Cash flow management optimisation using statistical and machine learning techniques : application : client company of PwC

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dc.contributor.author Nacerdine, Dounia Amira
dc.contributor.other Bouchafaa, Bahia, Directeur de thèse
dc.date.accessioned 2025-02-03T14:55:20Z
dc.date.available 2025-02-03T14:55:20Z
dc.date.issued 2024
dc.identifier.other EP00884
dc.identifier.uri http://repository.enp.edu.dz/jspui/handle/123456789/11176
dc.description Mémoire de Projet de Fin d’Etudes : Génie Industriel. Data Science-Intelligence Artificielle : Alger, Ecole Nationale Polytechnique : 2024 fr_FR
dc.description.abstract The project focuses on optimizing cash flow management for a client company by leveraging advanced predictive analytics, including machine learning and time series forecasting models. The aim is to provide future insights into cash flow trends, particularly for accounts receivable and accounts payable. This allows for better strategic financial planning, improved liquidity management, and efficient resource allocation, ultimately enhancing the firm’s financial stability and operational efficiency. fr_FR
dc.language.iso fr fr_FR
dc.subject Cash Flow fr_FR
dc.subject Machine Learning fr_FR
dc.subject Time Series fr_FR
dc.subject Accounts payable fr_FR
dc.subject Accounts receivable fr_FR
dc.subject PwC (PricewaterhouseCoopers) fr_FR
dc.title Cash flow management optimisation using statistical and machine learning techniques : application : client company of PwC fr_FR
dc.type Thesis fr_FR


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