Optimizing Financial Data Accuracy and Searchability Using AI User Interface and Large Language Models: A Case Study of CEO Compensation

Artificially intelligent chatbots are automated software used by organizationsto automate and enhance customer experience and interactions. In the context of corporate transparency and accountability, stakeholders require detailed and timely information on various aspects of the business, including top-executive management compensation. This study examines the use of an AI-powered user interface for the retrieval and generation of companies’ information pay ratio. Retrieval-Augmented Generation (RAG) and LangChain are the main elements used in this study. The study utilized 2021 data from Wharton’s collection of proxy statements and company filings from the SEC.gov website. The results reveal that the user interface is able to identify and deliver accurate information to a variety of users, such as stakeholders and researchers. The study also examines the building blocks of the proposed interface, detailing its technical blueprint through its features and fundamental components, identifying challenges, and explaining the model’s uses to promote flexibility and transparency. The results from the study provide shareholders and investors with insightful information to assist with their understanding and eventually the evaluation of information.