Internal Audit (IA) and Financial Crime Compliance (FCC) has a great opportunity to scale machine learning as the tool to monitor an enterprise-wide anti-money laundering (AML), transaction monitoring, risk scoring, email monitoring, media review, trade risk, anti-bribery, relationship integration, sanctions, subpoenas and more. Monitoring the performance of the processes with quality, false-positive, false-negative and tests further can support advance quality checks to assure the system is optimal.  A strong machine learning program with dashboards available to summarize and export details for any query, investigation, audit and regulatory request is visionary. 

Machine learning is all the need for financial crime compliance as a foundational component to integrate internal and external data into an analytics program that supports the goal, anti-money laundering and anti-crime.  

Integrated software and programs enable the medium to grow machine learning algorithms and output summarized dashboards, yet skilled data scientists and subject matter experts in the data and regulations are the shepherds.