Labels:
machine-learning secure-learning multi-party-computation

Description

Individually, major banks are facing significant challenges with respect to detecting money laundering. Due to privacy regulations and data confidentiality banks cannot readily share data, which makes it challenging to collaborate. The goal of this joint research project is to develop a Proof of Concept Multi-Party Computation solution for collaborative monitoring and detection of money laundering.

Major banks are facing significant challenges with respect to detecting money laundering. The amounts of money being laundered are potentially huge and difficult to detect by a single bank as criminals often make use of transactions via different banks on a national and international level, and via cryptocurrency exchanges. Due to privacy regulations and data confidentiality banks cannot readily share data, which makes it challenging to collaborate. One approach could be to perform Anti Money Laundering (AML) analyses on a data silo with pseudonymized transaction data of multiple bank. However, such an approach faces challenges on privacy concerns and legislation. Additionally, it is unlikely that many foreign or international banks will collaborate like this on a short term. It would be better to have a decentralized solution for these purposes.

The goal of this joint research project is to develop a pilots and Proof of Concepts solution for collaborative monitoring and detection of money laundering using Privacy Enhancing Technologies, such as Multi-Party Computation, synthetic data and Federated Learning. Furthermore we investigate the transition to include this AML capability in daily operations. MPC consists of innovative cryptographic techniques that offer opportunities for organizations to jointly analyze their data without sharing or revealing this data to anyone. This program can be seen as a Regtech approach and contributes to a solution for the (legal) data confidentiality issues that are faced in data sharing initiatives. The consortium is open for other (international) financial institutions, to join the consortium to collaboratively fight money laundering without sharing sensitive data.

Contact

  • Alex Sangers, Project Manager Privacy Enhancing Technologies, e-mail: alex.sangers@tno.nl