02584nab a22003737c 4500 00006725 ES-MaONT 20241218012046.0 210927s2021 xxkar||| ||||i00| 0 eng d 9789264805118 (HTML) 9789264503939 (PDF) 9789264713093 (EPUB) 10.1787/8f99ec8c-en doi ES-MaONT Organización de Cooperación y Desarrollo Económico 2843 Data-driven, information-enabled regulatory delivery / OECD Paris : OECD Publishing, 25 September 2021 37 p. : gráf., tablas ; 1 documento PDF texto isbdcontent informático isbdmedia recurso en línea rdacarrier This report draws upon the results of three projects in different regions in Italy, covering distinct regulatory areas, to assess the increasingly important role played by data analytics in applying and enforcing rules. The importance of risk-based approaches to regulatory inspections and enforcement is well known. However, regulators seeking to incorporate risk-based approaches still encounter roadblocks in terms of insufficient data generally and inadequate data management tools specifically. While using some risk analysis is more efficient than no risk analysis at all, data-related roadblocks have made it more difficult to identify risk factors. This problem has become more pronounced during the COVID-19 pandemic, where regulatory inspections and enforcement activities and related interventions had to be prioritised in order to balance safety concerns. However, recent developments have shown that data management can help improve inspection systems quite quickly, in an easier and cheaper way than in the past, because costs for equipment are lower, less specialist staff time is required, and computing power has increased. Developments in machine learning have also made the analysis of large volumes of data faster. Empresas 2189 2345 Industrias Italia 2751 herramientas basadas en datos herramientas digitales modelos predictivos riesgos sistemas regulatorios https://www.oecd-ilibrary.org/sites/8f99ec8c-en/index.html?itemId=/content/publication/8f99ec8c-en 0 Acceso al documento https://www.oecd-ilibrary.org/governance/data-driven-information-enabled-regulatory-delivery_8f99ec8c-en 0 Más información z ELIB 6725 6725 0 0 0 3 1 7672 01 01 2021-09-27 1000020176918 2021-09-27 00:00:00 2021-09-27 INF