Corporate Laundering Database

Sr# Company Name Country AML Network Risk Rating
1 Microsoft Corporation United States 🔴 High Risk
2 IBM Corporation United States 🔴 High Risk
3 MetLife Inc. United States 🔴 High Risk
4 Prudential Financial United States 🔴 High Risk
5 AXA S.A. France 🔴 High Risk
6 Allianz SE Germany 🔴 High Risk
7 Richemont International United Kingdom 🔴 High Risk
8 Kering SA France 🔴 High Risk
9 Louis Vuitton Moët Hennessy (LVMH) France 🔴 High Risk
10 Alibaba Group United Kingdom 🔴 High Risk
11 Tencent Holdings United Kingdom 🔴 High Risk
12 ZTE Corporation China 🔴 High Risk
13 Huawei Technologies China 🔴 High Risk
14 Royal Caribbean Group Liberia 🔴 High Risk
15 Carnival Corporation United States 🔴 High Risk
16 United Parcel Service (UPS) United States 🔴 High Risk
17 FedEx Corporation United States 🔴 High Risk
18 Mastercard Incorporated United States 🔴 High Risk
19 Walmart Inc. United States 🔴 High Risk
20 MoneyGram International, Inc. United States 🔴 High Risk
21 Western Union Company United States 🔴 High Risk
22 PayPal Holdings, Inc. United States 🔴 High Risk
23 Alphabet Inc. United States 🔴 High Risk
24 Amazon.com Inc. United States 🔴 High Risk
25 Meta Platforms Inc.  United Kingdom 🔴 High Risk
26 Apple Inc. United States 🔴 High Risk
27 American International Group (AIG) United States 🔴 High Risk
28 Marsh & McLennan Companies United States 🔴 High Risk
29 Apex Digital Payments United Kingdom 🔴 High Risk
30 Robinhood Financial LLC United States 🔴 High Risk
31 Block Inc. United States 🔴 High Risk
32 Brink’s Global Services  United States 🔴 High Risk
33 Ericsson  Sweden 🔴 High Risk
34 McKinsey & Company United States 🔴 High Risk
35 SNC-Lavalin Canada 🔴 High Risk
36 Thyssenkrupp AG Germany 🔴 High Risk
37 LafargeHolcim Ltd Switzerland 🔴 High Risk
38 Alstom S.A. France 🔴 High Risk
39 Daimler AG Germany 🔴 High Risk
40 Ford Motor Company United States 🔴 High Risk
41 Toyota Motor Corporation Japan 🔴 High Risk
42 Samsung Electronics Korea, South (South Korea) 🔴 High Risk
43 GlaxoSmithKline plc  United Kingdom 🔴 High Risk
44 AstraZeneca PLC  United Kingdom 🔴 High Risk
45 Sanofi S.A. France 🔴 High Risk
46 Pfizer Inc. United States 🔴 High Risk
47 Novartis AG  Switzerland 🔴 High Risk
48 Anglo American plc United Kingdom 🔴 High Risk
49 Vale S.A. Brazil 🔴 High Risk
50 Eni S.p.A. Italy 🔴 High Risk
51 Shell plc United Kingdom 🔴 High Risk
52 TotalEnergies SE France 🔴 High Risk
53 Bayer AG Germany 🔴 High Risk
54 BASF SE Germany 🔴 High Risk
55 Unilever PLC United Kingdom 🔴 High Risk
56 Nestlé S.A. Switzerland 🔴 High Risk
57 PepsiCo Inc. United States 🔴 High Risk
58 Coca-Cola Company United States 🔴 High Risk
59 Procter & Gamble (P&G) United States 🔴 High Risk
60 Johnson & Johnson  United States 🔴 High Risk
61 Honeywell International Inc. United States 🔴 High Risk
62 Boeing Company​ United States 🔴 High Risk
63 Siemens Energy AG Germany 🔴 High Risk
64 General Electric Company (GE) United States 🔴 High Risk
65 Fiat Chrysler Automobiles (FCA) Netherlands 🔴 High Risk
66 Volkswagen AG Germany 🔴 High Risk
67 BHP Group Limited Australia 🔴 High Risk
68 Glencore International AG Switzerland 🔴 High Risk
