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What is the impact of generative AI in the financial services industry? That’s a question that a panel of experts at the VB Transform 2024 discussed on Wednesday providing deep insights.
The panel discussion included leaders from Bank of America, Brex, Google and Cerebrus who shared their perspectives on how AI is reshaping the financial services industry. Financial services are using gen AI for various use cases, including customer service, engineering support and operational efficiency improvements
“Generative AI is very good at raising the floor,” David Horn, head of AI at Brex said.
Horn noted that finance can be a very complex topic, that can be particularly difficult for smaller businesses that might not have the resources to have a dedicated Chief Financial Officer (CFO). With gen AI, he said that complex topics can be translated into an easier-to-understand natural language that can potentially enable a digital CFO capability for an organization.
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How Bank of America is testing out gen AI for financial services
For Awais Bajwa, head of Data and AI Banking at Bank of America, the promise of gen AI is considerable.
Among the use cases for gen AI at Bank of America outlined by Bajwa is improving developer efficiency and productivity within the bank’s large engineering organization of more than 10,000 developers. He also noted that it can help knowledge workers more efficiently ingest and process information by enabling knowledge discovery and summarization. Future potential use cases in customer-facing recommendations and automating customer service, though the bank is still in the early exploration phase for those types of applications.
Bajwa also detailed how gen AI is evaluated. He emphasized that explainable AI is critical to Bank of America.
“We need to be able to understand the weights and understand the data that the model is being trained on,” he said.
Gen AI is bringing new insights to financial services data
Financial services organizations tend to have a lot of data.
For Zac Maufe, global head of regulated industries at Google Cloud, gen AI is the catalyst that can potentially help financial services organizations to unlock insights from data better.
“I would call it a data-rich world, but insight-poor,” Maufe said.
Maufe noted that data has ended up in silos for various reasons including technology constraints and organizational preferences. He also said that the financial ecosystem contains a large amount of both structured and unstructured data.
“I think that the future really is getting much faster, better accurate insights out of all of that data,” he said.
With financial services, regulations and compliance are always key concerns. Those concerns might be leading to a more measured pace of adoption of gen AI. Maufe said that many gen AI deployments in financial services are for internal use cases where organizations are using a human in the loop as a control point. He does however see a near-term future where gen AI is even more widespread and prominent in financial services.
“There’s a lot of work that’s going on around grounding, explainability and around embeddings to get to a place where this can be more primetime,” Maufe said.
