Fraud rates in the UK have been climbing to new record heights, so much so that the UK’s industry body UK Finance has been talking for the first time about fraud posing a national security threat. According to latest figures, £754m was stolen from bank customers during the first half of this year - a 30% rise compared to the same period in 2020.

So-called Authorised Push Payment Fraud (APP fraud) - where fraudsters target unsuspecting customers through scams or phishing attacks – is rising dramatically. APP fraud losses increased 71% during the first half of 2021 - surpassing the amount of money stolen through card fraud for the first time.

Latest UK fraud figures need to be a wake-up call for the industry

The rise of new payment types and digital experiences has presented fraudsters with unique new opportunities to commit crimes. Cybercriminals are increasingly connected and organised, and can impersonate consumers’ digital personas from anywhere, anytime. This must be a wake-up call for financial institutions (FIs). The industry must find new ways to collaborate to detect illicit activity if we are to win the battle against fraud.

Collaborate to combat the threat

From regulators to law enforcement to banks, every party involved in combating and prosecuting fraud must collaborate effectively. One solution that will yield extremely effective results is harnessing the benefits of sharing network intelligence. By linking the intelligence of organisations, individual players can build fraud strategies based on learnings from a consortium of shared signals, i.e., prior knowledge of where fraudsters have been before. In an ideal world, members would connect to the consortium via a central body, such as a central bank, creating a community that shares real-time fraud patterns.

To put this into perspective, an example of a signal is the number of transactions someone makes with a specific payment option within three hours. Most consumers are not in a rush to perform as many transactions as possible in a short time frame. When you compare the number of legitimate transactions to fraudulent ones, as the count of transactions within three hours increases, the probability that it is legitimate decreases rapidly.

Harnessing network intelligence also takes advantage of a hybrid-type Machine Learning (ML) approach - one that leverages the best of every player’s approaches. It enables FIs to maintain the strength of their custom-type signals, complemented by signals exchanged with their community, as well as signals from third-party fraud intelligence sources.

Adopting such a data-driven insight allows banks, processors, acquirers, and networks to securely share and consume industry-wide fraud signals to feed their ML models alongside proprietary data.

In the fight against fraud, it pays to be prepared - and predictive, as fraudsters will always be on the lookout for new ways to commit crimes. So, collaboration is key. Providing FIs access to a vastly expanded community of fraud and risk data, dramatically enhances the way the industry can add value and protect their customers. Ultimately, it will stop fraudsters from getting the upper hand.