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BayesAML

The capability to identify customers with high risk profiles has a positive impact on an institution’s ability to
mitigate and manage risk. BayesAML predictive analytics tool employs a genuine risk-based approach to
identifying high risk profiles and behavior, and alerts users to suspicious transactions to prevent
money laundering or financing of terrorism.

BayesAML

With an estimated that 3%-5% of global GDP laundered every year, regulations now require commercial and financial entities to “know their customers” and to thoroughly assess, classify and monitor customer transactions for signs of money laundering.

BayesAML analytics provides insurers, banks, casinos and other at-risk entities with a genuine risk-based approach to anti-money laundering. Whether used in connection with new accounts or ongoing customer and transaction monitoring, real-time BayesAML alerts users to suspicious activity and contains a workflow procedure to advise them about the next best steps to take to disprove or confirm suspicions.

BayesAML takes customer assessment and transaction monitoring to a new level and effectively protects against suspicious customers and transactions and their negative effects on solvency and compliance.

Benefits of BayesAML:

Combines expert knowledge and historical data

Handles missing values and calculates risk using uncertain information

Efficient inference engine supports real-time risk identification

Models are easy to develop, extend and change

Integration is straight forward

Intuitive graphical models make it easy to communicate about the connections between money laundering risk, customers, products and transactions

BayesAML Whitepaper

Learn more about BayesAML in our White Paper

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  • Products
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    • BayesAML
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