Next-generation AML is coming to the forefront as the financial services industry goes through massive digital transformation and as regulators expand their definition of reasonable control and governance. Robotics, semantic analysis and artificial intelligence,particularly machine learning, will be central to this evolution. Instead of reacting to past information, machine learning delivers a forward-looking advantage. You can distill new data elements that weren’t previously available for AML models. Let the computer uncover patterns the human eye would never see. Validate those insights and feed the results back into modeling efforts. The more training a model gets with feedback data, the smarter it becomes and the less tuning it requires. Not ready to give up your trusted rules? Adopting machine learning doesn't mean you have to abandon established ways of working. The right route for an organization's AML modeling might be a complementary approach, a hybrid of rules and predictive models.

Additional resources
◉ How AI and Machine Learning Are Redefining Anti-Money Laundering – [ Ссылка ]
◉ How SAS Delivers Anti-Money Laundering/CFT Compliance Solutions – [ Ссылка ]
◉ The SAS Viya Advantage – [ Ссылка ]
◉ SAS News & Announcements – [ Ссылка ]


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