The Royal United Services Institute (RUSI) Future of Financial Intelligence Sharing (FFIS) is currently carrying out a research project into “The Role of Privacy Preserving Data Analytics in the Detection and Prevention of Financial Crime”. Privitar sits on the project’s Research Technical Advisory Group.
The project aims to explore specific privacy enhancing technology (PET) use-cases relevant to financial information-sharing partnerships to understand how privacy enhancing technology and advanced analytics, in combination, may contribute to increased effectiveness of information-sharing for Anti-Money Laundering (AML) and Counter-Terrorism Financing (CTF) purposes, and to examine the implications of such technologies in terms of both additional privacy protections and intrusions.
The project will provide an international comparative study looking at:
- Describing the technical ecosystem. What technical capabilities exist or are under development in the field of privacy preserving analytics with the potential to support AML and financial crime prevention objectives?
- Exploring relevant use-cases. What current and potential use-cases exist for privacy preserving analytics in AML and financial crime prevention; with a particular focus on the relevance to public/private information-sharing (and associated private/private information sharing) within financial information-sharing partnerships?
- Identifying privacy implications. What are the implications of these AML and financial crime prevention use-cases in terms of enabling both privacy protections and privacy intrusions?
- Understanding adoption challenges. What key technical, legal, policy, regulatory and cultural issues (considering both AML and data privacy issues) may affect the utilisation of privacy preserving analytics for AML and financial crime prevention purposes in the target countries?
The study will seek to provide greater clarity on the link between technical capabilities for sharing, specific use-cases and wider policy, legal, cultural, data protection and data governance considerations. The findings of the research project will be published in early 2021.