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USE CASE

Anti-Money Laundering

Objective

  • Leverage ML to more accurately spot suspicious and criminal behavior. 

  • Balance compliance and cost by assessing risk of customers, enforcing anti-corruption laws and managing your reputation. 

  • Ensure complete transparency to meet regulatory needs.

Outcome

Business Value

  • Leverage ML to more accurately spot suspicious and criminal behavior. 

  • Balance compliance and cost by assessing risk of customers, enforcing anti-corruption laws and managing your reputation. 

  • Ensure complete transparency to meet regulatory needs. 

  • Fill rule gaps by learning new features and money laundering patterns automatically to implement new rules in your upstream rules-based AML system

H2O's AI and Data Approaches

  • Pattern-based AI detection to find anomalous patterns

  • Consensus modeling

  • Behavior profiling

  • AML Random Forest that can ingest alerts from 3rd party rules engines

  • Probablistic matching engines

Anti Money Laundering Anti Money Laundering

Resources

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