The difficulties posed by money laundering and terrorism financing have grown in complexity and scope in an era where the global financial system is becoming more connected and digital. Given this, the Global System for Mobile Telecommunications Association has called for a radical transformation in countries’ approaches to combating these threats.
In the 30-page document made available to The Guardian, AI is described as the theory and development of computer systems able to perform tasks that normally require human intelligence. Examples include tasks such as visual perception, speech recognition, decision-making under uncertainty, learning, and translation between languages.
The report noted that transaction monitoring is the practice of discovering and reporting unusual transactions that could suggest money laundering, terrorism financing or other illegal activity. While traditional detection methods may struggle to keep pace with sophisticated criminal techniques, it is said that AI can analyse vast financial data to identify potential money laundering and terrorism financing activities through machine learning methods.
GSMA noted that it is possible for us to also employ ML and NLP to extract important information and insights about clients from unstructured data, such as social media posts, news articles, or public records. According to the body, AI technologies are in use for AML and CFT compliance, stressing that overall, AI technologies are an integral part of the compliance strategies for institutions in combating money laundering and terrorism financing, with varying degrees of adoption for different technologies.
The difficulties posed by money laundering and terrorism financing have grown in complexity and scope in an era where the global financial system is becoming more connected and digital. Given this, the Global System for Mobile Telecommunications Association has called for a radical transformation in countries’ approaches to combating these threats. It noted that…