“We’re using Gemini as the translator, as the interface between the input from the customer and multimodal agents and the language chain that we have built,” says Piotrowski. “It helps us serve that last mile of the customer-facing experience. It is tailor-made to work only with the data, which means we avoid hallucinations. Explainability is important to our clients, so no doubt can be injected into the conversation.”
As Bud Financial continues to grow and develop new applications, Piotrowski is optimistic on the growth potential for GenAI-powered financial products. “Financial institutions don’t need better CRM,” he explains. “Getting quality data is the big thing. They need to make better use of the data they already have to understand their customers. We think this is a massively underdeveloped area, and there is a lot we can do in terms of rethinking how a bank operates and making it more data-focused.”
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BankUnited Innovates Its Customer Service with SAVI
Besides applying GenAI tools to customer data to gain insights, the technology has a growing role in helping financial institutions deliver better customer service.
BankUnited, a regional bank headquartered in Miami Lakes, Fla., uses GenAI to empower SAVI, its internal chatbot. Before SAVI, BankUnited employees sometimes struggled to deliver time-sensitive answers to queries from the bank’s small-business customers, resulting in lengthy call times and inconsistent answers.
Working with AWS, BankUnited developed SAVI using its Bedrock service and the Claude 2 model. SAVI serves as a policy management system, with access to more than 400 internal documents that employees can use natural language to query.
“It’s been a game changer,” says Jeiner Morales, senior vice president of data analytics and business systems for BankUnited. “We’ve gone from being reactive and spending time looking things up or waiting for answers to being proactive. Our bankers can now get quick, accurate answers right in front of them. This allows them to spend less time searching for information and more time actually listening to customers, understanding their needs and helping them make decisions.”
When queried by employees, SAVI delivers answers in under 10 seconds, with a 95% accuracy rate. BankUnited has gained wider benefits from the GenAI tool as well.
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“We’ve reduced back-office support calls by about 40%,” says Morales. “We’re also seeing improvements in customer satisfaction, employee confidence and even training outcomes. New hires feel more supported because they have this tool that can guide them. ROI isn’t just dollars, it’s about time saved, better decisions, and happier employees and customers. And by that measure, it’s been a real win.”
Having worked through the initial challenges of working with GenAI, BankUnited is now positioned to continue innovating across its 55 locations.
“This was one of our first generative AI implementations, so risk management and governance were new muscles we needed to build,” Morales says. “The technology was new, and we had to be 100% sure we were protecting customer and company data. We worked very closely with our risk and compliance teams to put guardrails in place, from data access to model validation and human review. It helped us create a framework that we now use and continue to mature for our AI initiatives.”