Periodic Reporting for period 2 - TRACE (Tracking illicit money flows)
Reporting period: 2023-01-01 to 2024-06-30
With the rise and spread of illicit money flows (IMFs) and crimes enabled by information and communications technology (ICT), law enforcement agencies (LEAs) and financial intelligence units (FIUs) need innovative policing tools in the virtual sphere to counter these threats, particularly in relation to crimes such as financing of terrorism and money laundering through online gambling, art and antiquities, use of cryptocurrencies in property market transactions, and cyber-extortion, which are integral to serious and organised crime. The TRACE Project’s use cases were based on the above threats. EUROPOL states that to disrupt and deter these threats, LEAs must trace financial trails to seize criminal assets. TRACE provides LEAs with state-of-the-art tools and a flexible, modular, open-source platform to: Enhance LEA innovation in artificial intelligence (AI); identify and track IMFs; analyse cross-border money transfers using innovative technologies that process multiple metadata feeds; test and validate new methods for detecting IMFs; enhance information-sharing efficiency among EU LEAs; develop solutions compliant with the rule of law, fundamental rights, and data protection measures that address societal and jurisdictional challenges; pave way for recovering proceeds of crime; and disrupt IMFs.
The TRACE tool can track suspicious financial flows, reconstruct networks, standardise electronic evidence, and recover assets - ultimately fostering public trust in law enforcement and strengthening efforts against financial crime.
The TRACE tool can track suspicious financial flows, reconstruct networks, standardise electronic evidence, and recover assets - ultimately fostering public trust in law enforcement and strengthening efforts against financial crime.
TRACE implemented activities to achieve its objectives, producing 61 deliverables and 26 broad results across 11 Work Packages (WPs). In WP1, TRACE operationalised project management tools (e.g. project manual, and data management plans) to ensure the effective implementation of the project. In WP2, TRACE analysed money flows in use cases such as web forensics for terrorism investigations, and online gambling, while sharing insights with EU LEAs and FIUs. The use cases have exposed challenges such as complex corporate structures and the use of new financial instruments like decentralised finance (DeFi), cryptocurrencies, and NFTs. In WP3, TRACE developed data acquisition and simulation services. Example, TRACE enabled data access to I2P and planetary file systems, complementing services for surface web, deep web, and TOR investigations. TRACE developed analytical services in WP4, such as generating unique identifiers (e.g. bank accounts, cryptocurrency hashes, PGP keys) to create time-sensitive investigation graphs of hidden network activities across web layers. In WP5, TRACE developed backend infrastructure and service integration, such as creating a crowd investigation knowledge graph to facilitate cross-border collaboration and enhance investigative insights. WP5 centralised the development of the TRACE tool, incorporating interconnected layers of solution structures. WP6 involved front-end UI development and system validation. Example, TRACE co-developed with LEAs improved investigation tools to address emerging and traditional crimes. WP7 involved optimisation of information-sharing practices and policy recommendations. Example, TRACE examined the legal framework for cross-border investigations of IMFs in 22 European countries, identifying jurisdictional gaps and good practices. TRACE also explored the inclusion of cyber forensics in European forensic institutes and advised policymakers on strengthening these capabilities.
In WP8 and WP11, TRACE explored ethical, legal and social impact of its solutions. It designed a compliance framework ensuring ethical acceptability of solutions aligned with data protection laws, and fundamental rights. TRACE has advanced best practices for the legal and ethical use of AI by LEAs. WP9 involved training and collaboration, where TRACE delivered curricula and training for FIUs and LEAs on detecting IMFs with TRACE technologies.
WP10 involved dissemination, exploitation and communications, targeting stakeholders (e.g. LEAs), civil society organisations, and the public. The results of TRACE were exploited and disseminated in WP10 through demonstrations, newsletters, scientific publications, etc. For instance, TRACE published 12 scientific articles, 6 newsletters, and 9 briefing policy papers on tracing IMFs and recovery of criminal assets. Example, TRACE sent, to LEAs and policymakers, newsletters and policy papers on areas such as investigation knowledge, and benchmarks for detecting and investigating IMFs in country reports.
TRACE publications have exploited the results of several deliverables such as on e-evidence (D7.6): See publication on “Cross-border access to electronic evidence in criminal matters”, https://journals.sagepub.com/doi/10.1177/20322844241258649(opens in new window). The TRACE-informed book (AI, Law and Ethics in Countering Financial Crime, Cambridge University, 2025 pending) demonstrates another exploitation of deliverables.
Exploitation of the TRACE tool is also being optimised at Austrian Ministry of Defence. Thus, the TRACE "reasoning mechanism" and "system architecture and case management" are run at Austrian National Defence Academy.
