Financial data modeling: an analysis of factors influencing big data analytics-driven financial decision quality

Purpose - Financial firms are looking for better ways to harness the power of data analytics to improve their decision quality in the financial modeling era. This study aims to explore key factors influencing big data analytics-driven financial decision quality which has been given scant attention in the relevant literature. Design/methodology/approach - The authors empirically examined the interrelations between five factors including technology capability, data capability, information quality, data-driven insights and financial decision quality drawing on quantitative data collected from Jordanian financial firms using a cross-sectional questionnaire survey. Findings - The SmartPLS analysis outcomes revealed that both technology capability and data capability have a positive and direct influence on information quality and data-driven insights without any direct influence on financial decision quality. The findings also point to the importance and influence of information quality and data-driven insights on high-quality financial decisions. Originality/value - The study for the first time enriches the knowledge and relevant literature by exploring the critical factors affecting big data-driven financial decision quality in the financial modeling context.