Exogenous Data Using Large Language Models Like ChatGPT

Abstract

This chapter explores the role and potential of Large Language Models (LLMs) like ChatGPT to process exogenous data for various applications through illustrations with GPTs and several useful plug-ins, as well as a practical use case. Exogenous data refer to data external to organization’s traditional, usually internal, financial data collection processes and may include social media, online searches, networks, and news media. The aim of utilizing exogenous data in accounting and auditing is to complement traditional financial reporting and assurance methods by offering a more nuanced and comprehensive view of a company’s activities, as well as enhancing the quality of reporting and audit processes. Stakeholders can improve their decision-making processes by integrating publicly available exogenous data into their analyses. Although exogenous data can provide valuable insights beyond traditional financial statements, acquiring such data might be expensive and time-consuming. Therefore, there is a need for effective tools like ChatGPT to facilitate the process of extracting and analyzing data.