Overview

ML4AML is a Machine Learning Module within Compliance Studio that has been tailored to address specific use cases in the AML domain using ML4AML APIs.

Module Hierarchy

The following figure illustrates the approach that is used for modularizing the ML4AML module.

ML4AML Module Hierarchy

ML4AML Modules

The module implements user interface API’s for all the possible Machine Learning (ML) operations. Here are the details:

  • aif: This class implements user interface API’s for ML.

  • aif_utility: The utility class contains reusable components that interacts with Compliance Studio.

  • amles: The amles class is a special use case of supervised learning for anti-money laundering for event scoring (AMLES).

  • supervised: The supervised class contain methods required for supervised learning. It inherits methods from the aif and aif_utility classes.

  • unsupervised: The unsupervised class contain methods required for the customer segmentation usecase. It inherits methods from the aif class.