The financial landscape is witnessing a seismic shift with the advent of instant payments, known as real-time payments (RTP).
In a recent post by Hawk AI, the firm asked how banks can use AI to manage instant payment fraud risk.
The EU’s new regulations mandate banks to offer instant payments, mirroring the US’s launch of the FedNow Service. Currently, over 300 banks and credit unions have embraced FedNow. By 2027, it’s expected that 27.8% of all electronic payments globally will be in real-time, a significant increase from 18% in the previous year.
However, this convenience brings heightened risks of fraud, money laundering, and terrorist financing. The quick pace of instant payments equates to rapid fraud, necessitating real-time monitoring by banks to safeguard their customers and financial health.
In response to these challenges, banks are required to bolster their fraud prevention measures. The EU’s new rules necessitate that instant payment providers verify the match between the beneficiary’s IBAN and name, alerting payers to potential errors or fraud risks. This regulation shifts the financial burden of fraud onto banks, even when the payee is not their customer, escalating the stakes for fraud prevention.
The criticality of real-time fraud detection has never been more apparent. Banks are now under a tight ten-second window to screen payments for risks, including money laundering and terrorist financing. Failure to identify fraud in this narrow timeframe makes the bank liable for the losses incurred.
UK’s regulations have already set a precedent by holding both sender and receiver financial institutions accountable for fraud damages. Banks must now integrate anti-money laundering (AML) and anti-fraud solutions to tackle money mule transactions and suspicious activities effectively. Moreover, instant payment fraud often involves unsuspecting victims, making it imperative for banks to scrutinize payment counterparties meticulously.
Maximilian Riege, Chief Risk Officer at Hawk AI, explains, “While the victim plays a necessary part in completing the fraud, the transaction itself is not criminal. This differentiates it from typical money laundering activities, adding complexity to the bank’s role in detecting and stopping fraudulent transactions.”
To combat instant payment fraud, banks must leverage AI and technology for speed, precision, scalability, pattern and anomaly detection, and reducing false positives. Immediate and precise checks are crucial, given the ten-second window for processing instant payments. Moreover, the increase in transaction volumes demands scalable solutions.
AI’s capability to predict known fraud patterns and identify emerging ones is invaluable. The technology can discern deviations in transactions from billions of others, offering a robust solution for fraud detection at scale. Reducing false positives is equally important to maintain customer satisfaction and streamline the instant payment process.
Consider a scenario where a bank, following the introduction of instant payments, experiences a spike in fraud losses. In response, it implements scalable, real-time AI models to scrutinize transactions for fraudulent patterns, effectively reducing fraud losses, enhancing customer experience, and conserving investigative resources.
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