Fazekas, Mihály; Poltoratskaia, Viktoriia; Wells, Helene; & Tierens, Michel. (2025). Developing a data-driven corruption risk model to strengthen integrity in Belgium. Practical considerations for the Federal Internal Audit. OECD Publishing, Paris, https://doi.org/10.1787/e85587eb-en.
In light of increasing demands for transparency and accountability in public finance, digital transformation is emerging as a strategic priority for oversight and integrity institutions. This technical paper explores the experience of Belgium’s Federal Internal Audit (FIA) in developing a data-driven audit risk model, supported by the OECD and Government Transparency Institute. It explains the Corruption Risk Index and the risk indicators selected for the proof-of-concept data analytics model for FIA’s future use. It also provides practical considerations for integrating advanced analytics and identifies key enablers for sustainable implementation, including data quality, stakeholder engagement, and continuous model improvement.
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