Bank Attributes and Financial Performance in Nigeria New Insights From Adopting Machine Learning Programming Approach

Abstract

This paper examined the influence of bank attributes on financial performance of deposit money banks in Nigeria, using base data from annual reports and accounts of 13 purposively selected deposit banks in Nigeria for 8 years, culminating into 104 data set. The study adopted Python 3 to run the predictive models in order to evaluate their performance from the Jupyter Notebook and PyCharm (IDE).  The exploratory data analysis (EDA) was deployed to uncover hidden insights for a better preparation to better assumptions that would satisfy the choice of best analytical tool. The results from analysis provide empirical evidence that credit risk and capital ratio are effective determinants of commercial banks’ performance in Nigeria. Nevertheless, this behavioural pattern should take cognizance of requirement of Basel III especially the required minimum capital, leverage ratio, liquidity coverage ratio and net stable funding ratio (NSER).

Keywords: Credit risk, capital to assets ratio, liquidity risk, risk-adjusted return on asset, Nigeria