Where Are Banks Using AI?

AI in Banking

Artificial intelligence (AI) is hot right now. Especially after the late 2022 launch of ChatGPT, the AI-powered chatbot from OpenAI, every industry is thinking about how this technology can be used to enhance experiences and efficiencies, and banking is no exception. But where and how exactly can financial institutions leverage AI? According to NVIDIA’s recent State of AI in Financial Services report, there are a slew of use cases these organizations have for AI across customer experience and internal functions, and at the top of the list are natural language processing (NLP), recommender systems, and portfolio optimization.

A big takeaway from this dataset is that two out of three of the top use cases speak directly to enhancements that can be made to the customer experience. While there are certainly many ways to leverage AI behind the scenes (fraud detection, for example, ranked quite high, as well) that NLP and recommender systems are sitting together at the top suggests a meaningful focus on how to use AI to better engage with customers. ChatGPT, for instance, is widely considered to represent a major leap forward in the world of NLP, and its ability to demonstrate how customers might interact with a machine capable of responding like a human has gotten a lot of people excited about the future of customer service. (As we discuss in our January 2022 report on AI in banking, improving customer service through the use of AI-powered chatbots is not only one of the most promising applications of AI in the industry but also one of the most accessible.) Meanwhile, using AI to power recommender systems or next-best action offers the ability to create stickiness more accurately and seamlessly for customers.

The use of AI to reimagine the customer experience is coming for sure. And it makes a ton of sense, particularly in the current environment. The advent of ChatGPT is leading to a flurry of activity (and competition) and will likely give rise to a new wave of AI startups that look to build on the foundations laid by this technology. That, in turn, will probably bring advanced NLP even more into the spotlight, in financial services and elsewhere. Even beyond the use cases above, we could begin to see this technology used in more advanced areas like financial advice or even onboarding flows. It is an exciting time, but it’s also one that is likely filled with uncertainty, especially in the banking world where data privacy and compliance are so important. We’ve already seen examples of how ChatGPT can be used in nefarious ways — like in malware, for instance. As a result of this, it’s important to remember not to get overly excited. Yes, there is opportunity. But there is still a long way to go before these systems are finetuned and capable of being used at scale. Ultimately, while AI has a lot of promise, this is very much the beginning of the beginning.