The Impact Of Big Data Analytics Using Artificial Intelligence

Abstract

This research aims to explore the impact of big data analytics using artificial intelligence in its four dimensions (expert systems, machine learning, neural networks, and intelligent agents) on the effectiveness of financial risk management. To achieve this goal, a case study was conducted on the National Popular Credit Bank (CPA), where data were collected through a questionnaire directed at a sample of 55 employees, and analyzed using the Structural Equation Modeling methodology (SEM-PLS) to provide practical evidence of the nature of this relationship in the CPA. The research found a strong positive impact of the combined dimensions of artificial intelligence on financial risk management, explaining 68.6% of the variance in the dependent variable (R²=0.686). The results revealed a variation in the importance of these dimensions; the analysis showed a statistically significant effect of machine learning and intelligent agents, while no effect was found for expert systems and neural networks. These results highlight the strategic importance of predictive and automated technologies in enhancing risk management in the banking sector.