THE IMPACT OF ELECTRONIC BANKING ON THE FINANCAIL PERFORMANCE OF COMMERCIAL BANK IN NIGERIA

ABSTRACT This study Examine the impact of electronic banking on the financial performance of commercial banks in Nigeria. With the rapid adoption of digital banking methods such as Automated Teller Machines (ATMs), Point of Sale (POS) terminals, and mobile banking, Nigerian banks face both opportunities and challenges in enhancing their financial performance and promoting financial inclusion. The research examines how transaction volumes through these digital platforms affect banks' profitability, with a focus on banks listed in Nigeria. The findings aim to provide insights for policymakers, bank management, and future research on digital banking’s role in the financial sector. It explores key concepts such as the evolution of e-banking, its benefits, and the challenges faced by both consumers and banks. The research also discusses various theories related to e-banking adoption, including trust, security concerns, and the role of automated delivery channels. Furthermore, it highlights the implications of e-banking for banks, including competitive pressures, security issues, and the shift towards a cashless society. The findings emphasize the need for banks to enhance customer satisfaction and address technological and security challenges in Nigeria's evolving banking landscape. The study use secondary data from 2019 to 2023. Focusing on Automated Teller Machines (ATM), Point of Sale (POS), and mobile banking (MB) as independent variables, the study uses Deposit Money Bank Total Assets (DMBTA) as a proxy for bank performance. The research employs the Cross-Section Augmented Autoregressive Distributed Lag (CS-ARDL) model to analyze both short- and long-term dynamics, considering cross-sectional dependence. Preliminary tests, including correlation, unit root, and cointegration tests, will ensure the validity of the model. It also, investigates the relationship between Deposit Money Bank Total Assets (DMBTA) and key financial indicators: ARPT, PRPT, and MRPT. Descriptive and inferential analyses, including panel unit root, cointegration, and CS-ARDL models, were conducted on data from multiple countries. Findings reveal that while short-run changes in ARPT, PRPT, and MRPT significantly impact DMBTA, only MRPT has a statistically significant long-term effect. The study highlights the presence of cross-section dependence, slope heterogeneity, and long-run relationships among the variables. Results suggest a strong short-term connection and provide insights for managing bank assets in dynamic financial environments.