Google Cloud rolls out an AI-powered anti-money laundering tool for banks

The tool is redefining the possibilities of monitoring money laundering activity and enhancing overall financial crime risk detection

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After successfully launching the trial with HSBC, Google Cloud has unveiled its AI-powered tool to revolutionize anti-money laundering efforts in the financial sector. The product leverages the power of AI and machine learning aids banks and other financial institutions in detecting money laundering and reporting suspicious activities.

Money laundering is denoted as one of the costly challenges faced by the financial service sector. The new tool put forward by Google Cloud is redefining the possibilities of monitoring money laundering activity and enhancing overall financial crime risk detection.

According to reports, HSBC, a customer of Google Cloud, successfully used the product, detected 2-4 times more true positive risk, and found the alert volumes reduced by more than 60%. The Group Head of Financial Crime Risk and Compliance at HSBC, Jennifer Calvery, said, “Google Cloud’s Anti Money Laundering AI tool has significantly improved HSBC’s AML detection capability. Google’s models already demonstrate the tremendous potential of machine learning to transform anti-financial crime efforts in the industry at large”.

She further added, “By enhancing our customer monitoring framework with Google Cloud’s sophisticated AI-based product, we have been able to improve the precision of our financial crime detection and reduce alert volumes meaning less investigation time is spent chasing false leads. We have also reduced the processing time required to analyze billions of transactions across millions of accounts from several weeks to a few days.”

How does the tool guard against money laundering?

Money laundering is a grave issue faced by every financial institution, so using the right tool for risk detection is critical. Google Cloud aims to distinguish its tool by doing away with the typical rules-based programming used to set up and maintain AML surveillance programs.

As per the record, the UN estimates around 2-5% of the global GDP, or roughly $2 trillion, is laundered annually, and regardless of billions of dollars invested in the anti-money laundering systems over the recent decades, over 95% of system-generated alerts are closed as false positives in the initial stages of review.

Here Google Cloud’s AI-powered anti-money laundering tool offers a consolidated risk score generated by machine learning as an alternative. Transactional patterns, Know-Your-Customer, and network behavior data form the risk score to identify situations of high-risk retail and commercial customers.

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