Our client is a leading European financial institution, offering banking, wealth management, and payment solutions to their retail and business clientele.

The financial institution’s internal audit team responsible for money laundering wanted to:

• Develop an independent data-driven system to leverage client transaction information
• Intercept high-risk transactions and flag clients not yet reported as suspicious transactions
• Increase the effectiveness of internal control currently based on random samples or selected by experiential triggers

• Limited number of tagged cases corresponding to various money laundering scenarios
• Disparate data sources within the bank
• Limited visibility on suspicious operations among non-customers
• No benchmark of model performance: Not all cases flagged by the model were investigated, making an evaluation of false/true positive cases complex