Machine learning plays a pivotal role in effective fraud prevention systems. In this article, learn how machine learning can significantly improve your business' ability to stop fraud attacks. With the recent surge in e-commerce usage globally, the possibility of an online fraud attack is at an all-time high. This would represent an 18% increase in fraud losses compared to the US$17.5 billion recorded in 2020. Customers want to have the assurance that they can purchase products without experiencing a false decline, and merchants want to feel that they can trust the legitimacy of new incoming transactions.

Describing how his company's fraud prediction system is like an unaccompanied child visiting a zoo, is when Wally Wang becomes the most animated… and the unsupervised machine-learning approach starts to make sense: "There's no mom to teach a child what a tiger is. The child by intelligence will automatically get the point of how to recognize a tiger or a goose. The connection will be built by the child. That's how the AI part plays here, the algorithm does the detection… We build up a model, making the child more intelligent, to be able to tell automatically when an animal is evolving into another species." DataVisor uses unsupervised machine learning to predict fraud attacks on companies.

ComeOn, a world-leading online gaming platform, has agreed a partnership with Featurespace, the gaming sector's number one machine learning fraud prevention company. The collaboration will see Featurespace's ARIC platform integrated into ComeOn's system to improve player protection from fraud attacks, without impacting the customer experience. Featurespace was created out of Cambridge University's Engineering Department, co-founded by world-renowned experts in applied statistics, Professor Bill Fitzgerald and Dave Excell. The agreement further underlines ComeOn's commitment to innovation and continues to put the customer at the heart of the ComeOn player experience. Featurespace is the world-leader in Adaptive Behavioural Analytics and creator of the ARIC platform, a machine learning software system developed out of the University of Cambridge.

The UK's National Crime Agency recently warned that businesses and law enforcement agencies are losing the'cyber arms race." One of the key threats was found to be fraud, with 700,000 cases contributing to the 2.46 million'cyber incidents' of 2015. Of real concern was the NCA finding that cyber criminals remain one step ahead in terms of technical capabilities – but that is beginning to change. The UK government has pledged to spend 1.9 billion on cyber defences over the next five years, with businesses and law enforcement setting up networks and shared threat intelligence in order to fight evolving and increasing cyber threats. There is also a renewed focus on the technologies used to fight cyber crime, with one company deploying machine learning and behavioural analytics in the fight against fraud. British company Featurespace uses adaptive behavioural analytics and real-time machine learning in order to detect fraud in the financial services sector.