Crises, emergency procurement and corruption risks

This introductory chapter delves into the multifaceted challenges posed by corruption to global progress and stability, with a particular emphasis on its heightened prevalence during crises. Public procurement systems, which play a crucial role in emergencies, become more vulnerable under emergency circumstances. The interconnected nature of contemporary crises, exemplified by the Covid-19 pandemic, underscores the necessity to shift from a mere responsive stance to a comprehensive approach. This approach should center around proactive preparedness, effective prevention, and mitigation strategies. The chapter highlights the impact of emergency shocks on anti-corruption enforcement and emphasizes the need for adaptive corruption risk assessment systems during crises. While common red flags remain foundational to such systems, their interpretation and use during non-competitive situations or crises require caution. Contextually, measures to mitigate false positives need reinforcement. Furthermore, the chapter addresses the challenges faced by researchers and policymakers in measuring corruption and advocates for a balanced measurement approach. It underscores the transformative potential of big data and data analytics in comprehending, detecting, and mitigating corrupt practices. The discussion introduces the CO.R.E. project (CO.R.E. - Grant agreement n. 101038790), an EU-funded initiative under the Internal Security Fund Police (ISFP) program. This project aims to adapt corruption risk assessment systems to emergency contexts. Aligned with previous and concurrent projects, the CO.R.E. project capitalizes on big data potentials for corruption risk assessment, and further introduces a crisis-specific methodology and a general measurement framework for red flag computation during crises. The project provides a mapping of corruption risks over emergencies through the CO.R.E.-CI (Composite Indicator), which aggregates individual red flags. Leveraging public procurement big data, the CO.R.E.-CI facilitates prioritizing high-risk cases and guides focused audits and preventive measures. The chapter closes with a description of the structure of the present book.