TRACE’s engagement with LEAs has set a forum for LEAs to harness their interaction, improving information sharing efficiency. Training materials developed in WP9 have been regarded by trainees and partners as providing a clear, user-friendly approach adaptable to diverse audiences.
By unlocking the potential of ICT, TRACE has laid pathways for leveraging AI-driven practices in combating IMFs.
In WP8 and WP11, TRACE explored ethical, legal and social impact of its solutions. It designed a compliance framework ensuring ethical acceptability of solutions aligned with data protection laws, and fundamental rights. TRACE has advanced best practices for the legal and ethical use of AI by LEAs. WP9 involved training and collaboration, where TRACE delivered curricula and training for FIUs and LEAs on detecting IMFs with TRACE technologies.
WP10 involved dissemination, exploitation and communications, targeting stakeholders (e.g. LEAs), civil society organisations, and the public. The results of TRACE were exploited and disseminated in WP10 through demonstrations, newsletters, scientific publications, etc. For instance, TRACE published 12 scientific articles, 6 newsletters, and 9 briefing policy papers on tracing IMFs and recovery of criminal assets. Example, TRACE sent, to LEAs and policymakers, newsletters and policy papers on areas such as investigation knowledge, and benchmarks for detecting and investigating IMFs in country reports.
TRACE publications have exploited the results of several deliverables such as on e-evidence (D7.6): See publication on “Cross-border access to electronic evidence in criminal matters”, https://journals.sagepub.com/doi/10.1177/20322844241258649(opens in new window). The TRACE-informed book (AI, Law and Ethics in Countering Financial Crime, Cambridge University, 2025 pending) demonstrates another exploitation of deliverables.
Exploitation of the TRACE tool is also being optimised at Austrian Ministry of Defence. Thus, the TRACE "reasoning mechanism" and "system architecture and case management" are run at Austrian National Defence Academy.
TRACE’s engagement with LEAs has set a forum for LEAs to harness their interaction, improving information sharing efficiency. Training materials developed in WP9 have been regarded by trainees and partners as providing a clear, user-friendly approach adaptable to diverse audiences.
By unlocking the potential of ICT, TRACE has laid pathways for leveraging AI-driven practices in combating IMFs.
TRACE engaged extensively with LEAs to understand the technological and legal landscape for investigating IMFs. Through surveys with 42 LEAs, TRACE found a need for improved software solutions, particularly in automated data and document extraction, cross-border legal system harmonisation, and effective data sorting to enhance the efficiency and effectiveness of criminal investigations. These findings were widely disseminated among LEAs, impacting their understanding of user requirements.
The following modules developed by TRACE are among elements that surpass state-of-the-art visualisation applications: TRACE features a dynamic graphical interface (TRACE Graphic Interface), which visualises data via a backend JSON file; Users can engage with various analytical tools, including customisable filters, search modules, and pathfinding features to understand connections between entities; TRACE tool also includes features for fine-tuning company shareholdings and allows for the addition of edges and nodes based on user expertise. Its geo-location functionality and algorithm-driven node placement provide an intuitive visualisation experience.
As TRACE tool helps in tracing IMFs, it could contribute to recovering part of more than €715 billion criminal assets (estimated by UNODC) that is laundered in the world annually. Through its dissemination activities, TRACE reassures the public that the EU and governments are proactive in countering serious threats. By identifying IMFs early, evaluating threats, disrupting criminal organisations, and enabling preventive actions that reduce IMFs, TRACE tool has established a model that LEAs and technology experts can build upon to develop future solutions for countering IMFs.
The following modules developed by TRACE are among elements that surpass state-of-the-art visualisation applications: TRACE features a dynamic graphical interface (TRACE Graphic Interface), which visualises data via a backend JSON file; Users can engage with various analytical tools, including customisable filters, search modules, and pathfinding features to understand connections between entities; TRACE tool also includes features for fine-tuning company shareholdings and allows for the addition of edges and nodes based on user expertise. Its geo-location functionality and algorithm-driven node placement provide an intuitive visualisation experience.
As TRACE tool helps in tracing IMFs, it could contribute to recovering part of more than €715 billion criminal assets (estimated by UNODC) that is laundered in the world annually. Through its dissemination activities, TRACE reassures the public that the EU and governments are proactive in countering serious threats. By identifying IMFs early, evaluating threats, disrupting criminal organisations, and enabling preventive actions that reduce IMFs, TRACE tool has established a model that LEAs and technology experts can build upon to develop future solutions for countering IMFs.