Google claims the new tools are far more efficient than traditional rules-based approaches at detecting money laundering at scale.
Google Cloud recently announced the launch of its “Anti Money Laundering AI” (AMLAI) service after a successful trial with London-based financial services group HSBC.
AMLAI uses machine learning to create risk profiles, monitor transactions, and analyze data. Per a blog post from Google Cloud:
“AI transaction monitoring replaces the manually defined, rules-based approach and harnesses the power of financial institutions’ own data to train advanced machine learning (ML) models to provide a comprehensive view of risk scores.”
In practice, Google Cloud claims its trial partner, HSBC, saw an increase of two to four times the number of positive alerts and a 60% reduction in false positives.
The service’s cost will vary depending on the number of customers serviced daily with the AML and risk scoring systems and how many customers are included in the training dataset used to spin the model up.
AMLAI’s launch signifies the furtherance of Google and Google Cloud’s ambitions in the fintech space. While the current AI zeitgeist centers around generative AI products such as Google’s Bard chatbot, the company has quietly been making its presence felt as both a fintech developer and banking services vendor.
Related: Google Cloud launches free courses to help users build their own GPT-style AI
During the COVID-19 pandemic, Google rapidly deployed a paycheck protection program loan processing tool. Over the years, the company has dabbled in alternative payment solutions such as its widely-adopted Google Pay service and the advent of Google-sponsored debit cards featuring NFC connectivity.
Google’s further involvement in the anti-money laundering sector could be a positive sign for the growing industry. According to an analysis from BlueWeave consulting, the global AML market size was estimated at roughly $3 billion in 2022 and is expected to reach nearly $8 billion by the decade’s end.
Mitigating factors causing the projected growth include the rise of non-traditional payments, an ever-changing regulatory landscape, and a steadily creeping increase in the number of money laundering cases globally.
