OECD (2019). Analytics for Integrity: Enhancing Integrity Risk Assessments through Data-Driven Approaches. Available at: https://www1.oecd.org/gov/ethics/analytics-for-integrity.pdf
Effective risk management in infrastructure projects relies on strategic and robust risk assessments in order for managers to identify risks and adapt controls to mitigating them. Risk assessments are often qualitative, relying on observations of employees and experts involved in the projects. To complement these perception-based approaches, those responsible for managing risks in infrastructure—project managers, procurement officials and risk managers—can take advantage of data analytics to further isolate risks and ensure they calibrate control activities appropriately. Doing so, requires investments and planning, and avoiding ad hoc initiatives in favour of an approach that strategically embeds analytics into existing risk management and assessment policies and processes. With this in mind, this report explores strategies, practices and tools for taking data-driven approaches to assessing integrity risks, with an emphasis on applications to infrastructure projects. The report offers insights, considerations and cautions for creating a data analytics capacity, and draws from the OECD’s Recommendations on Public Integrity, Digital Government Strategies and work with a major infrastructure project in Mexico.
Mihály Fazekas drafted Section 3 illustrating a practical application of data-driven corruption risk assessments for an infrastructure project in Mexico, namely the construction of the the New International Airport of Mexico (Nuevo Aeropuerto Internacional de México).