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Abstract
The study examined the effect of machine learning on firm performance of deposit money banks in Nigeria. The specific objective was to determine the effect of machine learning on return on assets and return on investment of deposit money banks in Nigeria. Ex-post facto research design was used in the study. The population of the study consisted of all the (14) quoted deposit money banks in Nigeria Exchange Limited up to December, 2024. The study utilised 10 deposit money banks out of the total population as sample size. The data collected from the banks’ annual reports covered the period of 8 years from (2017 – 2024).Ordinary least square regression analysis used in testing the hypotheses revealed the following: machine learning has a significant positive effect on the on return on investment of deposit money banks in Nigeria (? = 0.718441; p-value = 0.0115); machine learning has a significant positive effect on the earnings per share of deposit money banks in Nigeria (? = 3.262692; p-value = 0.0081). In conclusion, as banks integrate machine learning technologies, they can expect to see improvements in their financial outcomes, which could enhance their overall competitiveness and efficiency in the marketplace. Given the significant positive effect of machine learning on return on investment (ROI), the study recommends that bank executives should prioritize the integration of machine learning technologies into their operational strategies. This can involve investing in training programs for staff to enhance their data analytics skills and implementing machine learning systems to optimize asset management and profitability. Keywords: Machine Learning Technology, Return on Investment, Earnings per Share