Banks spend a significant amount of time looking for and summarizing information and documents internally, which means that they spend less time with their clients.

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”).

For example, 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.

Sometimes, customers need help finding answers to a specific problem that’s unique and isn’t pre-programmed in existing AI chatbots or available in the knowledge libraries that customer support agents can use. For example, assisting a customer resolve fraudulent transactions. That kind of information won’t be easily available in the usual AI chatbots or knowledge libraries.

That’s where gen AI comes in to help get customers the answers they need. It 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. 

To fully understand global markets and risk, investment firms must analyze diverse company filings, transcripts, reports and complex data in multiple formats. They must also quickly and effectively query this data to fill their knowledge bases

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.

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.

Gen AI can give developers context about the underlying regulatory or business change that will require them to change code by providing summarized answers with links to a specific location that contains the answer. It can assist in automating coding changes, with humans in the loop, helping to cross-check code against a code repository and providing documentation.

For example, today, developers need to make a wide range of coding changes to meet Basel III international banking regulation requirements that include thousands of pages of documents. Gen AI could summarize a relevant area of Basel III to help a developer understand the context, identify the parts of the framework that require changes in code and cross check the code with a Basel III coding repository.

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.