This report looks at how data analysis techniques and information management tools can help make regulatory inspections more efficient through better risk analysis, targeting and co-ordination. It is based mainly on work conducted by the OECD in Italy (funded by EC DG REFORM) to pilot the use of machine learning techniques and data-driven analysis for risk assessment and to improve information systems integration. The pilots, undertaken in the regions of Campania, Lombardy and Trentino,, cover several regulatory domains -- food safety, occupational safety, and environment. They show how better use and management of data can improve inspection systems even within a relatively short timeframe. The approach is based on improving the identification and rating of risk factors, so as to focus regulatory efforts on those businesses or establishments with the highest risks.

This report was approved by the Regulatory Policy Committee at its 24th Session on 21st April 2021 and prepared for publication by the OECD Secretariat.

This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.

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