Google Cloud has announced the launch of Anti Money Laundering AI (AML AI), an artificial intelligence (AI)-powered product designed to help global financial institutions more effectively and efficiently detect money laundering.
Google Cloud’s AML AI provides a consolidated machine learning (ML)-generated customer risk score as an alternative to rules-based transaction alerting. The risk score is based on the bank’s data including transactional patterns, network behavior, and Know Your Customer (KYC) data to identify instances and groups of high-risk retail and commercial customers. The product can adapt to changes in underlying data, delivering more accurate results, which increases overall program effectiveness and improves operational efficiency.
Google Cloud’s AML AI is using proprietary ML technology as well as Google Cloud technologies, such as Vertex AI and BigQuery. The product handles the complexities of running ML at scale, while also providing enriched explanations of the outputs to enable financial institutions to expedite the investigation workflow and improve the customer experience. To date, the solution has been put in production across several geographical regulatory jurisdictions.
“Google is a pioneer in AI, and now we’re making our tools, technologies, and expertise available to solve one of the biggest and most costly challenges in the financial services industry,” said Thomas Kurian, CEO of Google Cloud. “Building on our commitment to bring AI-powered innovation to the financial services industry, we are launching Google Cloud’s AML AI to help financial institutions more accurately and efficiently identify AML risk while enhancing business operations and governance.”
Google Cloud’s AML AI product delivers the following benefits:
- Increased risk detection: AML AI can outperform current systems in detecting financial crime risk. Google Cloud customer HSBC found that they can now detect two to four times more true positive risk, enhancing their ability to identify and prevent money laundering activities.
- Lower operational costs: AML AI minimizes wasted investigator time by reducing alert volumes and providing explainable outputs that speed up individual investigations. In fact, HSBC saw alert volumes decrease by more than 60%.
- Improved governance and defensibility: AML AI provides financial institutions with auditable and explainable outputs to support internal risk management. This approach is now in production in several geographies, each with their own regulatory requirements.
- Improved customer experience: By increasing precision and significantly reducing false positives, AML AI minimizes the need to engage with customers for additional compliance verification checks.
AML AI can help customers reduce their operational costs while simultaneously improving the strength of their AML program. In the future, Google Cloud plans to provide Generative AI foundations for the financial services industry with the goal of boosting employee productivity, for example, to reduce the time needed for an analyst to investigate potential suspicious activity.
