The Financial Industry’s Role in Combating Human Trafficking: Time for a Change

This article is written to assist financial sector professionals in cases where suspicious transactions or customer behavior may indicate cases of human trafficking. Experience shows that open source intelligence provides actionable insights and context on persons of interest and their transactions. This article will offer some insights on the Egmont Group’s 2023 survey and assessment of Financial Intelligence Unit (FIU) best practices for effectively integrating OSINT into FIU operations. It makes the case for a revised framework to address identified OSINT challenges in financial operations.

Human Trafficking is Worse Than You Think

Human trafficking (HT), also known by other umbrella terms – often used interchangeably — as modern slavery, trafficking in persons, trafficking in human beings, is a global crime affecting every country in the world and virtually every economic sector. There are an estimated 49.6 million people living in conditions of HT worldwide (GEMS, 2022). Each year, these crimes generate $236 billion in illicit profits (ILO, 2024). There was an estimated $346.7 billion in illicit flows and money laundering activity contributed by HT in 2023 (Nasdaq-Verafin, 2024). HT was identified as the most pervasive criminal economy globally in 2021, though it became a close second to financial crimes in 2022 with the addition of new indicators (GITOC, 2023). 

The 10 countries with the largest estimated numbers of victims living in HT include some of the world’s most populous (six are G20 nations) — India (11 million), China (5.8 million), North Korea (2.7 million), Pakistan (2.3 million), Russia (1.9 million), Indonesia (1.8 million), Nigeria (1.6 million), Türkiye (1.3 million), Bangladesh (1.2 million), and the United States (1.1 million) (GSI, 2023). 

The top three countries of origin of federally identified HT victims in the United States consistently include the United States, Mexico, and Honduras (Philippines in 2016 and 2018) (TIP, 2017-2023). Based on criminal justice data (UCR HT 2013-2022), HT takes place in every state in the U.S. — California, Texas, Florida, and New York have the highest numbers of reported cases (NHTH, 2021), while Mississippi has the highest incidence rate per 100,000 population (U.S. Census, 2021).

HT is much worse than estimated given the hidden nature of the crime, underreporting and misclassification of cases, movement across state and national borders, inadequate awareness and understanding of the issues, e.g. lack of centralized data collection, victim identification and perceptions; inadequate sharing of victim information among various stakeholders; few dedicated HT resources; myth acceptance; etc.

The Importance of Following the Money

Given the nature of the crime and the above statistics, human trafficking (HT) ranks among the top predicate offenses associated with money laundering (FATF, 2011, 2018). It generates large sums of illicit proceeds which can be paid or transferred in cash, electronic funds transfers/remittance systems, credit card transactions, payment apps, or virtual assets. Money mules (victims, family members, associates and businesses), acting as witting or unwitting conduits, are used to obfuscate criminals’ identities and their sources of funds to evade detection and facilitate the deposit and flow of illicit proceeds around the world. Financial activity from HT can intersect with the regulated financial system at any point in the HT lifecycle (NMLRA, 2024) and shows a range of transactions that may seem innocent in isolation, but understanding these transaction patterns as a whole, and in context, allow for a greater understanding of the transaction profile of a person or business involved in trafficking.

There are several models detailing the stages of the HT lifecycle in literature, such as:

• TRACE, 2018: Recruitment, Transport, Housing, Exploitation
• Zimmerman and Pocock, 2013: Recruitment, Travel/Transit, Exploitation, Integration/Reintegration (model also includes the possibility of detention and re-trafficking at various points in the process)
• OSCE, 2010: Recruitment/Entry, Transportation, Exploitation, Victim Disposal, Criminal Proceeds
• UNODC Profiling, 2008: Pre-Departure, Departure, Transport/Travel/Transit, Arrival, Exploitation, Identification, Rehabilitation/Repatriation/Reintegration
• UNODC Toolkit, 2008: Recruitment, Transportation and Entry, Exploitation, Other Offences
• IOM, 2004: Recruitment, Travel, Exploitation

Since AML measures (know-your-customer [KYC] checks, thorough background investigations, due diligence, etc) are usually implemented before financial institutions (FIs) establish relationships with clients, FIs are in a unique position to help detect and disrupt HT through banking data and customer behaviors. Analyzing the flow of funds may uncover illicit proceeds, identify victims, traffickers, and related bad actors, or point to transactional evidence such as hotel bookings, online advertising, geographic movement, or transportation. One constant is that the money always flows away from the victims of the crime (Nasdaq-Verafin, 2024).

The Office of the OSCE Special Representative and Coordinator for Combating Trafficking in Human Beings provides a comprehensive guide for financial investigations including several resources for case studies, typologies and investigative techniques. Appendix A is a synthesized list of high risk businesses associated with HT. Appendix B is a list of HT financial indicators (Behavioral, KYC, Transactional) and red flags (OSCE, 2019).

