The Impact of Data Analytics on Financial Asset Management Efficiency and Financial Prediction Accuracy in Strategic Decision Making in the Digital Era

Abstract

Digital transformation in the financial sector has driven the adoption of data analytics technology to support strategic decision-making.This study aims to analyze the impact of data analytics on the efficiency of financial asset management (X1) and the accuracy of financial predictions (X2) in supporting financial decision-making (Y). The research employs a quantitative approach using secondary data obtained from financial reports of fintech-based companies during the 2018–2023 period. The independent variables include the efficiency of financial asset management and the accuracy of financial predictions, while the dependent variable is the quality of financial decision-making. The data is analyzed using multiple linear regression to identify relationships and effects between variables. The findings indicate that the efficiency of financial asset management has a significant positive impact on financial decision-making, with a coefficient of 0.45. Similarly, the accuracy of financial predictions significantly contributes with a coefficient of 0.39. The regression model achieves an Adjusted R² value of 0.82, meaning that the model explains 82% of the variability in financial decision-making. This study underscores the importance of data analytics in enhancing operational efficiency and informational accuracy to support strategic decision-making. Companies are advised to increase investment in big data technology and artificial intelligence while providing employee training to effectively utilize these technologies.