69 Rolls-Royce Holdings plc United Kingdom 🔴 High Risk
70 Rio Tinto Group United Kingdom 🔴 High Risk
71 Airbus SE Netherlands 🔴 High Risk
72 Telia Company AB​ Sweden 🔴 High Risk
73 National Australia Bank Limited (NAB) Australia 🔴 High Risk
74 Commonwealth Bank of Australia Australia 🔴 High Risk
75 Westpac Banking Corporation Australia 🔴 High Risk
76 BBVA Compass United States 🔴 High Risk
77 Sumitomo Mitsui Banking Corporation Japan 🔴 High Risk
78 Mitsubishi UFJ Financial Group (MUFG) Japan 🔴 High Risk
79 Sberbank of Russia Russia 🔴 High Risk
80 UniCredit Bank AG  Germany 🔴 High Risk
81 Banco Santander, S.A.  Spain 🔴 High Risk
82 Nordea Bank Abp  Finland 🔴 High Risk
83 ABN AMRO Bank N.V.​ Netherlands 🔴 High Risk
84 Swedbank AB Sweden 🔴 High Risk
85 ING Bank N.V. Netherlands 🔴 High Risk
86 BNP Paribas USA  United States 🔴 High Risk
87 Standard Bank Group Limited South Africa 🔴 High Risk
88 Barclays PLC​ United Kingdom 🔴 High Risk
89 Standard Chartered Bank United Kingdom 🔴 High Risk
90 Industrial and Commercial Bank of China (ICBC) ​ China 🔴 High Risk
91 Odebrecht S.A. Brazil 🔴 High Risk
92 Petrobras S.A. Brazil 🔴 High Risk
93 Banamex (Banco Nacional de México) Mexico 🔴 High Risk
94 Bank of America Corporation​ United States 🔴 High Risk
95 Wells Fargo & Co. United States 🔴 High Risk
96 Citigroup Inc. ​ United States 🔴 High Risk
97 JPMorgan Chase & Co. ​ United States 🔴 High Risk
98 Commercial Bank of Dubai PSC (CBD) United Arab Emirates 🔴 High Risk
99 First Abu Dhabi Bank PJSC (FAB)​ United Arab Emirates 🔴 High Risk
100 Al Rajhi Bank Saudi Arabia 🔴 High Risk
101 Bank Audi sal ​ Lebanon 🔴 High Risk
102 National Bank of Egypt Egypt 🔴 High Risk
103  VTB Bank PJSC​ Russia 🔴 High Risk
104 Gazprombank Russia 🔴 High Risk
105  Skandinaviska Enskilda Banken (SEB) Sweden 🔴 High Risk
106 Lloyds Banking Group plc United Kingdom 🔴 High Risk
107 Raiffeisen Bank International (RBI) Austria 🔴 High Risk
108 UBS Group AG Switzerland 🔴 High Risk
109 Mossack Fonseca & Co. Panama 🔴 High Risk
110 Trafigura Group Pte. Ltd. Singapore 🔴 High Risk
111 Fowler Oldfield Ltd United Kingdom 🔴 High Risk
112 Goldman Sachs Group, Inc. United States 🔴 High Risk
113  Toronto-Dominion Bank (TD Bank) Canada 🔴 High Risk
114 Rabobank National Association United States 🔴 High Risk
115 LexisNexis United States 🔴 High Risk
116 Wirecard AG Germany 🔴 High Risk
117 Wachovia Bank United States 🔴 High Risk
118 Jin Yao Pharmaceutical Co., Ltd China 🔴 High Risk
119 GRIDEN DEVELOPMENTS LIMITED United Kingdom 🔴 High Risk
120 SEABON LIMITED United Kingdom 🔴 High Risk
121 CRYSTALORD LIMITED United Kingdom 🔴 High Risk
122 Nazaha Saudi Arabia 🔴 High Risk
123 Lyoned Trading Co LLC United Arab Emirates 🔴 High Risk
124 AFC Import Export Tourism A.S. Turkey 🔴 High Risk
125 Silopi Elektrik Uretim A.S. Turkey 🔴 High Risk
126 Zeyfa Import Export A.S. Turkey 🔴 High Risk
127 Wise (Nuqud) Ltd United Arab Emirates 🔴 High Risk
128 Rmeiti Exchange Lebanon 🔴 High Risk
129 Hassan Ayash Exchange Lebanon 🔴 High Risk
130 Arab Bank (New York Branch) United States 🔴 High Risk
131 Malik Exchange United Arab Emirates 🔴 High Risk
132 Mirabaud (Middle East) Limited United Arab Emirates 🔴 High Risk
