Investment banks can benefit from generative AI in multiple ways

Investment banks are increasingly turning to generative AI to enhance their operations and boost productivity. While AI and automation have long been utilized in the industry, the potential of large language models (LLMs) and generative AI to revolutionize various functions across the transaction life cycle is now being recognized.

Studies have shown that generative AI can significantly improve productivity in financial services. For example, a study by Stanford researchers found that generative AI increased a call center’s productivity by 14%. Another study by MIT concluded that generative AI helped reduce time and improve the quality of work for marketers, consultants, and data analysts.

Major players in the industry are already exploring the benefits of generative AI. JPMorgan Chase has applied to trademark a product called “IndexGPT” for investment advice, while Wells Fargo is using LLMs to enhance regulatory reporting and business processes. Federal Reserve researchers have also found that GPT models can effectively analyze and classify Federal Open Market Committee announcements.

Vendors to investment banks are also investing in generative AI technology. Bloomberg has launched “Bloomberg GPT,” a large language model tailored for finance, and Pitchbook has introduced the “VC Exit Predictor” tool to predict startup growth prospects.

Generative AI is expected to have a significant impact on front-office operations in investment banking. It can streamline tasks such as content creation, analytical capabilities, and code development, ultimately improving productivity and efficiency. Analysts predict that the use of generative AI could increase front-office employee productivity by 27%–35% by 2026, leading to substantial revenue growth.

Overall, the adoption of generative AI in investment banking is poised to revolutionize the industry, offering new opportunities for automation, innovation, and improved client interactions.