Countering public grant fraud in Spain
: machine learning for assessing risks and targeting control activities
Organización de Cooperación y Desarrollo Económico
creator
text
technical report
Paris
OECD Publishing
30 November 2021
2021
monographic
eng
pdf
p. : gráf., tablas ; 1 documento PDF
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.
specialized
/ OECD
Todos los derechos reservados ; OECD
Políticas públicas digitales
España
gobiernos
fraude
riesgos
subvenciones públicas
técnicas de aprendizaje automático
gestión de datos
Intervención General de la Administración del Estado
OECD Public Governance Reviews
pdf
https://www.oecd.org/publications/countering-public-grant-fraud-in-spain-0ea22484-en.htm
https://www.oecd.org/publications/countering-public-grant-fraud-in-spain-0ea22484-en.htm
Todos los derechos reservados ; OECD
ES-MaONT
211130
20211130141013.0
00006837