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Fintech solutions offer consumers unparalleled convenience and flexibility, but these benefits often come at a cost. As a general rule, anything that makes financial transactions easier for customers also makes them easier for criminals to exploit.
More and more transactions happen at the tap of a button. However, this has also given rise to a new type of scam known as authorized push payment (APP) fraud, whereby criminals manipulate victims into making real-time payments for things that don’t exist. As a result, APP fraud losses are expected to hit $6.8 billion by 2027.
Artificial intelligence (AI), now squarely on the frontlines of both cybercrime and its prevention, is thus a major focus area for fintechs and financial services organizations. Earlier this year, global payments company MasterCard integrated AI into its fraud-prediction technology to identify, in real-time, compromised credit and debit cards, aiming to replace them before any criminal use can take place.
How can AI help enhance fraud detection?
With the total global cost of online payment fraud – including APP fraud – expected to reach $343 billion by 2027, it’s never been more important for fintechs to integrate proactive measures to address this escalating threat. Nonetheless, with millions of online transactions every day, doing so has become extremely challenging at the required scale.
AI-based solutions aim to close the gap while also accelerating the identification of potentially fraudulent transactions and preventing them from impacting consumers. Like similar solutions, MasterCard’s new AI capabilities incorporate machine learning and the predictive analysis of contextual information to detect suspicious payments in real-time. For instance, if the location or timing of a transaction is unusual, the transaction will be prevented and flagged for manual review.
A more recent innovation in AI for fraud detection and prevention is adaptive learning. While payment providers have already had real-time fraud-prevention measures in place for some time now, they’ve been limited in their abilities to tackle emerging fraud tactics, such as AI-powered social engineering scams. Fortunately, that’s expected to change thanks to adaptive learning, where machine learning models learn continuously from enormous amounts of data to enhance detection accuracy over time.
In the case of MasterCard, the company also uses AI to detect patterns in stolen card data, which is already abundant given there are billions of stolen payment card credentials circling around the dark web marketplaces. These cards can remain undetected for months or even years, until discovered through intensive analysis by fraud prevention teams. However, by the time that happens, there’s a good chance they’ve already been used for fraudulent payments.
The hope is that MasterCard’s use of AI will allow them – as well as other fintechs – to take a more proactive approach to fraud prevention and, in doing so, restore consumer trust in financial services.
