ChatGPT in banking: Balancing its promise and its risks

ChatGPT and other large language artificial intelligence models have extensive implications both good and bad for the future of banking. Technology forecaster Brian Roemmele makes a strong case for how generative AI can improve customer service — but also suggests ways to avoid potential pitfalls of this rapidly evolving technology.

The banking industry is in the very early days of exploring how generative AI models like ChatGPT can be applied to transform financial services. Many institutions are beginning to run small-scale pilot projects or proofs of concept to evaluate potential use cases in customer experience enhancements, back-office automation, risk assessment and fraud detection as well as product innovation. While generative AI offers benefits, financial institutions must also navigate challenges, minimizing potential flaws of this nascent technology.

To gain insightful commentary on both the tremendous potential benefits as well as inherent risks new AI capabilities could bring to banks and credit unions, we conducted a two-part interview with Brian Roemmele, a prominent thought leader and expert on digital innovation and emerging technologies, for the Banking Transformed podcast. He offered a balanced perspective on how financial institutions can embrace the upside of generative AI like ChatGPT while also carefully mitigating downside risks.

Enhancing customer experiences with personalized AI

A major opportunity Roemmele highlighted during the interview is using ChatGPT and similar models to provide hyper-personalized customer service and advice. “Banking is absolutely ripe for conversational interfaces,” says Roemmele. “And what we’re seeing with some of these large language models is the ability to really create conversational experiences between consumers, small businesses and financial institutions.”


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