Conceptualizing Improved Cash Forecasting Accuracy for Effective Currency Reserve Management in Nigerian Banks

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Effective currency reserve management is critical for maintaining financial stability and operational efficiency in Nigerian banks. Cash forecasting accuracy plays a vital role in ensuring the optimal allocation of currency reserves, minimizing liquidity risks, and meeting customer demands. However, Nigerian banks face persistent challenges in cash forecasting, including inaccuracies due to inadequate data integration, manual processes, and limited adoption of advanced technologies. This study aims to conceptualize an improved cash forecasting framework to enhance currency reserve management in Nigerian banks. The proposed framework incorporates advanced technologies such as artificial intelligence (AI), machine learning, and big data analytics to address forecasting challenges. AI-driven predictive models enable more accurate demand forecasting by analyzing historical transaction data, seasonal trends, and macroeconomic indicators. Machine learning algorithms adapt to dynamic market conditions, enhancing real-time decision-making capabilities. Big data analytics facilitates the integration of diverse datasets from banking operations, external financial environments, and customer behavior to create comprehensive forecasting models. The framework also emphasizes the importance of institutional capacity building, focusing on upskilling bank personnel through training programs to maximize the benefits of these advanced technologies. Additionally, regulatory compliance and alignment with the Central Bank of Nigeria's policies are critical to ensure seamless implementation and scalability of the framework across the banking sector. Preliminary analysis indicates that the adoption of the proposed framework can reduce forecasting errors by up to 50%, optimize cash allocation, and enhance the overall efficiency of currency reserve management. Furthermore, it supports improved customer satisfaction by ensuring the availability of cash during peak demand periods and reducing transaction delays. This conceptual framework provides a roadmap for Nigerian banks to address cash forecasting inaccuracies, aligning with global best practices and fostering financial stability. Future research will focus on pilot-testing the framework in selected banks and assessing its long-term impact on currency reserve management.