Publication: Governance Risk Assessment System (GRAS): Advanced Data Analytics for Detecting Fraud, Corruption, and Collusion in Public Expenditures
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2023-11-21
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2023-11-21
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Corruption poses a significant threat to development and has a disproportionate impact on the poor and most vulnerable. Government agencies struggle to identify fraud and corruption in public expenditures. Risk assessments usually rely on manual analysis and follow-up on specific complaints or anecdotes which requires substantial resources. Assessments are often limited in scope and ineffective, failing to generate the evidence needed to build strong cases. The World Bank developed the Governance Risk Assessment System (GRAS), a tool that uses advanced data analytics to improve the detection of risks of fraud, corruption, and collusion in government contracting. GRAS increases the efficiency and effectiveness of audits and investigations by identifying a wide range of risk patterns. GRAS makes use of public data and is based on a robust and comprehensive conceptual framework which draws on insights from experienced practitioners and sound academic research. This report presents GRAS’s main features, examples of GRAS implementation, and outlines the steps government agencies can take in applying GRAS in their countries. GRAS was developed in Brazil, where it has been piloted in four subnational governments and has helped to investigate fraud, corruption, and collusion in public procurement. Concrete results include the identification of over 850 suppliers with strong indication of collusive behavior, 450 suppliers likely registered under strawmen, 500 cases of conflict of interests involving suppliers owned by public servants, and about 4500 companies with connections to political campaigns, among other examples.
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“World Bank. 2023. Governance Risk Assessment System (GRAS): Advanced Data Analytics for Detecting Fraud, Corruption, and Collusion in Public Expenditures. Equitable Growth, Finance and Institutions Insight - Governance. © World Bank. http://hdl.handle.net/10986/40640 License: CC BY-NC 3.0 IGO.”
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