FALCON ¦ Policy Brief No. 3 Combatting Corruption and Fraud in Public Procurement

Combatting Corruption and Fraud in Public Procurement: Practical Policy Steps for EU Decision‑Makers

Public procurement is a core state activity and a prime vulnerability for large‑scale corruption and fraud. While EU procurement directives provide a strong legal backbone for above‑threshold contracts, most procurement value and activity falls outside their direct scope. That gap leaves room for inconsistent national practices, artificial contract splitting, excessive use of direct awards and weak monitoring of implementation. To reduce inflated costs, low‑quality delivery and resource misallocation, policymakers must extend effective oversight beyond headline thresholds, accelerate digital and analytical reforms, and tighten accountability around non‑competitive awards. The recommendations below focus on realistic, cost‑sensitive actions that increase detection, deter abuse and improve cross‑border comparability.

Strengthen oversight of below‑threshold procurement rather than simply lowering thresholds

The EU directives meaningfully constrain corruption risks where they apply, but the current thresholds exclude many contracts. Lowering thresholds to bring all contracts under EU procedural regimes would impose heavy administrative burdens and overwhelm publication systems. A better approach is stronger and more consistent enforcement of above‑threshold rules across member states together with targeted, risk‑based oversight of below‑threshold activity. Risk scoring tools, open‑source intelligence and company data can flag suspicious patterns – such as repeated small contracts to the same suppliers, unusual bid patterns, or signs of contractual splitting – so authorities can prioritise audits. This targeted supervision reduces the incentive to fragment contracts to avoid scrutiny while containing administrative costs.

Drive e‑procurement adoption with standardised, interoperable data

Electronic procurement increases transparency and access, but current implementation suffers from inconsistent formats and weak links to company registries and financial datasets. EU member states should mandate standardised, machine‑readable public procurement records with unique identifiers that link tenders, suppliers and contract implementation data. Required fields should include not only tender notices and award decisions but also implementation metrics – payments, timelines, amendments, and cost breakdowns. Standardisation enables routine cross‑checking, third‑party analysis and more effective audits, while training and clear guidance reduce the transition burden for contracting authorities and businesses.

Bastian Schwind-Wagner _Follow

"Strengthening oversight of below‑threshold procurement and standardising e‑procurement data are practical steps that will make corruption harder to hide and easier to detect. When combined with targeted risk‑based monitoring and tighter controls on direct awards, these measures protect public funds without imposing unmanageable administrative burdens.

Integrating ethically governed AI for risk scoring and investing in capacity for investigation will prioritise the most concerning cases and reduce time wasted on false leads. Transparency, human oversight and safeguards for due process must accompany any analytic system to preserve fairness and public trust."

Integrate AI and machine learning into e‑procurement systems, aligned with safeguards

Automated analytics can process vast datasets to detect anomalous patterns and prioritise investigations. AI‑based risk engines can surface likely corrupt or fraudulent behaviour earlier and more reliably than manual review alone. Implementation must align with the EU AI Act and ethical standards: models should be transparent, auditable, and include human oversight and mechanisms to correct false positives. The FALCON project’s prototype platform demonstrates how multiple indicators across procurement, company and financial domains can support near‑real‑time risk assessment and investigation prioritisation. Rolling out such systems at scale requires investment in data quality, model validation, staff training and clear governance for data use.

Tighten rules and oversight on direct awards

Direct awards – contracts granted without competitive procedures – are inherently higher risk. The EU Court of Auditors’ finding that more than 15% of contracts were direct awards in 2021 is a signal that controls are insufficient in some jurisdictions. Member states should restrict direct awards to narrowly defined exceptions such as genuine emergencies or security‑sensitive procurements, require rigorous pre‑award justification and approval, and ensure robust post‑award documentation and ex‑post audits. Clear thresholds for acceptable use, mandatory public reporting of all direct awards, and independent review mechanisms will reduce abuse and increase public trust.

Institutionalise data‑driven indicators and build investigatory capacity

Corruption detection works best when it is systematic. Authorities should adopt common corruption risk indicators and red‑flag systems based on administrative big data, company registries and financial signals. Investment is needed in research to refine indicators, in data platforms that allow secure linking of datasets, and in the organisational capacity for agencies to act on alerts. Best practice includes combining quantitative risk scoring with focused qualitative investigation and ensuring law enforcement and procurement oversight bodies can exchange relevant information while respecting legal safeguards.

Policy implications – what success looks like

A harmonised approach to procurement oversight, stronger digital systems, and analytic detection tools will reduce discretionary decision‑making and make corrupt patterns easier to spot and prosecute. Standardised procurement data and interoperable identifiers enable cross‑institutional collaboration and comparative risk analysis across jurisdictions. Targeted monitoring of below‑threshold contracts prevents easy circumvention, while tighter limits and controls on direct awards close a major loophole. Together, these measures will improve value for money and public confidence in procurement outcomes.

Implementation priorities and sequencing

Begin with achievable reforms that build capacity and generate quick returns:

1. mandate standard, machine‑readable procurement data and required implementation fields;
2. introduce risk‑based oversight pilots for below‑threshold tenders using existing datasets;
3. tighten documentation and reporting requirements for direct awards; and
4. pilot AI risk‑scoring tools under strict governance to validate indicators and reduce false positives.

Parallel investments in staff training, model governance and interagency data sharing arrangements will be essential to scale these pilots into durable systems.

Risks and safeguards

Data and algorithmic tools can produce false positives and, if poorly governed, may unfairly target suppliers. Transparent model design, audit trails, human review of alerts and appeal processes for affected parties are necessary. Privacy and due process safeguards must guide linking administrative datasets and sharing information across agencies. Finally, reforms must balance transparency with administrative feasibility to avoid overload of contracting authorities.

Conclusion

Combatting corruption in public procurement requires focused upgrades to oversight where most activity occurs, digital standardisation to enable analysis, integration of ethically governed AI for early detection, and a strict narrowing of direct awards. These measures, implemented in a phased, risk‑sensitive way, will close common loopholes, strengthen enforcement, and improve procurement outcomes across the EU.

Dive deeper

• FALCON ¦ Shiji A., Gibson H., Guiver C. Policy Brief: Recommendations for Combatting Corruption and Fraud in Public Procurement, November 2025, CENTRIC. ¦ Link