Using Technology to Bring Transparency to the Offshore Economy and Disrupt IFFs
Illicit financial flows (IFFs) are the illegal movement of money across borders, often involving practices like tax evasion, money laundering or corruption. As the world has become more interconnected, illicit financial flows have significantly harmed the public good in countries across the globe. The International Monetary Fund estimates $500 to $600 billion in lost revenue to governments each year, leading to global inequality, political corruption, regional instability, and economic volatility of immeasurable proportions.
Illicit financial flows are secretive by nature. Powerful individuals and organizations use this anonymity to shield themselves from financial regulations, laws, and criminal liability. To lift the curtain of illicit financial flows, it is essential to identify those beneficial owners that operate in the shadows.
The International Consortium of Investigative Journalists (ICIJ) created the Offshore Leaks Database with data from groundbreaking investigations into the offshore economy. This publicly available platform links beneficial owners to over 819,000 offshore entities in more than 200 countries and territories around the world. Continually updated, the database reveals how the rule of law is bent and broken with a system of financial secrecy benefiting a global elite.
ICIJ’s project takes the Offshore Leaks Database to the next level, developing Web API technology for seamless, real-time data sharing of this beneficial ownership registry. This sustainable information exchange will enable the public to integrate the Offshore Leaks Database to their own systems, so that regulators, legal entities, and other change agents may recoup lost revenue and bring accountability to the offshore economy.
Computerized System for Quality and Consistency of MERs
GAFILAT is an international organization that brings together 18 Latin American countries. It promotes and evaluates the implementation of the International Standard against money laundering (ML) and financing of terrorism (FT) (FATF 40 Recommendations).
Countries are evaluated in a Mutual Evaluation (ME) process based on the FATF methodology, which assesses the extent to which AML/CFT systems comply with the standard and their effectiveness.
MEs are fundamental to the overall AML/CFT system, as they identify deficiencies in the systems and issue recommendations for improvement. ME reports (MER) provide information on jurisdictions' risks, allowing for appropriate actions to be taken if necessary. For this reason, the quality and consistency of the MER are important.
The assessment methodology presents complex areas that, added to the particularities of the countries, may generate discussions and different interpretations on the analysis performed and its consistency with the standard. There could be situations in which contradictory conclusions or precedents can been reached, which could affect the quality and consistency of the MER.
Currently, there is no database in the FATF Global Network (GN) that unifies the assessments as well as the criteria analyzed and conclusions adopted in the MER and their discussions. The GAFILAT Quality and Consistency System will be a tool that will consolidate, index and systematize FATF and GAFILAT MERs and the precedents arrived at, to contribute to the quality and consistency of future MERs.
The system will enable comparative analysis of technical criteria and key issues throughout the assessments. It will also produce reports and statistics that can be integrated into other GN projects. It will also make it possible to visualize the decisions made in the evaluations according to the risk and context of the different countries.
The system is part of the digitalization process that GAFILAT has been carrying out in recent years. It is an innovative response to a visible and concrete need with great implications for the efficiency of GAFILAT's work and potential for implementation throughout the entire GN.
Digital Transformation of AML/CFT/CPF Supervision to Prevent and Combat IFFs Related to Environmental Crime
The project is managed by the Cambridge Centre for Alternative Finance (CCAF) at the Cambridge Judge Business School. It focuses on the development of a proof-of-concept (POC) and working prototype for AML, CFT and CPF supervisors and financial intelligence units (FIUs) to enhance their capabilities to collaboratively prevent and combat illicit financial flows related to environmental crimes. AML/CFT/CPF supervision, ESG supervision and the involvement of financial authorities in combating environmental crime are all recent areas of work that require innovative approaches, constant refinement of methodologies and scalable tools.
Therefore, the CCAF is conveying a Working Group of financial supervisors from jurisdictions representing different income levels, capacity, resources and experience. These supervisors are working on either AML/CFT/CPF or ESG supervision, supported by world renowned experts, technologists, data scientists and investigative journalists.
The Working group will research the following topics:
- Technology-enabled implementation of the Financial Action Task Force priorities
- Beneficial ownership and corporate transparency efforts
- Risks related to cryptocurrencies and digital assets
- Overlapping and varying of mandates, use cases and solutions for FIU intelligence function and Central Banks supervision
- Private-public partnership and data fusion enhanced by AI/ML- and blockchain-driven data collection, storage, analytics and visualisation
The collaborative research will inform the development of a POC for a suptech application to prevent and combat illicit financial flows related to environmental crime. The prototype will combine data governance software, process automation and advanced analytics to strengthen inter-agency cooperation. This will provide more granular and timely transactional data with intelligence about configuration and activities of the criminal networks, to establish better feedback loops between banks, FIUs and law enforcement agencies.
Wildlife Trafficking Anti Money Laundering Risk Assessment Model for Asia - Development and Testing
The Hong Kong Special Administrative Region (HKSAR) is a global hub in the wildlife trade, an international financial centre and vital staging post for trade across Asia. On the doorstep of Mainland China and fixed between demand centres and biodiverse landscapes, the HKSAR has become a key node in illegal wildlife trade (IWT) networks. From 2015 to 2020, 2,817 wildlife seizures led to the confiscation of 2,215 metric tonnes of wildlife, conservatively valued at EUR86.9 million, and the arrests of 1,842 individuals. Despite the high values and serious and organised criminality involved, no investigations resulted in convictions for financial crimes in any wildlife cases. Routine arrests of ‘mules’ or ‘couriers’ have been interpreted as demonstrating “a low level of ML threat.” However, absence of evidence is not evidence of absence and there are numerous cases from other jurisdictions illustrating that illicit finances related to IWT have flowed into the city.
In light of its strategic position, the scale capital flows and also of IWT, the HKSAR is a natural launchpad for efforts to combat converging wildlife and financial crimes and to develop scalable solutions. To this end, ADM Capital Foundation (ADMCF), AML Analytics and KPMG Advisory (Hong Kong) Limited (KPMG)) are collaborating on a risk model for Asia. With partnering financial institutions, they will utilise Red Flag Tests (RFTs) developed by AML Analytics to test the detection logic of AML/CFT systems and publish an AML Risk Rating Model developed by KPMG on how to better detect and disrupt IWT-related financial crimes.
ADMCF brings expertise on the various modus operandi of wildlife criminals exploiting the HKSAR and years of data from its ‘Seizure to Sentencing’ (S2S) programme. AML Analytics has developed an innovative RFT solution customised to specifically tackle IWT using synthesised transaction data to identify vulnerabilities in a transaction monitoring system and its ability to alert against IWT-related transactions. KPMG will develop risk scoring models to detect suspicious patterns and activity post-gap analysis. In combination, this initiative will bolster awareness in a vital financial hub and provide a workable playbook for local and global FIs and regulators to identify and tackle converging financial and wildlife crimes.
ADM Capital Foundation in consortium with AML Analytics and KPMG Hong Kong