Revolut launches machine learning to detect card fraud and hits 3 million users

Mobile first bank, Revolut, has unveiled a new fleet of machine learning technology that has already seen a fourfold reduction in card fraud, primarily tackling e-commerce payments, card cloning and card theft.

Its new technology is able to develop insights and predictions into customer behaviour to identify new card fraud patterns such as abnormal spending, without explicit human intervention. If a customer’s payments drastically deviate from their usual spending habits, Revolut is able to automatically freeze card payments until a customer verifies himself from within the Revolut app – saving time and hassle.

Separately, Revolut has just launched new machine learning technology for detecting money laundering, a dynamic mathematical model that calculates a risk score for each user based on their activity history. It processes all transactions in Revolut live and statistically determines the probability of money laundering based on the profile of the user and various features extracted from the transaction.

Revolut’s new fraud detection technology comes at a time when the company is experiencing phenomenal growth and  launching in several international markets. Revolut has now signed up three million customers in Europe and is opening 250,000 new current accounts each month.

I speak with banks all the time, and several of them have already approached us with offers to buy this technology. What we can accurately display in ten minutes would typically take a large bank over an hour to establish with their current manual processes. If you’re on a mission to reach tens of millions of customers and scale your business globally, then you cannot rely solely on manual human processes to effectively protect your customers against financial crime, especially as criminals are becoming more savvy in their tactics.

Nik Storonsky, Founder & CEO of Revolut