Generative AI has emerged as a powerful addition to the existing set of AI-powered tools in the field of financial services. By leveraging natural language processing (NLP) algorithms, these machine learning models have numerous use cases, from providing instant insights to streamlining workflows, as well as boosting time savings for professionals.

Some of the key generative AI use cases in financial services include:

Generative artificial intelligence (genAI)—a cutting-edge technology that enables tools (i.e., the chatbot ChatGPT) to generate content—is rapidly gaining popularity within the financial services, wealth management, and banking industries. 

  • Financial Reporting: Generative AI can be used to automate the process of financial reporting. Through historical financial data analysis, genAI algorithms can generate accurate and comprehensive financial reports, saving time and dramatically reducing the chance of human error. 

  • Earnings Analysis: Training models on historical earnings reports allows generative AI algorithms to produce insights and predictions about future earnings. This can help financial professionals make informed investment decisions and identify potential opportunities in the market.
  • Market Research: GenAI can also be a valuable tool for conducting market research, as it can analyze large volumes of market data, predict market trends, analyze customer preferences, and conduct competitor analysis. When used proactively, financial professionals gain a competitive edge and make data-driven decisions.