The risk of money laundering spans the entire financial services ecosystem - banks, payment providers and newer cryptocurrencies, such as Bitcoin and Ripple and more. Given how much financial activity occurs every second, everyday, it’s important for banks and financial organizations to develop a robust...
A traditional AML solution would not flag an alert for this new customer. However, graph-based features dig deeper to find that new account shares a phone number with several customers with SARs. The graph-based solution creates a new AML alert missed by the traditional AML...
.main_body li { list-style-position: inside; margin-left: 40px; text-indent: -1.5em; color: #606060; font-size: 90%; } On June 3 2018, the Commonwealth Bank of Australia was fined $700 million for AML non-compliance. Some of the problem areas at the bank included: ...
Graph analytics is an ideal technology to support AML. Graphs overcome the challenge of uncovering the relationships in massive, complex and interconnect data. The graph model is designed from the ground up to treat relationships as first-class citizens. This provides a structure that natively embraces...
You know a technology has reached a tipping point when your kids ask about it. This happened recently when my eighth grade daughter asked, “What is Machine Learning and why is it so important?”. Answering her question, I explained how Machine Learning is part of AI,...
Today, criminals are using extremely sophisticated, ever-adapting tactics to bypass traditional anti-fraud solutions for money laundering. Any organization facilitating financial transactions – including non-bank money service businesses such as digital/mobile payment services, life insurers and retailers, to name a few – falls within the scope...