OSINT Advantages and Challenges

Advantages: In the EG study, FIUs indicated that OSINT contributes to multiple areas and is highly important. Among these areas are the development of typologies, the possibility of identifying patterns at a macro level, the possibility of identifying threats and trends related to ML/TF, profile subjects, links between individuals and/or legal entities that cannot be identified in a suspicious transaction report (STR) but are related to other activities, positive/negative information on individuals or entities, trace assets, etc. Experience has shown that when OSINT is integrated into each stage of the FININT lifecycle, it can provide:

• A comprehensive view of the financial landscape to help identify patterns and anomalies.
• Additional context, such as social media activity, public statements, and business affiliations, to map out relationships and connections between various entities and individuals and identify networks involved in money laundering or HT financing.
• Information on any publicly known adverse activities, such as legal issues, negative news reports, or affiliations with high-risk regions or individuals.

The integration of OSINT into FIU operations significantly broadens the scope of information available beyond traditional financial reports and records and allows for a more comprehensive and effective approach to combating financial crimes. 

Challenges: The EG noted several challenges in FIU use of OSINT, including difficulty in verifying the source and information reliability, lack of required technology, subscription cost, jurisdictional/cross-jurisdictional internet prohibition and blockades, FIUs’ specific internet content access prohibition, OSINT searcher anonymity concerns (non-tipping off the FIU interest), data protection regulations/data security laws, and information overload. These challenges may be addressed by:

• Using established intelligence source evaluation and information reliability assessments for OSINT (Wikipedia, 2022).
• Several key technologies and tools are needed but there is no single integrated technology platform that consolidates data from all sources into a single dashboard. Some platforms do combine multiple OSINT functionalities for complex financial crime investigations and provide a unified view of search results, automate some tasks, and offer advanced resolution capabilities to facilitate OSINT analytical insights. The choice of platforms and the mix of technologies will vary based on the organization’s needs, regulatory requirements, and financial investigation considerations such as priority intelligence requirements and gaps, type of online activity, managed attribution, artificial intelligence analyst agent, virtual machine, virtual private network, desktop configuration, workflows, etc. The Human Trafficking Technology Roadmap, Appendix B, provides a useful list of data aggregators, web-based services, and investigation and digital forensics tools (MIT, 2019).
• Noting that traffickers are able to access publicly available red flags and typologies and modify their schemes accordingly to go undetected.
• Many OSINT tools are free/freemium and resource compilations are readily available, e.g. Bellingcat, 2023; AaronCTI, 2024; OSINT Framework, 2024; OSINT For Finding People, 2024; Taranenko, 2024; Burton, 2024; FININT, 2023.

Automated Transaction Monitoring: The Finance Against Slavery and Trafficking Blueprint shows awareness of the threat of human trafficking (HT) is not what it needs to be and these crimes cannot be prevented without the active engagement of the financial sector (Liechtenstein Initiative, 2019). The conventional method of transaction monitoring as the central basis for generating financial intelligence reports achieves little in the area of HT. This is due to the lack of meaningful indicators for automated monitoring. The HT indicators commonly used mainly serve to support compliance staff for the further investigation of suspicious transactions they have already noted, and to distinguish HT from other forms of crime. These indicators are often not applicable to the conventional transaction monitoring systems used in the financial sector to screen/filter out suspicious activities. Transactions linked to HT may therefore not be recognized by anti-money laundering (AML) software, and may never be analyzed by a compliance officer. Many HT transactions are not recognized as such but are mistaken for conventional money-laundering activities when they are reported to FIUs (FATF, 2023). 

Need for a Risk-Focused Framework

Some FI managers and analysts have long maintained that OSINT was marginal for compliance and risk management since Anti-Money Laundering and Counter-Terrorist Finance (AML/CTF) regulations largely only require use of customer documents or the patterns of account behavior available from information on hand. AML practitioners are recognizing the inadequacy of this approach and are developing new frameworks with risk-focused, intelligence-/investigator-led models. 

The Financial Crimes Enforcement Network (FinCEN) issued a notice of proposed rulemaking (NPRM), Fact Sheet: Proposed Rule to Strengthen and Modernize Financial Institution AML/CFT Programs, FIN-2024-FCT1, 28 Jun 2024, pursuant to a part of the AML Act. The NPRM would amend AML/CFT programs under existing regulations to expressly require that such programs be effective, risk-based, and reasonably designed. It would also would require FIs to review government-wide AML/CFT priorities and incorporate them, as appropriate, into risk-based programs, and would provide for certain technical changes to program requirements. 

The National Money Laundering Risk Assessment (NMLRA) identifies money laundering threats, vulnerabilities, and risks that the United States currently faces and includes human trafficking among the AML/CTF National priorities (NMLRA, 2024).

The Financial Action Task Force recommendations, International Standards on Combating Money Laundering and the Financing of Terrorism & Proliferation, also emphasize a risk-based approach and the importance of using information from all available sources, including publicly available information, to combat money laundering and terrorist financing (FATF, 2012-2023).

New platforms and frameworks are needed to integrate FI internal data streams with carefully curated OSINT in secure and accessible environments at each stage of the FININT process.