Quantitative Enhancements in Forecast Accuracy Through Sector-Specific Predictive Modeling Techniques: A Comparative Study Between Retail and Financial Services

Prabhuralkar Deepika S

Authors

Prabhuralkar Deepika S Junior Data Analyst, Researcher, Chennai, india Author

Keywords:

Predictive Modeling, Forecast Accuracy, Retail, Financial Services, Machine Learning, Sector-Specific Techniques

Abstract

Accurate forecasting is critical in both retail and financial services for optimizing decision-making and resource allocation. This paper explores the impact of sector-specific predictive modeling techniques on forecast accuracy, with a focus on comparing retail and financial sectors. Employing machine learning algorithms, statistical models, and data-driven approaches, we identify distinct patterns and performance benchmarks across sectors. Results indicate that customization based on sectoral data enhances forecast accuracy significantly, underscoring the importance of tailored predictive modeling. The study provides actionable insights into how organizations can refine their forecasting strategies to achieve optimal outcomes.

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