Google is working to offer banks a form of Artificial intelligence capable of combating money laundering.
According to the website of Google Cloudtale AI model will be able to identify suspicious and potentially fraudulent activities, quickly and effectively.
For banking institutions, all this means reduced verification times e lower operating costs, with a financial system that, in the medium to long term, could become much safer overall. While few companies currently have access to this innovative AI system, it is likely to be a real trailblazer for highly efficient automated banking checks.
To reveal more details about that system have been Julie Chang e Dylan Tokarrespectively audio producer and journalist at the Wall Street Journal.
Tokar revealed that Google Cloud developed the anti-money laundering program, differentiating it from other AI-based banking solutions due to its “manually defined rules“. While other platforms are based on complex human parameters, Google’s technology simplifies this whole process.
Money laundering: Google provides a very powerful tool to banks
According to Tokar, the creation of rules by humans often leads to false positives which require in-depth investigations, making checks cumbersome and problematic.
Through its AI model, Google Cloud seeks to streamline this process by reducing human input and identifying alerts that actually require investigation. According to what has been made public, the AI model in question he has been training for three years through banking data, trying to learn as much as possible about the financial world.
Google Cloud, again through its official website, has outlined the information that the AI model will analyze, including transaction details, information on the accounts involvedthe customer relationsi corporate data and much more. This comprehensive approach allows AI to identify patterns and anomalies that can be traced back to money laundering activities.
As already mentioned, Google is currently testing AI on a very limited number of institutions. In particular, HSBCrecorded a significant reduction in false positives (about 60%) and an increase in true positives (with cases more than doubling). This demonstrates the enormous potential of this control system.