Anti-money laundering look back review

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A leading credit cards company identifies and investigates their customers for an anti money laundering transaction monitoring look back review.

Client's challenge

PwC assisted a leading payments company with conducting an investigation to identify and examine suspicious customers in accordance with anti-money laundering regulations. Large volumes of customer and transaction data and no prior analytical expertise in this field created significant challenges for the client.

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PwC's solution

  • Enhanced traditional AML rules by uncovering instances of suspicious account activities and behaviors hidden within terabytes of transaction and customer data.

  • Developed graph search tool to identify all direct and indirect customer and product connections for each customer - explored 90M entities and 180M relationships to quantify customer account structures and identify risky topologies.
    Analyzed a data set of close to 1T transactions to develop a metric to identify suspicious customer and merchant relationships based on relationship strength relative to other cardholders.

  • Matched customer transaction sequences to  AML risk patterns that capture specific instances of risky behavior, eliminating false positives.

  • Developed an algorithm to match duplicate customer entries caused by name and address changes as well as duplicate account applications - eliminating over 10K duplicate customers records.

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Impact on client’s business

  • Reduced the number of false positives to a quarter of what was initially estimated by applying advanced analytical techniques such as nPath, network, and segmentation.

  • Reduced the time required for manual investigations through increased visibility into the suspicious activities and customer/account relationships.

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How PwC can help your business

PwC’s financial services data analytics practice is comprised of more than 200 professionals offering a full range of advisory solutions across: financial risk modeling, risk analytics, customer analytics, data analytics strategy and organization, and data analytics technology. 

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Julien Courbe

Julien Courbe

Financial Services Leader, PwC US

Anand Rao

Anand Rao

Global & US Artificial Intelligence and US Data & Analytics Leader, PwC US

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