9.6.3.1 Anti-Money Laundering Pattern Data Discovery

Anti-money laundering (AML) refers to the laws, regulations, and procedures intended to prevent criminals from disguising illegally obtained funds as legitimate income.

The AML Pattern Data Discovery is a scenario that helps you to see new financial crime patterns. These patterns enable you to easily explore any relationship among entities in real-time to extract valuable insights from your data.

This data discovery pattern quickly uncovers emerging, complex money laundering and terrorist financing threats with network and entity generation processes that automatically build network diagrams and reveal hidden relationships. The advanced graph analytics enables entity resolution by looking at multiple data sources and references to a customer, then accounting for inconsistencies, errors, abbreviations, and incomplete records to help determine whether they relate to the same entity.

The scenario includes the following actions that you can perform for the data discovery:

• Creating a Notebook or Model for Your Financial Crime Discovery
• Loading a Financial Crime Graph
• Insight to Customize and Arrange Data in a Graph
• Customizing the Nodes and Edges of the Graph