Basel Institute on Governance ¦ Money Laundering, Money Dirtying (Part II) – Insights from 42 Case Studies

Untangling Grand Corruption: Patterns of Illicit Financial Flows from 42 Case Studies

Grand corruption and illicit financial flows are two sides of the same coin: corrupt actors create opportunities to divert large public resources, and those diverted funds then travel through complex financial networks to hide origin and ownership. Recent preliminary research from the Falcon project analyzed 42 corruption cases spanning the 1990s to 2024 to identify recurring patterns in the financial side of grand corruption. The study seeks a unified financial perspective that treats the corrupt acts and the subsequent money movement as a single, integrated process, enabling better detection, research and enforcement.

How the study was conducted

Researchers compiled 42 case studies from judicial records, asset-recovery reports, official press releases and open-source media. Using a 5W1H approach to capture when, where, why and how each scheme operated, they extracted variables tied to the financial anatomy of schemes: types of benefits exchanged, transaction channels, intermediaries and jurisdictions involved. The sample covered many economic sectors (energy supply was heavily represented) and a multi-decade temporal span. The aim was to move beyond isolated anecdotes and build a comparative framework that highlights systematic features across diverse grand corruption cases.

What the evidence shows about the utilities exchanged

Monetary compensation dominates: in approximately 86% of cases investigators identified direct or indirect monetary payments as the primary mechanism to transfer illicit benefits. Non-monetary benefits – luxury gifts, favors or other in-kind advantages – played a notable role too, appearing in nearly 29% of cases. Qualitative review indicates these non-monetary utilities are not peripheral: they help build trust, cement relationships and smooth transactions between officials and private actors. Examples include luxury gifts exchanged alongside cash in procurement arrangements during the COVID-19 period – illustrating how social and relational factors are central to many corruption schemes.

Transaction channels: overlaps and differences between “money-dirtying” and money laundering

Bank transfers are central in both the initial dirtying of funds and the later laundering stages; wire transfers are highly prevalent across the dataset. However, the study identified relative differences: offshore accounts and real estate show greater involvement in the classic laundering phase, while cash and gifts are relatively more common in the initial dirtying of public funds. These distinctions suggest physical proximity and interpersonal exchange matter in the earlier stages, while cross-border corporate structures and asset investments play a larger role in later concealment and integration. Critically, channels are rarely exclusive – most schemes employ multiple methods sequentially or in parallel (for example, moving proceeds offshore, then buying foreign real estate).

Bastian Schwind-Wagner _Follow

"Grand corruption often begins with transactions that look legitimate on paper, such as consultancy fees or procurement payments, but those flows become contaminated when used to secure private gain. Identifying the “dirtying” phase alongside later layering and integration helps detect schemes earlier and targets prevention where it can be most effective.

To operationalize this approach, investigators and financial institutions need standardized cross-border data, improved beneficial‑ownership transparency, and technological tools that link entities, accounts and transactions. Strengthened cooperation between anti‑corruption and anti‑money‑laundering actors will shorten investigations and increase the chance of recovering diverted public assets."

Intermediaries and corporate vehicles: the façade of legitimacy

Corporate entities and legal arrangements are nearly ubiquitous: about 90% of cases involved corporate vehicles such as shell or front companies, trusts or other structures used to create a veneer of legitimacy, mask beneficial ownership and route payments. Common patterns include labelling corrupt payments as consultancy fees, fictitious invoices routed through consulting or holding companies, and the placement of assets into trusts to obscure true owners. Individual facilitators – family members, business partners and professionals – appeared in more than half of cases, with particularly strong involvement in the initial dirtying stage. This reinforces the social embeddedness of many schemes: trusted people and known networks are often used to move funds and disguise their origin.

Transnational complexity and the role of “satellite” jurisdictions

The 42 cases involved actors and financial links across 84 countries, and each case used on average more than four “satellite” jurisdictions – third countries that facilitate banking, corporate registration or asset purchases without being principal participants in the underlying corrupt act. Frequently used satellites included Cyprus, British Virgin Islands, Switzerland, the United Kingdom and Singapore. Choice of satellite jurisdictions is not random: selection is driven by geographic proximity, economic and political stability, and financial opacity. Satellites are typically deployed to open bank accounts, incorporate companies, and acquire real estate or luxury goods – mechanisms that enable layer-and-integrate steps in laundering and prolong concealment.

