Machine Learning-based Digital Fraud Detection
Payment fraud has a long history and is the most common form of online fraud in the United States and the world. Recently, however, digital fraud has increased so much that it is difficult for many to distinguish the myth from reality.
Faced with the relentless threat of criminals, it has become indispensable to use state-of-the-art systems with learning capabilities, as companies strive to stay ahead. This reflects how organised crime and state-sponsored fraudsters are stepping up their fraud efforts.
The most common approaches to fighting online fraud include rules and prediction models that are no longer up to the complexity of today’s increasingly advanced online threats. The vast majority of new and emerging attacks in the field of digital fraud rely on machine learning and other automation techniques to commit fraud — an old approach to fraud prevention that cannot catch up.
Integrating AI-based platforms to detect online fraud into a high-risk game is a key part of the AI that today enables us to expand online fraud prevention. Digital businesses with a particular business model and their fraud analysts can take results from fraud analyses based on…
