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

In series:OECD Public Governance Reviewsview more titles


Abbreviations and acronyms
Executive summary
Risk-based control in Spain: A foundation for improved analytics
Fraud in public grants: Piloting a data-driven risk model in Spain
Looking ahead: A roadmap of datasets to enhance the fraud risk model of Spain’s Comptroller General
Annexes3 chapters available
Descriptive statistics of variables in the cleaned dataset
Full list of variables in the uncleaned dataset
List of variables used in the analysis
Powered by OECD iLibrary