CLOUD COMPUTING AND FINANCIAL PERFORMANCE OF LISTED DEPOSIT MONEY BANKS IN NIGERIA

The financial performance challenges encountered by Nigerian deposit money banks highlight the necessity for innovative solutions. The inefficiencies of conventional banking systems and elevated operating costs call for a transition to technology-driven strategies that can enhance profitability and sustainability. Cloud computing offers a promising solution to these issues, providing a flexible, scalable, and cost-effective alternative to traditional IT infrastructure. This study examines the impact of cloud computing technologies on the corporate performance of listed deposit money banks in Nigeria, focusing on Return on Assets (ROA) as the primary measure of performance. The analysis includes variables such as Automated Chatbot Banking Services (ACBS), Deep Learning Machine in Credit Risk Assessment (DLM), Machine Learning Solutions (MLS), and Return on Asset (ROA). The study utilizes panel EGLS (Cross-section weights) regression analysis to analyze data from a sample of ten (10) listed deposit money banks in Nigeria over a specified period. The results reveal that while ACBS, DLM, and MLS have statistically insignificant impacts on ROA, Firm Size (FSZ) shows a significant negative relationship with ROA. Specifically, the coefficient value and probability for each variable are as follows: ACBS (Coefficient = 0.005605, Probability = 0.7065), DLM (Coefficient = -0.001099, Probability = 0.9507), MLS (Coefficient = 0.007189, Probability = 0.7268), and FSZ (Coefficient = -0.116778, Probability = 0.0000). The study concludes that while cloud computing technologies hold potential for operational improvements, their current utilization does not significantly impact the financial performance of Nigerian deposit money banks as measured by ROA. The significant negative impact of firm size on ROA suggests that larger banks may encounter greater operational challenges that outweigh the potential benefits of cloud computing technologies.