Graph Analysis and Visualization for Anti-Money Laundering

An adequate Anti – Money Laundering (AML) program is a key regulatory requirement for financial institutions. Graph analysis can be used to drive detection of suspicious activity and graph visualization can be used to provide insight to AML investigators about relationships which would otherwise be difficult to detect or understand.

The speakers will walk through a case study about the use of graph analysis in an AML program at a large financial institution, which will encompass:

The types of graph analysis that can be relevant to money laundering detection (payment, account, shared customer attributes etc.) and to analyze financial data
Issues in presenting useful interactive graph visualizations, especially of financial data
Examples of graph visualizations displaying financial relationships that can't easily be conceptualized through traditional methods

Currently a Director within PwC Advisory and co-leader of the Forensics Services Data Analytics practice. A client service engagement leader with a focus on the financial services industry. Clients include major financial institutions and regional banks. Across 10 years with PwC, primarily focused on anti-money laundering, third party risk management, regulatory and management reporting, payments processing and finance transformation; within these areas, successfully leveraged technology to provide impactful and effective solutions for clients. Additionally, led the design and implementation of multiple large scale web based applications for regulatory compliance purposes.

Evan Clark is a Senior Associate in the Forensic Services Data Analytics practice. He focuses on data analysis and visualization for investigations and regulatory compliance and has experience with financial modeling for litigation and business interruption claims.