Google Cloud, a division of Alphabet, has introduced its revolutionary Anti Money Laundering AI, following a successful trial with HSBC. This innovative AI-powered tool aims to transform anti-money laundering efforts within the financial sector by harnessing the capabilities of AI and machine learning. It assists banks and other financial institutions in detecting instances of money laundering and reporting suspicious activities.
Money laundering poses significant challenges to the financial services sector. However, Google Cloud’s new tool is poised to redefine the landscape of monitoring money laundering activities and bolster overall financial crime risk detection.
Reports indicate that HSBC, a Google Cloud customer, achieved impressive results using the product. They experienced 2-4 times more accurate identification of risk and observed a reduction of over 60% in alert volumes. Jennifer Calvery, Group Head of Financial Crime Risk and Compliance at HSBC, expressed her satisfaction with the Anti Money Laundering AI, stating that it significantly improved their AML detection capabilities. She further highlighted the immense potential of machine learning in transforming anti-financial crime efforts across the industry.
Calvery added that by incorporating Google Cloud’s sophisticated AI-based product into their customer monitoring framework, HSBC was able to enhance the precision of financial crime detection and reduce the need to investigate false leads. The processing time required to analyze billions of transactions across millions of accounts was also significantly reduced, from several weeks to just a few days.
How does this tool combat 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 tool offers a consolidated risk score generated by machine learning as an alternative. Transactional patterns, Know-Your-Customer and network behaviour data form the risk score to identify situations of high-risk retail and commercial customers.
