Financial Forecasting Accuracy in Nigerian Commercial Banks: An Assessment

The ability to generate accurate financial forecasts is a foundational competency in commercial banking, as it underpins decisions on liquidity management, loan pricing, provisioning, and capital planning. This study assesses the accuracy of financial forecasting practices in selected commercial banks in Nigeria, examining the methodologies used, the degree of forecast error, and the organisational factors that influence forecasting quality. Primary data are gathered through structured interviews and questionnaires administered to 80 senior financial planning and analysis officers across eight commercial banks with national operational coverage. The study compares projected versus actual figures for key metrics including net interest income, credit loss provisions, and operating costs across the period 2021 to 2023. Data are analysed using mean absolute percentage error, root mean squared error, and thematic analysis of qualitative responses. The theoretical framework draws on bounded rationality theory and the organisational learning perspective on forecasting behaviour. The study examines whether the adoption of artificial intelligence and machine learning tools has improved forecasting outcomes and how macroeconomic volatility, including exchange rate and inflation shocks, degrades forecast accuracy. Recent literature from the banking sector globally highlights forecast errors as significant contributors to liquidity crises and regulatory breaches. This study contributes Nigerian-specific evidence on forecasting quality with recommendations for the Central Bank of Nigeria's supervisory oversight and for internal audit frameworks in commercial banks. Keywords: financial forecasting, commercial banks, forecast accuracy, Nigeria, planning