Anti-corruption et intégrité dans le secteur public
Countering Public Grant Fraud in Spain
Machine Learning for Assessing Risks and Targeting Control Activities
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.
Available from November 30, 2021Also available in: Spanish