Analytics platform for strategic tax management
Tax Authority strengthens oversight and data-driven decision-making
Challenge
Uruguay’s National Tax Authority needed to evolve from being a large-scale data collector into a truly analytics-driven organization.
Tax data originated from multiple systems, with significant monthly volumes, continuous growth, and high volatility. Reporting requests were handled individually across operational systems, leading to duplicated efforts, fragmented views of information, and heavy reliance on IT teams.
This environment limited the agency’s ability to segment taxpayers, identify risk profiles, prioritize audit plans, measure the fiscal impact of regulatory changes, and generate reliable statistics for executive decision-making across Revenue, Audit, Planning, Internal Control, and Economic Advisory units.
Solution
A corporate analytics platform was implemented to consolidate tax information into a single, governed data repository, automating extraction, transformation, and data integration processes.
The solution incorporated metadata management, formal data quality rules, and multidimensional analytical models. It enabled the development of executive dashboards, analytical cubes, and standardized reporting within a unified platform.
As a result, the agency gained consistent managerial and operational insights to support key processes. The platform significantly reduced the operational impact on transactional systems while expanding analytical autonomy across all decision-making levels.
14
Improvement in institutional efficiency index
29
Relative reduction in VAT evasion
380
Formal data quality and control rules implemented
Benefits
The value behind the solution
Unified data for strategic decisions
A single, trusted version of tax data across the organization.
Smarter, risk-based enforcement
Data-driven taxpayer segmentation and prioritization of audit resources.
Greater analytical independence
Multidimensional models and dashboards that reduce IT dependency and strengthen performance oversight.
Our methodology
The project followed a structured approach combining enterprise data architecture design, progressive data mart development, and the formalization of a data governance framework with metadata and quality controls.
Technical teams and business users were trained to ensure adoption, operational independence, and long-term sustainability of the analytics environment.
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