cdd-risk-review

Automating customer due diligence (CDD) file reviews involves extracting customer identification, beneficial ownership, and risk rating data to check compliance against the FFIEC BSA/AML Examination Manual. This process identifies gaps and generates review memos with recommended actions.

An event-driven CDD refresh is a compliance review triggered by specific changes in a customer's profile or behavior. It is required alongside new account and periodic refresh reviews to maintain ongoing monitoring standards mandated by the CDD Final Rule.

Yes, you can use Python with pandas and numpy to process CDD PDF files. The extraction analyzes customer identification and beneficial ownership information, verifying risk ratings and ongoing monitoring triggers to ensure regulatory compliance.

The best way to handle periodic CDD refreshes is to automate the review of customer due diligence files against regulatory standards. This approach analyzes risk ratings and monitoring triggers to systematically identify compliance gaps and output recommended actions.

The compliance process supports new account, periodic refresh, and event-driven refresh CDD review types. It analyzes customer identification, beneficial ownership, risk rating, and ongoing monitoring data to ensure adherence to financial regulations.

Yes, automated CDD review analyzes new account files to identify gaps in beneficial ownership and customer identification. It evaluates the extracted data against internal policies and regulatory standards to generate a review memo with recommended actions.