Abstract
global Islamic finance industry has experienced significant growth in recent years, establishing Islamic financial institutions (IFIs) as prominent players in the international financial landscape. To maintain competitiveness and sustainability, IFIs must embrace innovation and explore avenues for maximising their performance. This research aims to investigate the effect of AI-based Chatbots on the value and profitability of IFIs in Organisation of Islamic Cooperation (OIC) countries. The study has employed quantitative methodology, and the data was collected from the Bloomberg database, Thomson Reuters DataStream, World Development Indicators and annual reports of 104 IFIs across 44 OIC countries from 2020 to 2022. Employing the Generalised Method of Moments (GMM), this study investigates the impact of AI-based Chatbots on the value and profitability of IFIs. The findings show a positive impact of Chatbot on Return on Assets (ROA), Return on Equity (ROE), and Tobin’s Q (TBQ). Furthermore, the analysis reveals that variables such as Gross Domestic Product (GDP), institutional size (SIZE), and age (AGE) exhibit positive associations with the value and profitability of IFIs. Conversely, the study identifies Consumer Price Index (CPI) as exerting a negative influence on the value and profitability of IFIs, indicating potential challenges posed by inflationary pressures. IFIs may consider investing in the development and deployment of advanced AI technologies to enhance overall profitability. Keywords: AI-based Chatbot; Profitability; Islamic financial institutions (IFIs); OIC Countries; Dynamic GMM
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.