FALCON ¦ Policy Brief No. 6 Recommendations for Combatting Corruption of Politically Exposed Persons

Why PEPs Matter in Financial Crime Detection

Politically Exposed Persons, or PEPs, sit at the center of a major financial crime challenge. Because they hold or have held prominent public functions, they can be exposed to a higher risk of bribery, embezzlement, abuse of office, money laundering, and illicit financial flows. When these risks are not properly identified and managed, the consequences reach far beyond individual cases. They can weaken public trust, distort markets, undermine democratic institutions, and damage the rule of law.

Corruption involving PEPs is a structural threat to governance and economic integrity. As financial networks become more complex and cross-border ownership structures become harder to trace, identifying suspicious conduct linked to politically connected individuals has become more difficult. That is why stronger data, better legal tools, and more advanced analytics are essential.

What Counts as a PEP

The Financial Action Task Force (FATF) divides PEPs into three main groups:

1. Foreign PEPs are individuals entrusted with prominent public functions by another country. This includes heads of state, senior politicians, senior government officials, judicial or military officials, senior executives of state-owned corporations, and important political party officials.
2. Domestic PEPs are people who hold or have held those same kinds of roles within their own country.
3. International organization PEPs are those who have been entrusted with a prominent function by an international organization, such as senior management or board-level equivalents.

This classification matters because PEP status is a practical risk signal. It does not mean wrongdoing has occurred, but it does mean that enhanced due diligence (EDD), closer monitoring, and more careful scrutiny are justified.

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"Politically Exposed Persons present a distinct corruption risk because their public roles can give them access to influence, discretion, and sensitive decision-making power. When oversight is weak and data is fragmented, hidden ownership, conflicts of interest, and suspicious financial activity can be much harder to detect.

Stronger PEP controls depend on better data sharing, tighter conflict-of-interest rules, and careful use of AI-supported analytics. These measures can help authorities identify high-risk patterns earlier, improve cross-border cooperation, and reduce opportunities for illicit enrichment and abuse of office."

Why Current Systems Fall Short

The policy brief highlights a major problem: implementation is uneven across the EU, and enforcement remains fragmented. While the EU has adopted anti-money laundering rules and transparency measures, the systems used to identify and monitor PEP-related risks are still incomplete.

One of the main weaknesses is data fragmentation. Information about company ownership, procurement activity, beneficial ownership, asset declarations, sanctions exposure, and political affiliations often sits in separate systems that do not connect well with each other. This makes it difficult for authorities to detect hidden relationships, conflicts of interest, or illicit enrichment schemes.

In practice, corruption often depends on concealment. The same brief points to shell companies, family or close-associate networks, intermediaries, and opaque ownership structures as common methods used to hide the real beneficiaries of suspicious activity. Without connected data, those patterns are easy to miss.

Building Better Data Infrastructure

A central recommendation is to create a fully interoperable EU-wide data ecosystem. The idea is not just to publish functional PEP lists, but to link those lists with other important databases through shared technical standards and secure access rules.

That would include company registries, beneficial ownership registers, public procurement databases, sanctions databases, asset declaration systems, and lobbying transparency registers. When these sources are connected, authorities can more easily identify politically connected firms, suspicious procurement awards, undeclared interests, and signs of unexplained wealth.

The brief also argues that access should be widened for competent authorities such as Financial Intelligence Units (FIUs) and Law Enforcement Agencies (LEAs), under clear legal conditions and with proper safeguards. Cross-border cooperation is especially important, because corruption schemes involving PEPs often move through multiple jurisdictions.

Why Legal Frameworks Need Strengthening

PEP risk is not only a data problem, it is also a governance problem. Certain procedures are especially vulnerable because they give officials too much discretion and too little oversight.

Public tenders, emergency procurement, politically influenced appointments, discretionary licensing, and opaque lobbying practices are all areas where politically connected actors may obtain unfair advantage. The policy brief argues that EU Member States should narrow the scope of such discretionary procedures and apply stronger oversight to politically sensitive decisions.

Conflict-of-interest rules also need to be tighter and more consistent. The brief recommends stronger and harmonised frameworks requiring disclosure of assets, business interests, beneficial ownership links, gifts, outside activities, and close family relationships. It also stresses the importance of looking backward, so that benefits and relationships can be examined before appointment, not only after misconduct is suspected.

The Role of AI in Detecting PEP-Linked Corruption

The brief makes a strong case for using artificial intelligence and machine learning in anti-corruption work, while keeping human oversight in place. These tools can help detect patterns that are too complex or too large for manual review alone.

By combining procurement records, corporate ownership information, financial indicators such as crypto assets, and PEP datasets, analysts can identify suspicious patterns, hidden relationships, and unusual transactions. This can support the detection of unexplained wealth accumulation, politically connected suppliers, concealed ownership structures, offshore arrangements, and irregular procurement behavior.

FALCON’s work is especially relevant here. Its knowledge base and Corruption Intelligence Pictures show how linked datasets can improve investigation prioritization and help authorities react faster. The aim is not to replace investigators, but to give them better tools.

Safeguards Must Come First

The use of AI in corruption detection must remain aligned with the EU AI Act, GDPR, and ethical AI principles. That means human oversight, transparency, explainability, and accountability are essential.

The brief also notes an important practical risk: AI systems can make inaccurate predictions or even produce false results. That is why they should support decisions, not make them on their own. Explainability features are needed so that authorities can understand why a case was flagged and assess whether the alert is credible.

What This Means for the Financial Crime Community

PEP-related corruption is best tackled through a combination of better data, stronger legal controls, and more effective analytics.

A more connected European framework would improve early detection, reduce regulatory fragmentation, and strengthen cross-border cooperation. It would also make it harder for politically connected individuals to hide illicit enrichment behind complex ownership chains or weak oversight systems.

PEP risk is not just a screening exercise, it is a strategic corruption risk that demands integrated datasets, stronger institutional controls, and practical use of advanced analytics. If authorities can link information faster and act earlier, they can reduce opportunities for abuse of office, illicit financial flows, and political capture of public resources.

Dive deeper

• FALCON ¦ Guiver C., Policy Brief: Recommendations for Combatting Corruption of Politically Exposed Persons, July 2026, Centre of Excellence in Terrorism, Resilience and Organised Crime Research (CENTRIC). ¦ Link