Towards Standardized Tax Reporting: Leveraging Business Analytics in the Inland Revenue Department

Abstract

The Inland Revenue Department (IRD) of Nepal has been recognized for its leadership in e-governance through the integration of digital technologies into tax administration. While existing systems have successfully transitioned manual processes into electronic formats, the absence of a comprehensive analytical reporting platform limits the ability of decision-makers to independently access and interpret critical data. This research investigates the key management reporting requirements within IRD by conducting a structured survey among senior officials. Priority reports focused on revenue collection, income tax returns, VAT returns, and taxpayer registration were identified and systematically standardized based on parameter prioritization. To address the performance constraints of Online Transaction Processing (OLTP) systems in generating complex reports, an Online Analytical Processing (OLAP) model is suggested. The model supports advanced business analytics operations such as slicing, dicing, aggregation, and dynamic visualization, enabling multidimensional insights for effective policy formulation and operational oversight. Demonstrated use cases highlight the model’s capacity to generate actionable intelligence, with potential for further extension into predictive analytics using machine learning and AI. This approach bridges the gap between digital data collection and strategic decision-making, offering a scalable and adaptable solution for tax authorities in similar developing contexts.