A Comprehensive Approach to Improving Enterprise Management Processes Through Applying Deep Learning Algorithms: A Case Study
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This paper addresses the critical need to enhance the management of pension payments at Benin’s National Social Security Fund (NSSF), highlighting the pivotal role of deep learning methodologies in achieving optimization. As a key institution responsible for safeguarding the financial well-being of the population through social security programs, the NSSF faces unique challenges in managing the large volume of regular pension payments. This study introduces an innovative deep learning-based approach specifically tailored to the complexities of pension payment management at the NSSF in Benin. By leveraging advanced neural network architectures, our methodology aims to streamline and optimize the processes involved in pension disbursements, focusing on improving accuracy, efficiency, and overall operational effectiveness. Key components of this approach include analyzing historical pension payment data, demographic trends, and relevant socioeconomic indicators to develop predictive models. These models help forecast and adapt to changing patterns, ensuring timely and accurate pension payments. Through a detailed case study on the NSSF of Benin, we demonstrate the practical application of deep learning in addressing the specific challenges faced by public entities managing pension payments.
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