133 R.J. O’Brien (MENA) Capital Limited United Arab Emirates 🔴 High Risk
134 HSBC Private Bank (Suisse) SA Switzerland 🔴 High Risk
135 Khanani & Kalia International Pakistan 🔴 High Risk
136 Lebanese Canadian Bank Lebanon 🔴 High Risk
137 Can Holding Turkey 🔴 High Risk
138 Mashreqbank PSC United Arab Emirates 🔴 High Risk
139 Emirates NBD Bank United Arab Emirates 🔴 High Risk
140 Ciner Group Turkey 🔴 High Risk
141 Halkbank Turkey 🔴 High Risk
142 Papara Fintech Turkey 🔴 High Risk
143 Bank of Beirut (UK) Ltd United Kingdom 🔴 High Risk
144 Istanbul Gold Refinery Turkey 🔴 High Risk
145 Kaloti Jewellery Group United Arab Emirates 🔴 High Risk
146 Lebanese Canadian Bank SAL Lebanon 🔴 High Risk
147 CYRUS OFFSHORE BANK Iran 🔴 High Risk
148 Galaxy Oil FZ LLC United Arab Emirates 🔴 High Risk
149 SAMAN TEJARAT BARMAN TRADING COMPANY Iran 🔴 High Risk
150 TRIOLIN TRADE FZCO United Arab Emirates 🔴 High Risk
151 Prevezon Holdings Ltd. Cyprus 🔴 High Risk
152 Swedbank AB Sweden 🔴 High Risk
153 ABLV Bank Latvia 🔴 High Risk
154 Banca Privada d’Andorra Andorra 🔴 High Risk
155 FBME Bank Tanzania 🔴 High Risk
156 Pilatus Bank Malta 🔴 High Risk
157 Ramon Olorunwa Abbas United Arab Emirates 🔴 High Risk
158 BSI Singapore Singapore 🔴 High Risk
159 Lu Huaying United Arab Emirates 🔴 High Risk
160 Green Alpine Trading LLC United Arab Emirates 🔴 High Risk
161 Babylon Navigation DMCC United Arab Emirates 🔴 High Risk
162 Charterhouse Bank Limited Kenya 🔴 High Risk
163 Bank of Latvia Latvia 🔴 High Risk
164 Bank of Mozambique (Banco de Moçambique) Mozambique 🔴 High Risk
165 1Malaysia Development Berhad (1MDB) Malaysia 🔴 High Risk
166 Arkan Mars Petroleum United Arab Emirates 🔴 High Risk
167 Omnivest Gold Trading LLC United Arab Emirates 🔴 High Risk
168 PT Asuransi Jiwasraya  Indonesia 🔴 High Risk
169 PT Bank Century Tbk Indonesia 🔴 High Risk
170 Nauru Nauru 🔴 High Risk
171 BTA Bank Joint Stock Company Kazakhstan 🔴 High Risk
172 Bank of Credit and Commerce International Luxembourg 🔴 High Risk
173 BNP Paribas France 🔴 High Risk
174 Credit Suisse Switzerland 🔴 High Risk
175 Commerzbank AG Germany 🔴 High Risk
176 ING Groep Netherlands 🔴 High Risk
177 Société Générale France 🔴 High Risk
178 Danske Bank Denmark 🔴 High Risk
179 HSBC Holdings United Kingdom 🔴 High Risk
180 Deutsche Bank Germany 🔴 High Risk
181 Abraaj Group United Arab Emirates 🔴 High Risk
182 NMC Health Plc United Kingdom 🔴 High Risk
183 KEVLAR GENERAL TRADING LIMITED LLC United Arab Emirates 🔴 High Risk
184 Gulf Invest Real Estate Broker United Arab Emirates 🔴 High Risk
185 HANEDAN GENERAL TRADING L.L.C United Arab Emirates 🔴 High Risk
186 HUSEYNOV DIAM L.L.C. United Arab Emirates 🔴 High Risk
187 GULF BUSINESS PARTNERS CORPORATION United Kingdom 🔴 High Risk
188 MALDEV GENERAL TRADING United Arab Emirates 🔴 High Risk
189 Lyra Enterprises Ltd United Kingdom 🔴 High Risk
190 Gulf Worldwide Distribution FZE United Arab Emirates 🔴 High Risk
191 Jubilee Store LLC United Arab Emirates 🔴 High Risk
192 JEWELLERY SPOT L.L.C United Arab Emirates 🔴 High Risk
193 Investcorp Holdings B.S.C. Bahrain 🔴 High Risk
194 GFH Financial Group B.S.C. Bahrain 🔴 High Risk
195 Osool Asset Management BSC Bahrain 🔴 High Risk

