Authors: Anvay Khanna
Abstract: Modern enterprises operating in volatile global markets require more than the static, retrospective financial reporting traditionally provided by ERP platforms. This review article proposes a Smart Forecasting Pipeline an integrated architecture that utilizes advanced analytics to detect and respond to financial volatility in real time. By transitioning from batch-based forecasting to AI-native streaming pipelines, organizations can identify anomalies and market shifts as they occur within the digital core. We evaluate the technical foundations of this transition, including the use of Long Short-Term Memory (LSTM) networks for time-series analysis, probabilistic forecasting for risk management, and Explainable AI (XAI) to ensure regulatory auditability. The study examines the architectural layers required to ingest high-frequency transactional data and the strategic challenges of data quality and model governance. By synthesizing current industry applications and future directions such as agentic AI, this research provides a roadmap for CFOs and architects to build resilient, autonomous financial ecosystems capable of navigating modern economic complexity.
DOI: https://doi.org/10.5281/zenodo.18229719
