Five generative AI use cases for the financial services industry

Generative AI has the potential to revolutionize the way we live, work, bank, and invest. Its impact could be as significant as the advent of the internet or the mobile device. Indeed, 82% of organizations considering or currently using gen AI believe it will either significantly change or transform their industry

1. Financial document search and synthesis

Gen AI can help bank employees effectively find and understand information in contracts (e.g., policies, credit memos, underwriting, trading, lending, claims, and regulatory) and other unstructured PDF documents (e.g., ”summarize the regulatory filings of bank X”).

Gen AI can help bank analysts accelerate report generation by researching and summarizing thousands of economic data or other statistics from around the globe. It can also help corporate bankers prepare for customer meetings by creating comprehensive and intuitive pitch books and other presentation materials that drive engaging conversations.

2.Enhanced virtual assistants

Gen AI excels in finding answers in large corpuses of data, summarizing them, and assisting customer agents or supporting existing AI chatbots. Gen AI-powered chatbots can also be more conversational. These capabilities help provide improved customer service experiences. For example, Gen AI can speed up credit card fraud resolution — a win-win for customers and customer service agents.

3.Capital markets research

In capital markets, gen AI tools can serve as research assistants for investment analysts. Such assistants can help sift through millions of event transcripts (e.g., earnings calls), company filings (e.g., 10Ks/10Qs), consensus estimates, macroeconomic reports, regulatory filings, and other sources, and quickly and intelligently identify and summarize key information.

4. Regulatory code change consultant

In the financial services industry, new regulations emerge every year globally while existing rules change frequently, requiring a vast amount of manual or repetitive work to interpret new requirements and ensure compliance. Developers need to quickly understand the underlying regulatory or business change that will require them to change code, assist in automating and cross-checking coding changes against a code repository, and provide documentation.

5. Personalized financial recommendations

While existing Machine Learning (ML) tools are well suited to predict the marketing or sales offers for specific customer segments based on available parameters, it’s not always easy to quickly operationalize those insights.

For example, creating marketing emails or in-app messages with specific financial recommendations can be time-consuming. Gen AI can help in the creative process of one-to-one personalized messaging at scale using conversational language. It can help improve customer experience, retention, and cross sales.