Corporate laundering is a sophisticated form of financial crime in which illicit funds are funneled through corporate structures to disguise their illegal origins. Unlike traditional money laundering, which often involves cash-based schemes, corporate laundering exploits complex legal and financial mechanisms within companies—such as shell firms, front companies, and layered corporate ownership—to obscure beneficial ownership and the source of funds.

These corporate entities may have no real business operations and are often incorporated in secrecy jurisdictions where transparency laws are weak. Through a series of transactions involving these companies, criminals make dirty money appear legitimate, facilitating tax evasion, bribery, corruption, fraud, and sanctions circumvention.

The global scope of corporate laundering is vast, affecting multiple sectors and jurisdictions. It enables criminal enterprises, corrupt officials, and illicit networks to integrate illicit proceeds into the legitimate financial system, thereby undermining economic stability, the rule of law, and public trust. Given the complexity and scale, combating corporate laundering requires comprehensive data, innovative investigative techniques, and international cooperation across regulatory, financial, and civil society domains.

Objectives of the Corporate Laundering Database

The Corporate Laundering Database is designed to serve as a central, authoritative repository of information on corporate entities and structures suspected or known to be involved in laundering illicit funds. It aims to promote transparency, due diligence, and accountability in detecting and preventing corporate financial crime.

Users who benefit from this database include regulatory agencies enforcing AML laws, financial institutions conducting customer screening and enhanced due diligence, investigative journalists exposing illicit networks, law enforcement entities pursuing criminal investigations, and the general public seeking transparency.

The core goals of the database are to:

  • Provide detailed, verifiable corporate profiles to reveal hidden ownership and suspicious linkages.
  • Support risk-based AML compliance by identifying high-risk sectors, jurisdictions, and corporate patterns.
  • Enhance cross-border information sharing to facilitate coordinated investigations.
  • Empower journalists and civil society in uncovering financial crime networks.
  • Strengthen global efforts to combat corruption, tax evasion, sanctions avoidance, and other criminal abuses of corporate entities.

By delivering reliable data and tools, the Corporate Laundering Database bolsters the integrity of the financial ecosystem and advances the fight against complex financial crime.

