How the Anti-TrustRank Algorithm Can Help to Protect the Reputation of Financial Institutions

摘要

When financial institutions are found to have their customers conduct money laundering through them, they are subjected to large fines. Moreover, the reputation of those institutions suffers greatly through public exposure. Consequently, financial institutions invest significant resources in building systems to automatically detect money laundering in order to minimize the negative impact of money launderers on their reputation. This paper investigates a graph algorithm called Anti-TrustRank and demonstrates how it can be used to identify money launderers. Our approach to using Anti-TrustRank is not replacing money laundering detection systems, rather is generating additional inputs to feed into such systems in order to improve their overall detection accuracy.