Using big data to improve banking decision-making

Abstract

This study aimed to investigate the role of utilizing big data analytics across its five dimensions (Volume, Velocity, Variety, Veracity, and Value) in improving the banking decision-making process at Al-Jumhouria Bank in Tripoli. To achieve the study objectives and test its hypotheses, the researcher adopted a descriptive-analytical approach. Methodological triangulation was employed, utilizing a structured questionnaire distributed to a simple random sample of (120) respondents out of a total population of (250) managerial and technical staff closely associated with decision-making, supplemented by standardized personal interviews. The study revealed several key findings, most notably: a statistically significant impact at the significance level (\ 0.05) of big data dimensions, both collectively and individually, on enhancing the quality and timeliness of banking decisions (strategic, operational, and credit), with "Value" and "Veracity" emerging as the most influential dimensions. Furthermore, results indicated that while Al-Jumhouria Bank possesses an acceptable technical infrastructure, it requires continuous upgrading to effectively handle the rapid influx of unstructured data. The study recommended the critical need to expand investment in advanced analytical software for real-time processing, deliver specialized training programs to enhance data-mining skills among bank personnel, and robustly update security frameworks to safeguard information confidentiality and reliability.