Evaluating the forecast indicators of the volume of highly liquid assets of commercial banks in the process of digital transformation

The study investigates the forecasting of highly liquid assets in commercial banks within the context of digital transformation, emphasizing their pivotal role in financial stability and liquidity management in the financial sector. Employing the ARIMA (AutoRegressive Integrated Moving Average) model, the study intends to project the dynamics of highly liquid asset volumes and their influence in terms of technological advancements. Overall, the analysis focuses on main determinants, including technological adoption, operational efficiency, regulatory frameworks, and market conditions, to evaluate their impact on liquidity management strategies in the banks. Also, the study further highlights the strategic integration of digital technologies, such as artificial intelligence, blockchain, and big data analytics, that is set to enhance decision-making processes and optimize liquidity management in commercial banking and financial sector overall.