Large Artificial Intelligence models in banking: balancing the promise and the risks. The topic will be analyzed by experts only at Banking 4.0.
ChatGPT and other large language artificial intelligence models have extensive implications both good and bad for the future of banking. Generative AI can improve customer service, but banks must be extremely careful to avoid the potential pitfalls of this rapidly evolving technology. The topic will be analyzed by experts only at Banking 4.0.
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, The Financial Brand 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.”
Roemmele envisions banks training individual AI models for each customer using their personal financial data and transaction history. Over time, these “personal banker bots” could gain deep insights into every customer’s unique circumstances to offer tailored recommendations on budgeting, investing, retirement planning and other financial challenges.
“Imagine a scenario with a financial institution where you’re talking to an interface that can understand your particular financial picture, make recommendations on how to allocate funds, think about planning for retirement or buying a house. Those types of conversational interfaces are coming.” — Brian Roemmele.
The power of this technology is that the more the AI interacts with a specific customer over time, the more personalized it can become at understanding their preferences and tailoring recommendations. This stands in contrast to the often rigid and repetitive scripted conversations with current non-AI chatbots.
“If you do it with care and you do it with dignity and permission by offering value to the client, by understanding more of the dimension of the milestones in life that that client is going through, your ability to finely tether an output is phenomenal,” states Roemmele.
An added benefit of conversational AI is that, when customers do need help, AI agents can provide rapid answers by quickly parsing questions and referencing vast knowledge bases rather than making customers wait on hold for the next available human agent. Generative AI also provides value by proactively offering personalized product recommendations, money-saving tips and basic financial planning or investment guidance tailored specifically to each customer’s risk tolerance, time horizon, current holdings and other factors.
Finally, as Roemmele explains, by continuously analyzing previous interactions, AI chatbots can assess customer sentiment, identify pain points, and loop in human agents as required.
Listen to parts 1 and 2 of the podcast with Brian Roemmele:
Anders Olofsson – former Head of Payments Finastra
Banking 4.0 – „how was the experience for you”
„So many people are coming here to Bucharest, people that I see and interact on linkedin and now I get the change to meet them in person. It was like being to the Football World Cup but this was the World Cup on linkedin in payments and open banking.”
Many more interesting quotes in the video below:
