SupTech toolbox for monitoring and combating money laundering: what's inside?

The European Banking Authority provides an overview of the new SupTech toolbox, which is intended to bring banking supervision into a new era.
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Aristotelis Zervos

Aristotelis Zervos, Editorial Director at 2B Advice, combines legal and journalistic expertise in Data protectionIT compliance and AI regulation.

With the publication of the AML/CFT package in June 2024 and the foundation of the Anti-Money Laundering and Countering the Financing of Terrorism Authority (AMLA) the EU has taken a significant step towards harmonized and technology-based money laundering and terrorist financing supervision. The AMLA will ensure the coordination of national authorities and introduce a uniform methodology for supervision. The use of Supervisory Technology (SupTech) The focus is on digital tools that can significantly increase the efficiency, quality and reach of supervision. A new report by the European Banking Authority (EBA) provides an overview of the powerful SupTech tools.

What the SupTech toolbox offers: Technologies and fields of application

In an EU-wide survey, the EBA has 60 SupTech projects which are currently mainly being developed or are already in use by supervisory authorities. These tools are primarily designed for use by supervisory authorities. However, they are also indirectly aimed at the supervised companies. This is because they provide interfaces, supply data and have to interact with the systems. The central technologies in particular include

  • Big Data & Data Analytics
  • Artificial intelligence (AI) & Machine Learning
  • Natural Language Processing (NLP)
  • Blockchain analysis
  • Automated process control (RPA)


Typical fields of application:

  • Risk assessments and clustering of suspicious patterns
  • Transaction monitoring (incl. crypto analyses)
  • Data visualization and automated reporting
  • Case management and whistleblower systems

Practical examples from the EBA study

The EBA study provides a number of concrete examples. These illustrate how SupTech is already being used in practice by supervisory authorities today and what added value this brings for supervision.

For example, one authority developed a central inspection planning system that bundles all relevant data and schedules and thus optimizes audit trails.

Another authority implemented an automated risk assessment system. This works with AI-supported clustering algorithms and semantic searches to identify risks faster and more precisely.

A blockchain analysis tool has been introduced for the cryptocurrency sector. This recognizes suspicious transaction patterns and thus improves the supervision of digital assets.

In addition, some supervisory authorities use natural language processing (NLP) and process automation to efficiently structure and evaluate large amounts of data from different sources, especially in crypto cases.

In practice, these solutions also require a high level of data quality and willingness to cooperate from the supervised companies. This is because their data supplies often form the basis for the analyses.

How the SupTech instruments strengthen supervision

The added value of the new EBA toolbox is multi-layered and goes far beyond simply increasing efficiency. It opens up the possibility of fundamentally redesigning supervisory processes in a data-driven and risk-oriented manner. This not only means faster analyses and more precise assessments, but also better preparation for future audits and regulatory requirements. By integrating AI-supported risk assessments, blockchain analyses and automated workflows, internal control systems can be proactively examined for weaknesses.

The toolbox also improves the ability to identify cross-border risks at an early stage and to standardize communication with international partners and supervisory authorities. It supports the traceability and auditability of decisions, which is crucial for compliance with regulatory transparency obligations.

In addition, the EBA toolbox promotes greater involvement of Compliance in strategic business decisions by providing data-based insights that can be directly incorporated into risk strategies and business policies.

Reading tip: BaFin publishes minimum requirements for the risk management of securities institutions

Challenges for SupTech tools

Although the new SubTech toolbox offers considerable potential, its widespread introduction is associated with numerous challenges.

Data quality is a key problem: if information is fragmented, outdated or incorrect, even the most powerful analysis tools lose their effectiveness. In addition, many authorities and companies do not yet have the necessary data governance in place to record and exchange information in a consistent, complete and standardized manner.

Human and technical resources are also limited. Qualified specialists in the fields of data science, AI and financial crime analysis are rare, and outdated IT infrastructures make it difficult to introduce new systems.

Legal uncertainties, particularly with regard to data protection and the Liability in automated decisions, create additional hurdles. Operational risks such as system failures, non-transparent algorithms or misinterpretations of analysis results can impair confidence in the technology.

Cultural barriers should also not be underestimated: Resistance to change, concerns about job relocation and a lack of digital skills among employees often lead to delays.

Finally, the lack of cooperation between supervisory authorities and international partners makes it difficult to develop interoperable, scalable solutions, often resulting in parallel isolated solutions that hinder the comprehensive exchange of information.

Best practices from the EBA toolbox

The EBA identifies a number of success factors that have been derived from previous experience with SupTech projects and are important for both supervisory authorities and supervised entities.

A central basis is the promotion of a Digital-first culturewhich goes beyond pure IT modernization and specifically targets the training of specialists and managers, continuous internal awareness-raising and the integration of digital skills into everyday life. In addition, the EBA recommends the development of robust data strategieswhich, in addition to standardization and interoperability, also contain clear data protection and data security concepts.

Another key element is the use of Pilot projects and regulatory sandboxesto test innovations in a controlled environment and identify risks at an early stage. These test fields are not only used for technology validation, but also for cooperation between the supervisory authority and market participants. The EBA also emphasizes the Demand referenceSupTech tools should be developed specifically to solve concrete supervisory or compliance problems instead of being implemented in a technology-driven manner without a clear use case.

Continuous improvement is achieved through Metrics and feedback loops supported. This includes clearly defined KPIs, regular evaluations and the inclusion of user feedback in order to measure the actual added value of the tools and make adjustments. Finally, the Cross-border cooperation a central criterion for success. Shared platforms, secure data rooms and data protection-friendly technologies such as federated learning make it possible to exchange information across countries and address risks in a coherent manner.

These best practices are not to be understood as one-off measures, but as a dynamic process that must be continuously adapted to technological and regulatory developments.

Conclusion: New era in AML/CFT supervision

The new EBA toolbox marks the beginning of an era in which AML/CFT supervision will become more data-driven, faster and more collaborative. Responsible persons should not only observe this development, but actively shape it. After all, those who prepare their internal processes and systems at an early stage will have a clear advantage in the future AMLA ecosystem. At the same time, dialog with supervisory authorities and data protection experts is crucial in order to clarify legal uncertainties and ensure interoperability.

Link tip: Report on the use of AMLCFT SupTech tools

Aristotelis Zervos is Editorial Director at 2B Advice, a lawyer and journalist with profound expertise in data protection, GDPRIT compliance and AI governance. He regularly publishes in-depth articles on AI regulation, GDPR compliance and risk management. You can find out more about him on his Author profile page.

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