Paper 2023/649
FinTracer: A privacy-preserving mechanism for tracing electronic money
, RMIT University, Australian National UniversityAbstract
Information sharing between financial institutions can uncover complex financial crimes such as money laundering and fraud. However, such information sharing is often not possible due to privacy and commercial considerations, and criminals can exploit this intelligence gap in order to hide their activities by distributing them between institutions, a form of the practice known as ``layering''. We describe an algorithm that allows financial intelligence analysts to trace the flow of funds in suspicious transactions across financial institutions, without this impinging on the privacy of uninvolved individuals and without breaching the tipping off offence provisions between financial institutions. The algorithm is lightweight, allowing it to work even at nation-scale, as well as for it to be used as a building-block in the construction of more sophisticated algorithms for the detection of complex crime typologies within the financial data. We prove the algorithm's scalability by timing measurements done over a full-sized deployment.
Metadata
- Available format(s)
-
PDF
- Category
- Cryptographic protocols
- Publication info
- Preprint.
- Keywords
- anti money launderingfinancial crimegraph analyticshomomorphic encryptionprivate graph analysis
- Contact author(s)
-
michael brand @ rmit edu au
hamish ivey-law @ anu edu au
tania churchill @ anu edu au - History
- 2023-05-11: approved
- 2023-05-08: received
- See all versions
- Short URL
- https://ia.cr/2023/649
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2023/649,
author = {Michael Brand and Hamish Ivey-Law and Tania Churchill},
title = {{FinTracer}: A privacy-preserving mechanism for tracing electronic money},
howpublished = {Cryptology {ePrint} Archive, Paper 2023/649},
year = {2023},
url = {https://eprint.iacr.org/2023/649}
}
