In this analysis, we will explore the functionalities and capabilities of Google Cloud’s Anti Money Laundering AI (AML AI) and how organizations can maximize the benefits of this technology by combining it with Daily Control™.
Understanding Google’s AML AI
Google Cloud’s Anti Money Laundering AI (AML AI) is an advanced tool that utilizes artificial intelligence to address the challenge of money laundering. It operates as an API that evaluates AML risk, offering a method for identifying potential suspicious activities. Developed to cater to both retail and commercial banking sectors, it is structured to meet model governance requirements, ensuring its compatibility with regulatory standards. A significant aspect of Google’s AML AI is its explainability. It is designed to be transparent, providing clear insights to a variety of stakeholders, including analysts, risk managers, auditors, and regulators.
How Google AML AI Works
As an alternative to rule-based transaction alerting, Google Cloud’s AML AI provides a consolidated machine learning (ML)-generated customer risk score.
The risk score is based on the Financial Institution’s data including transactional patterns, network behaviour, and Know Your Customer (KYC) information. This enables the identification of high-risk instances and groups among both retail and commercial customers. What sets this product apart is its ability to adapt to changes in underlying data, delivering more accurate results, which increases overall program effectiveness and improves operational efficiency.
Google Cloud’s AML AI uses 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.