service through AI-powered chatbots, offering insights and proactive spending advice. Additionally, these chatbots can facilitate chat-based commerce by enabling secure and convenient payment options within messaging apps. Internally, generative AI can provide meeting summaries, stress-relief resources, and more. By leveraging generative AI, financial institutions can enhance both the customer experience and operational efficiency.
