Effect of Accounting Information Systems on Enhancing Decision-Making Processes in Financial Institutions: A Case of Ecobank, Rwanda

Effect of Accounting Information Systems on Enhancing Decision-Making Processes in Financial Institutions: A Case of Ecobank, Rwanda

Elia Ninsima & Tarus Thomas
School of Graduate Studies, University of Kigali, Rwanda.
Email: nluckyelia@gmail.com

Abstract: This study examined the effect of Accounting Information Systems (AIS) on enhancing decision-making processes in financial institutions, using Ecobank Rwanda headquarters in Kigali as a case study. The research was anchored on Decision Usefulness Theory, Information Systems Success Theory, and Contingency Theory to assess the influence of data entry and processing, financial reporting, budgetary control, and cash management systems on managerial decision-making. A mixed-methods approach employing descriptive and explanatory research designs was adopted. Using a census approach, data were collected from 142 employees, with 138 valid questionnaires returned (97.2% response rate), complemented by four key informant interviews. Quantitative data were analyzed using SPSS through descriptive and inferential statistics. Multiple regression results showed that the model explained 60.2% of the variation in decision-making processes (R² = 0.602, F = 50.364, p < 0.001). Data entry and processing (B = 0.538, p < 0.001) and budgetary control systems (B = 0.378, p < 0.001) had significant positive effects on decision speed, accuracy, and strategic alignment. However, financial reporting systems (p = 0.700) and cash management systems (p = 0.373) did not show significant independent effects. The study concludes that despite Ecobank Rwanda’s adoption of automated AIS technologies, challenges such as data silos, spreadsheet-based reconciliations, and manual verification reduce system efficiency. It recommends strengthening automated data entry, enhancing budgetary monitoring, improving cash flow forecasting, and providing continuous AIS training to support evidence-based managerial decision-making.

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