02354nam a2200373 c 4500 00006837 ES-MaONT 20211130141013.0 211130s2021 ||||frt i 0| u|eng u DOI 10.1787/0ea22484-en. . ES-MaONT . Organización de Cooperación y Desarrollo Económico 2843 Countering public grant fraud in Spain : machine learning for assessing risks and targeting control activities / OECD Paris : OECD Publishing, 30 November 2021 p. : gráf., tablas ; 1 documento PDF texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier OECD Public Governance Reviews In the wake of the COVID-19 pandemic, governments face both old and new fraud risks, some at unprecedented levels, linked to spending on relief and recovery. Public grant programmes are a high-risk area, where any fraud ultimately diverts taxpayers’ money away from essential support for individuals and businesses. This report identifies how Spain’s General Comptroller of the State Administration (Intervención General de la Administración del Estado, IGAE) could better identify and control for grant fraud risks. It demonstrates how innovative machine learning techniques can support the IGAE in enhancing its assessment of fraud risks in grant data. It presents a working risk model, developed with datasets at the IGAE’s disposal, and maps datasets it could use in the future. The report also considers the preconditions for advanced analytics and risk assessments, including ways for the IGAE to improve its data governance and data management. Todos los derechos reservados ; OECD 2192 Políticas públicas digitales 2183 España gobiernos fraude riesgos subvenciones públicas técnicas de aprendizaje automático gestión de datos Intervención General de la Administración del Estado 5322 OECD Public Governance Reviews https://www.oecd.org/publications/countering-public-grant-fraud-in-spain-0ea22484-en.htm Acceso al documento 0 pdf INF udc 6837 6837 0 0 z 0 3 1 01 01 2021-11-23 1000020177031 2021-11-30 00:00:00 2021-11-30 INF web