Italy’s tax collection agency is preparing a major shift in its audit strategy beginning in 2026, moving from generalized investigations to a more focused, data-driven approach powered by artificial intelligence [[1]]. The change,spearheaded by the agency’s technology arm Sogei,aims to improve efficiency and target tax evasion through analysis of over 200 databases [[1]]. This move reflects a global trend toward leveraging big data in tax governance, as governments seek to combat increasingly sophisticated evasion schemes [[3]].
Italy’s tax agency is poised to overhaul its audit strategy in 2026, moving away from broad-based investigations toward a more targeted, data-driven approach. The shift, enabled by the agency’s operational arm Sogei, will leverage analysis of over 200 databases to identify taxpayers with a heightened risk of evasion.
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The new system will cross-reference financial data including costs, expenses, revenues, bank account activity, and income to pinpoint potential irregularities. This represents a significant change in how the Italian tax authority allocates its resources, allowing it to concentrate investigations where non-compliance is most likely.
Central to this enhanced selection process is a “score” representing taxpayer fiscal reliability, derived from Synthetic Reliability Indicators (ISA). The agency intends to use these indicators to prioritize audits and improve overall tax collection efficiency. This move reflects a broader trend among tax authorities globally toward utilizing big data and analytics to combat tax evasion, a practice that has gained momentum as technology advances.
Sogei’s capabilities are key to the implementation of this strategy, providing the infrastructure to process and analyze the vast amounts of data required for effective risk assessment. The Italian government has been investing in digital tools to modernize its tax administration, and this initiative is a direct result of those efforts.