Implications for detection, investigation and policy

The research underscores three practical necessities.

First, a unified framework that integrates the corrupt act and subsequent money flows is essential: treating monitoring (the initial conversion of public funds into private benefit) and laundering as two linked parts of one financial process yields richer analytic leverage and better-targeted interventions.

Second, the transnational and multi-actor nature of grand corruption requires standardized data collection and cross-jurisdictional aggregation; investigators need harmonized, high-quality information on contracts, transactions, beneficial ownership and asset movements to reconstruct schemes.

Third, technological solutions – network analytics, big-data systems and automated transaction monitoring – are required to trace networks of networks across legal entities, accounts and jurisdictions at scale.

Operational challenges and investigative realities

Detecting corrupt consulting fees or disguised payments is rarely straightforward. Many corrupt payments are covered by legitimate-looking contracts and invoices; distinguishing real consultancy from façade work often requires deep contract review, forensic accounting and witness testimony. Investigations typically combine open-source intelligence with restricted datasets (bank records, beneficial ownership registries) accessible only through judicial authorizations. High levels of secrecy in offshore financial centers and the resource intensity of long-lived probes mean some corrupt schemes remain opaque for years – cases can take a decade or more to reach conclusions. The Odebrecht example reinforces this: critical facts emerged only after insiders provided evidence.

On the typology of “money dirtying” and policy utility

Framing the initial conversion of publicly sourced funds into private assets as “money dirtying” provides an analytical lens that complements traditional laundering typologies. It highlights the precursor activities – how money becomes contaminated – and identifies prevention opportunities earlier in the criminal life cycle. The term helps prioritize indicators and enforcement attention on pre-laundering behaviors (contract awarding, budget manipulation, in-kind exchanges), not just on classic layering and integration. That said, adopting the label does not necessarily mean creating new legal burdens; instead, it can guide law enforcement, compliance and asset recovery priorities and refine third-party risk policies by clarifying which actions or transactional patterns warrant elevated scrutiny.

Practical steps for banks and compliance teams

Banks face difficult trade-offs but can improve detection by combining technological tools with contextual intelligence. Automated transaction monitoring, AI-supported pattern detection and comprehensive risk-scoring systems remain important, but so does tailoring red flags to sectoral and country contexts. Key actions include updating risk models to capture patterns typical of grand corruption (large public-contract-related payments routed through intermediate consultancies, repeated small transfers to related parties, use of satellites with specific features), improving beneficial-ownership due diligence, and strengthening co-operation channels with law enforcement and other banks. High-quality, timely access to ownership, corporate registry and cross-border transaction data is vital; banks must be able to escalate investigations when red flags align with contextual indicators.

Next methodological steps: crime scripting for financial flows

The Falcon team plans to refine the framework by applying crime script analysis to the 42 cases: dividing schemes into three phases – initiation (opportunity identification), execution (generation and transfer of illicit proceeds) and consumption (layering, integration and concealment). For each phase the template will map actors, scenes, pre- and post-activities, enabling conditions, facilitators and the precise financial mechanics: transaction types, chains, intermediaries and jurisdictions. Integrating financial crime scripting with actor-scene analysis should produce a structured typology useful to investigators, compliance officers and policy makers.

Concluding observations

The exploratory analysis from 42 cases reveals consistent patterns across diverse grand corruption schemes: monetary and non-monetary utilities are used to create corrupt relationships; wire transfers are pervasive but are supplemented by offshore entities and real estate; corporate vehicles and trusted intermediaries are core enablers; and satellite jurisdictions are selected non-randomly to exploit proximity, stability and opacity. These findings argue for bridging the gap between anti-corruption and anti-money-laundering efforts through shared data standards, improved cross-border cooperation, targeted technological investment and refined typologies that capture the dirtying phase as well as traditional laundering stages. Doing so will strengthen the ability of investigators and financial institutions to spot, disrupt and recover proceeds from grand corruption.