Generative AI in Finance: Showcasing Real-Life Implementations of LLMs in Banking in 2023
“It’s game-changing. It’s worth all the hype,” Chris Nichols, Director of Capital Markets at SouthState Bank.
At a recent fintech conference, Money 20/20, executives from global banks and digital finance companies hailed generative AI as an explosion of innovation that will unlock new possibilities. Banks are now actively exploring the potential of generative AI, particularly in areas like document search, conversation summarisation, and code generation.
Let’s take a look at a few examples of how global banks are experimenting with Generative AI inside their walls:
Morgan Stanley Wealth Management, a multinational investment bank based in the USA, is using generative AI to create an advanced chatbot that assists their team of financial advisors. This tool taps into the bank’s vast research and data library, providing advisors with the ability to ask questions and analyse large amounts of content. The chatbot’s answers are sourced directly from Morgan Stanley’s content and materials, allowing advisors to access valuable insights and free up time to better serve their clients.
ABN Amro, a banking giant in the Netherlands, is piloting the use of generative AI to generate summaries of conversations between bank staff and customers. Instead of manually taking notes during calls, agents rely on ChatGPT to generate these summaries. This technology allows employees to focus more on the clients themselves and reduces the time spent searching for specific product information.
Goldman Sachs, widely known for its technological advancements, is experimenting with generative AI tools to assist its software engineers. These tools help automate the process of generating lines of code, making the bank a more technology-driven organization.
SouthState Bank has implemented a language solution trained on bank documents, allowing employees to query the system and efficiently interpret internal records. This has led to faster onboarding of new employees and increased proficiency in specific topics or regulations.
Westpac has deployed a language model trained on conversations and banking data to streamline the mortgage application process. By automating tasks and validating information, the bank aims to make the process more seamless and reduce the back-and-forth with customers.
These examples highlight the immense potential of generative AI in the finance industry. As banks continue to explore and invest in these technologies, we can expect to see even more exciting applications in the future.
Looking ahead, Deloitte predicts that by 2026, the use of generative AI could boost productivity for front-office employees in global banks by 27% to 35%. This could potentially generate up to US$3.5 million in additional revenue per front-office employee by the same year. However, the adoption of generative AI is expected to be a gradual process.
Continue reading about experimentations with generative AI in the financial industry happening in 2023, hear from bank leaders about immediate benefits, and learn expert predictions for the future. Don’t miss out on seizing the same opportunities for your business — find out how to get started today. Read the full article now.