Key Data Points Tracked

Each corporate entity profiled in the database is cataloged with critical data points designed to assist in risk detection and investigation:

  • Company Name and Registration Details: Including official names, trade names, registration numbers, and incorporation dates to uniquely identify entities.
  • Country of Incorporation and Jurisdiction: Highlighting whether the company is registered in high-risk or secrecy jurisdictions known for lax transparency.
    Known Beneficial Owners: Individuals exerting ultimate control or ownership, disclosed directly or discovered through network analysis, which is crucial for identifying the true controllers behind opaque companies.
  • Related Shell Structures and Corporate Networks: Mapping linked companies used to layer transactions and hide illicit flows, including subsidiaries, sister companies, and holding firms.
  • Industry or Sector Involvement: Identification of high-risk sectors such as real estate, mining, pharmaceuticals, or procurement where money laundering is prevalent.
  • Red Flags and Risk Indicators: Flags include evidence or allegations of sanctions evasion, involvement in money laundering schemes, fraud cases, politically exposed persons (PEPs) associations, and suspicious transaction patterns.

This data structure enables compliance officers, regulators, and investigators to perform targeted due diligence and identify suspicious corporate entities at various points in the laundering cycle—from placement and layering to integration.

Case Studies and Patterns

Case Study 1: Danske Bank Scandal

One of the largest documented corporate laundering cases involved Danske Bank’s Estonian branch, where approximately €200 billion of suspicious transactions flowed through shell companies linked to Russia and former Soviet states. The laundering structure featured multi-layered shell entities registered in secrecy jurisdictions, used to obscure beneficial ownership and disguise transactions as legitimate business activities. Complex webs of offshore firms engaged in circular invoicing and trade-based laundering enabled criminals to integrate illicit proceeds into the European financial system undetected for years until whistleblower revelations triggered investigations and regulatory actions.

Case Study 2: Panama Papers Leak

The 2016 Panama Papers exposed over 214,000 shell companies created by Mossack Fonseca, a Panamanian law firm specializing in corporate secrecy. These structures were employed globally to hide ownership, evade taxes, conceal bribes, and circumvent sanctions. The leak revealed common laundering patterns such as nominee shareholders, layered ownership, and offshore accounts funneling illegal money from corrupt officials, criminals, and wealthy elites. The Papers demonstrated how corporate laundering exploits cross-border company networks combined with secrecy jurisdictions to shield dirty money behind legal facades.

Common Patterns:

  • Layering through Shell Networks: Use of multiple shell companies across jurisdictions to complicate ownership trails and transaction tracking.
  • Fake or Circular Invoicing: Generating fictitious trade invoices to justify cross-border transfers and disguise illicit capital flows.
  • Complex Ownership Chains: Multiple intermediary companies create legal and geographic distance between beneficiaries and illicit funds.
  • Use of Nominees and Fronts: Appointing third-party directors or shareholders to mask real owners, hindering accountability.

Both cases highlight the transnational character of corporate laundering schemes, requiring robust databases that map corporate ownership, relationships, and suspicious activity patterns to aid detection and enforcement.

Role of Offshore Jurisdictions and Loopholes

Offshore financial centers (OFCs) and secrecy jurisdictions play a pivotal role in enabling corporate laundering by offering legal loopholes and confidentiality protections. These jurisdictions—such as the British Virgin Islands, Seychelles, Cayman Islands, Delaware (USA), and UAE—feature minimal disclosure requirements, lax oversight, and often permissive corporate laws facilitating rapid company incorporation.

Key enablers in these jurisdictions include:

  • Lack of Beneficial Ownership Transparency: Many OFCs do not mandate public registers of ultimate beneficial owners (UBOs), allowing criminals to hide behind nominee shareholders and directors.
  • Nominee Directors and Agents: Incorporation services provide nominee appointments, legal intermediaries whose names appear on official documents while real owners remain concealed.
  • Banking Secrecy and Confidentiality: These jurisdictions often protect client identities and financial details from external scrutiny, complicating AML enforcement.
  • Legal Loopholes: Gaps in international cooperation, weak regulatory frameworks, and limited powers to investigate suspicious entities create enforcement blind spots.

Such conditions facilitate sheltering illicit money from tax authorities, regulators, and investigators. Criminals and corrupt officials exploit these features to layer and integrate illegal proceeds into the legitimate economy through shell companies, real estate, and financial instruments.

