Leveraging Google Cloud’s Anti Money Laundering AI with SGR’s Daily Control™ for Enhanced Compliance.

18.07.23

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.

Who uses it already

Google’s AML AI has already been adopted by several financial institutions, including HSBC, Brazil’s Banco Bradesco, and Lunar, a Denmark-based digital bank. The AI has been successful in identifying more risk, more defensibly, with fewer false positives and reduced time per review. This has made it an attractive solution for financial institutions looking to enhance their AML procedures.

Jennifer Shasky Calvery, the group head of financial crime risk and compliance at HSBC and the former top U.S. anti-money-laundering official, said the technology developed by Google Cloud represented a “fundamental paradigm shift in how we detect unusual activity in our customers and their accounts.” By using an AI-first approach, Google Cloud says its technology cut the number of alerts HSBC received by as much as 60%, while increasing their accuracy. HSBC’s “true positives” went up by as much as two to four times, according to data cited by Google.

Rafael Cavalcanti, SVP Data & Analytics at Bradesco said: « As threats become more sophisticated globally and the challenges in fighting money laundering become increasingly complex, we believe in the combination of AI and decision science as the best strategy to detect suspicious activity with more accuracy and efficiency, » continuing with « As one of the largest banks in Brazil with more than 70 million customers, we see the value of Google Cloud’s AML AI product for the financial industry and have greatly enjoyed working with Google Cloud in advancing the industry’s approach to anti-money laundering. »

Comprehensive Review of Google’s AML AI

The Wall Street Journal and Forbes have both reported on the launch of Google’s AML AI, highlighting its potential to revolutionize the way financial institutions handle AML procedures. The AI tool is said to be significantly more efficient than traditional rule-based methods for detecting large-scale money-laundering activities. The UN estimates that 2% to 5% of global GDP is involved in money laundering, linked to illegal activities like human trafficking and terrorism financing.

AML AI provides risk scores based on transaction data, accounts, know-your-customer (KYC) information, and previous suspicious activity, which analysts review in a case management system. During the trial with HSBC, the bank experienced increased positive alerts by two to four times, along with a 60% reduction in false positives, according to HBSC and Google Cloud.

The Wall Street Journal emphasizes the AI’s ability to replace or complement legacy transaction monitoring systems, its explainability to various stakeholders, and its reliance on the data provided by the user for its analysis. Google Cloud’s decision to do away with rule-based inputs to guide what its surveillance tool should be looking for is a bet on AI’s power to solve a problem that has dogged the financial sector for years.

The articles also discuss the challenges of deploying AI as the primary means of detecting money laundering due to regulatory and risk coverage concerns. Google Cloud developed AML AI to offer model governance, extensibility, and secure deployment within the customer’s tenant data.

How to combine this technology with SGR’s Daily Control™

SGR Compliance’s Daily Control™ is a SaaS solution that provides constantly updated datasets (Adverse Media, PEPs, Sanctions, etc.) to enhance due diligence. It allows users to seamlessly incorporate SGR datasets into their existing processes, choosing a suitable approach for their business requirements. The platform offers features such as event-driven screening, batch screening, automated monitoring, and a control center for managing compliance cases.

The integration of Google’s AML AI with Daily Control™ offers a remarkable opportunity to boost the efficiency and effectiveness of AML procedures. The AI’s ability to identify risks with greater accuracy, more defensibly, lower the number of false positives and expedite the review process, combined with Daily Control™’s comprehensive and up-to-date screening information, can provide a robust and holistic approach to AML procedures.

This integration empowers organizations to streamline their AML practices, optimize resource allocation, and ensure compliance with regulatory requirements.

To gain a deeper understanding of how high-quality data drives effective anti-money laundering compliance we recommend reading the insight « The Importance of Quality Data in Anti-Money Laundering Compliance: A Focus on ‘Quality In, Quality Out’« .


Key Takeaways

  • Google’s AML AI is a powerful tool that leverages artificial intelligence to combat money laundering.
  • It is designed to be transparent and understandable to various stakeholders, ensuring trust in its decision-making process and outcomes.
  • The AI can either replace or complement existing transaction monitoring systems, offering flexibility in its integration.
  • The integration of Google’s AML AI with Daily Control™ can provide a comprehensive, efficient, and effective solution to AML procedures.

 

Sources

  1. [Google Cloud Launches Anti-Money Laundering Tool for Banks Betting on the Power of AI – WSJ](https://www.wsj.com/articles/google-cloud-launches-anti-money-laundering-tool-for-banks-betting-on-the-power-of-ai-2512ccce)
  2. [Google Cloud Unleashes AI On Money Laundering Activities After Successful HSBC Trial – Forbes](https://www.forbes.com/sites/moorinsights/2023/06/23/google-cloud-unleashes-ai-on-money-laundering-activities-after)
  3. [Google Cloud Launches AI-Powered Anti Money Laundering Product for Financial Institutions – Google Cloud Press Corner](https://www.googlecloudpresscorner.com/2023-06-21-Google-Cloud-Launches-AI-Powered-Anti-Money-Laundering-Product-for-Financial-Institutions)

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If you are interested in learning more about SGR Compliance and how we can help you manage risk more effectively, please do not hesitate to contact us. We are always here to help, and we look forward to hearing from you soon.

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