Crowe DCI

Monitor Anti-money-laundering (AML) Risk While Strengthening Customer Relationships

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Financial institutions are required to establish criteria for monitoring accounts and relationships that pose greater than normal risk of Bank Secrecy Act and AML violations. To comply with this requirement and provide a more positive customer experience at the same time, Crowe Horwath LLP has developed the Crowe DCI framework that enables banks to integrate customer identification programs, customer risk rating, and AML enhanced due diligence activities into account-opening processes.

The Crowe DCI framework serves as an effective high-risk customer management technology and an easy-to-use AML case management tool. It supports risk-based, automated customer due diligence and has been applied successfully in multiple AML model validations.

The Web-based Crowe DCI architecture allows the solution to be embedded in your bank’s account-opening platform to allow seamless customer data collection. Crowe DCI also integrates with your transaction monitoring system, data warehouse, and common third-party information sources to provide a complete picture of risk.

 
Crowe DCI

What Sets Apart the Crowe DCI Solution

The Crowe DCI risk elements and scoring tables are tailored to reflect each institution’s particular risk assessment. The solution then is implemented using proven Crowe AML implementation methodology.

The Crowe DCI framework draws on the extensive experience of the Crowe financial crime services group. Features include:

  • Dynamic interview templates that gather customer due diligence information along with valuable customer insights
  • A risk-based, rules-driven design to produce a more accurate view of customers and the risk posed to the institution
  • The ability to create prospect and noncustomer entity profiles in a manner similar to customer entities
  • A flexible, industry-driven risk model library and scenario analyzer
  • Multistage case management with embedded investigation work steps
  • Customer activity collection including expected-to-actual activity comparisons
  • Collecting beneficial ownership information from covered entities