Addressing these loopholes via enhanced global transparency standards, public beneficial ownership registers, and tighter due diligence requirements is critical for disrupting corporate laundering.

Collaboration with Other Watchdogs

The Corporate Laundering Database is developed in close collaboration with international AML regulators, NGOs, investigative journalism consortia, and other transparency watchdogs. This multi-stakeholder alliance enhances data quality, coverage, and investigative impact.

Key partners include:

  • International Consortium of Investigative Journalists (ICIJ): Sharing investigative findings from Panama Papers, Pandora Papers, and other leaks to enrich corporate profiles.
  • Organized Crime and Corruption Reporting Project (OCCRP): Providing on-the-ground investigative data on kleptocratic networks and offshore abuse.
  • Global AML Regulatory Bodies: Aligning data collection and standards with FATF recommendations and FATF’s global AML guidance.
  • Non-Governmental Organizations (NGOs): Collaborating with anti-corruption organizations and transparency advocates to source public documents and reports.

This cooperation enables cross-border investigations by linking disparate data points, identifying transnational corporate laundering networks, and facilitating information exchange between law enforcement agencies and financial institutions worldwide.

The database’s interoperability with other AML tools—such as PEPs registries, real estate ownership databases, and cryptocurrency monitoring platforms—provides a comprehensive ecosystem for tackling complex financial crime networks.

How to Use the Database

Users can effectively navigate the Corporate Laundering Database through an intuitive interface offering powerful search and filtering options:

  • Search by Company Name or Registration Number: Quickly locate specific entities.
  • Filter by Jurisdiction: Focus on secrecy hotspots or high-risk countries like BVI, Cayman Islands, Seychelles, or Delaware.
  • Filter by Risk Indicators: Narrow down based on known flags such as sanctions links, PEP connections, involvement in fraud or money laundering cases.
  • Explore Corporate Networks: Map relationships between parent companies, subsidiaries, and linked shell entities.
  • Submit Data or Corrections: Registered users can contribute verified corporate information or flag suspicious companies through a secure submission process, supporting database accuracy and currency.

Use Case Examples:

  • Investigative Journalist: Searches for companies connected to recent whistleblowing cases or linked to controversial political figures to expose laundering schemes.
  • Compliance Officer: Screens onboarding clients by filtering entities registered in offshore jurisdictions with red flags or PEP links, triggering enhanced due diligence and risk assessment workflows.
  • Regulatory Investigator: Leverages network visualization of shell company clusters to uncover complex layering techniques and trace illicit fund flows.

Step-by-step tutorials and customer support guide users in maximizing the database’s potential to meet AML compliance, investigative research, and due diligence needs.

Legal and Ethical Framework

The Corporate Laundering Database operates under strict legal and ethical standards to ensure fairness, transparency, and accuracy. Inclusion is based solely on documented, verifiable data or credible suspicious activity reports—not on assumptions or allegations of guilt.

All data is sourced from reputable public records, investigative journalism, regulatory filings, and partner disclosures. The database complies fully with applicable data protection and privacy laws, safeguarding personal information and respecting individuals’ rights.

Editorial independence ensures that profiles do not constitute legal judgments or regulatory determinations. Users are advised to conduct their own due diligence and seek professional advice when making decisions based on database information.

A detailed Disclaimers & Ethics Statement is publicly available, outlining sourcing policies, data verification protocols, and the database’s commitment to responsible reporting in combatting financial crime without compromising fairness and privacy.

Join the global effort to expose and combat corporate laundering by contributing to or utilizing our Corporate Laundering Database. Whether you are a compliance professional, journalist, regulator, or concerned citizen, your verified tips, data submissions, and collaboration strengthen transparency and accountability.

Report suspicious companies, share investigative insights, and help close the gaps in financial secrecy that enable illicit flows. Together, we can enhance AML compliance, disrupt financial crime networks, and uphold the integrity of the worldwide financial system.

Explore the database, contribute today, and be part of the frontline defense in global anti-money laundering investigations.

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