Incorporating Financial Knowledge with ChatGPT to Make Informed Investment Decisions

Abstract

The present paper aims to assess the potential of AI technologies, such as ChatGPT, in the field of finance, by incorporating financial knowledge with ChatGPT to facilitate informed investment decisions. The research was designed based on the empirical study method, which tests hypotheses regarding the impact of financial knowledge within ChatGPT across three levels: Normal Financial Knowledge, Experienced Financial Knowledge, and Profound Financial Knowledge. These levels serve as independent variables, while informed investment decisions represent the dependent variable. Based on the case study method, this research is designed to provide empirical evidence regarding the integration of financial knowledge with ChatGPT to facilitate informed investment decisions. It employs artificial intelligence systems as the study population, with a sample consisting of ninety tested cases conducted on the ChatGPT platform using the purposive sampling technique. The data collected is in the form of documentary data resulting from direct testing by researchers through inquiries posed to ChatGPT on the OpenAI website. The study's most significant findings highlight ChatGPT's inability to provide equal opportunities for users, particularly for those requiring financial literacy. Consequently, not all users can make informed investment decisions. Therefore, the study suggests the necessity of enhancing certain aspects of ChatGPT. This could include incorporating mathematical equations and tables, along with offering users multiple response options for each question posed. This research can be the first local empirical research to evaluate AI technologies by incorporating financial knowledge with ChatGPT to make informed investment decisions.