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@article{180948,
        author = {Deepesh Vinodkumar Semlani},
        title = {Predictive Cash Flow Forecasting in Cloud ERP Systems: Leveraging AI and Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {3754-3760},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180948},
        abstract = {Accurate and timely cash flow forecasting is vital for financial stability, especially in today’s fast-changing and uncertain economic landscape. This review explores how AI and Machine Learning (ML), when embedded in Cloud ERP systems such as Oracle Cloud ERP and SAP S/4HANA, are transforming traditional forecasting methods. By leveraging time-series models, real-time data pipelines, and predictive analytics, organizations are moving from reactive financial planning to proactive liquidity management. This article synthesizes academic research, industry benchmarks, and platform-specific capabilities, providing an integrated perspective on the tools, models, benefits, and challenges of predictive cash flow forecasting. It proposes a theoretical framework, evaluates real-world case outcomes, and outlines a roadmap for future innovation in finance automation.},
        keywords = {Predictive Cash Flow, AI in Finance, Cloud ERP, Oracle Fusion ERP, LSTM Forecasting, Financial Planning Automation, Treasury AI, Time-Series Forecasting, Digital Liquidity Management, Explainable AI.},
        month = {June},
        }