Keynote – Privacy-preserving analytics for secure collaborative detection of financial crime (TNO)

Plenary

In the fight against financial crime, collaboration between banks is key. At the same time, protection of customer privacy is more important than ever. Banks are looking for ways to balance between privacy and value in their detection techniques. Privacy-enhancing cryptographic techniques, which lately have been moving from academics to real-world applications, can help maintaining this balance. These techniques enable collaborative analysis on sensitive data, while keeping the confidential and personal data private.

In a shared research project with ABN Amro and Rabobank, TNO is currently developing a proof-of-concept for Dutch banks for collaborative anti money laundering using Secure Multi-Party Computation (MPC). By applying state-of-the-art cryptographic techniques, banks could collaboratively identify exposure to high-risk cash or cryptocurrency deposits through inter-bank transactions.

During this talk, Marie Beth van Egmond, scientist at TNO, will give an introduction into these privacy-preserving techniques, demonstrate a proof-of-concept for collaborative money laundering detection and explain how privacy-preserving analytics can be applied for new opportunities for the Dutch banks.

Plenary