Artificial intelligence can play a big role in the defense against money laundering for its ability to:
- Automate tasks that formerly required human intervention, such as the disposition of alerts.
- Detect more risk and effectively prioritize it with sophisticated analytics techniques.
- Provide richer context for investigations.
Despite the potential, the financial services industry has been slow to adopt machine learning techniques for Anti-Money Laundering (AML). This paper explains what machine learning can do, presents six practical use cases and shows how SAS can help.
Click on the button below to download this SAS whitepaper to look at some ways machine learning is being put to use for AML, and in the process redefine AML
