VB Transform 2024 Panel: Finance Leaders Share How GenAI Is Changing Financial Services

The panel of experts from Bank of America, Brex, Google, and Cerebrus at VB Transform 2024 provided insights into how generative AI is transforming the financial services industry, with applications in customer service, engineering support, and operational efficiency.

Generative AI’s potential to simplify complex financial topics: David Horn from Brex highlighted gen AI’s ability to “raise the floor” by translating complex financial topics into easily understandable language, potentially enabling a digital CFO capability for smaller businesses lacking dedicated financial resources.

• Horn noted that finance can be particularly challenging for smaller organizations without a dedicated Chief Financial Officer (CFO).
• Generative AI can break down complex financial concepts into natural language, making them more accessible and understandable.

Bank of America’s exploration of gen AI use cases: Awais Bajwa from Bank of America outlined several potential applications of gen AI within the bank, focusing on internal use cases while cautiously exploring customer-facing applications:

• Improving developer efficiency and productivity within the bank’s large engineering organization of over 10,000 developers.
• Enabling knowledge workers to more efficiently process information through knowledge discovery and summarization.
• Potential future use cases include customer-facing recommendations and automating customer service, though the bank is still in the early exploration phase for these applications.
• Bajwa emphasized the importance of explainable AI, allowing the bank to understand the weights and data used to train the models.

Unlocking insights from financial services data: Zac Maufe from Google Cloud highlighted gen AI’s potential to help financial services organizations extract valuable insights from their vast amounts of structured and unstructured data:

• Financial services organizations often have a wealth of data but struggle to derive meaningful insights due to data silos and technological constraints.
• Maufe sees gen AI as a catalyst for unlocking insights from this data more quickly and accurately.
• He noted that many current gen AI deployments in financial services are for internal use cases, with human oversight as a control point.
• Maufe anticipates a near-term future where gen AI becomes more widespread and prominent in financial services as advancements are made in grounding, explainability, and embeddings.

Broader implications and critical analysis: While generative AI shows great promise in transforming the financial services industry, it is crucial to consider the regulatory and compliance concerns that may be tempering the pace of adoption. As the technology continues to evolve, it will be essential to strike a balance between innovation and ensuring the responsible and transparent use of AI in this highly regulated sector. Additionally, the panel’s focus on internal use cases highlights the need for further exploration and development of customer-facing applications to fully realize the potential of gen AI in financial services.