Developing an effective fraud toolkit for instant payment
Global adoption of instant payments is accelerating thanks to a growing demand for faster, more cost-effective payment capabilities. Datos Insights reports that 90% of European business organizations consider instant payments an important financial function for improving customer satisfaction, cash flow management and payroll efficiency.
What often goes unsaid in the discussion surrounding instant payments is the risk of fraud. The general industry assumption is that instant payments are more secure and far more adverse to tampering than traditional payment rails. As it turns out, this attitude isn’t unwarranted. Business respondents to a recent PYMNTS Intelligence report indicated only a 2% fraud rate on instant payments compared to rates of 63% when paying with checks. The question is, will the resistance to fraud last?
At present, layered encryption features and critical verification tools, such as Confirmation of Payee (CoP), make faster payments relatively secure. However, fraudsters are hard at work, using the lightning-fast settlement speeds of instant payments to batter the current defenses, and banks will need an all-new toolkit to protect against evolving fraud risks.
A wolf is waiting at the door – criminals develop new tactics
Uptake of instant payments continues to grow. In the EU alone, McKinsey & Company estimated an increase in the number of instant payments from around 3 billion at the end of 2023 to 30 billion by 2028, an average annual growth rate of 50 percent. For European banks, regulatory mandates are supporting that level of growth with real-time clearing platforms. Banks realize lower transaction costs, compared to legacy batch systems, as well as the option to layer on fee services that further drive revenue growth.
But a wolf is waiting at the door, ready to steal profitability directly from bank balance sheets. Employing a familiar bag of tricks, fraudsters are attacking instant payments and exploiting rapid settlement features in unexpected ways. The most prominent is the shift from large, one-off payments to low value transactions executed at high volumes.
Since traditional fraud systems were built to flag unusually large transfers or sudden large-scale changes in account balances, this approach is effective, easily outmaneuvering legacy controls. Data from industry body UK Finance shows that losses from unauthorized transactions increased by 2% in 2024 to £722 million, with a 14% increase in the total number of cases to 3.13 million.
Given the speed of instant payments and the growing complexity of fraud schemes, risk approaches that require long post transaction windows will become powerless as fraudsters put emerging technology to the test. UK Finance reveals that criminals are utilizing agentic AI at an ever-increasing pace, simplifying and cutting the cost of fraud schemes in the process. To fight fire with fire, banks will also need to employ the speed and power of AI to keep fraudsters in check and protect instant payment integrity, as well as bank profitability.
Creating the ultimate fraud toolkit
Many traditional risk assessments gather customer data and compare it against transaction activity, but identifying fraud in real-time will require deeper behavioral analysis and introspection. AI is rapidly moving the needle toward tighter controls, creating dynamic customer profiles that update in real time. While traditional profiles are based on known behavior – such as who the customer pays and when transactions are typically made – AI-driven models can explore an expanded world of signals to identify pattern deviations in milliseconds.
Say a commercial customer regularly pays a high-value invoice to a vendor using instant payments, and suddenly, the business receives a request from a vendor to divide the payment into eight smaller instant payments all made on the same day. Because the transactions are below callback thresholds and fully authorized by the business, traditional risk platforms would view these as acceptable transactions.
AI behavioral analysis sees it differently. Irregular patterns in payment interval frequency and the clustered nature of the transactions add up to a significant behavioral deviation in the eyes of AI-enabled risk systems. Identifying the fraud pattern then triggers a micro-delay in processing the instant payment, taking time to warn the customer of likely fraud or to halt the transaction entirely, awaiting an approval override.
Behavioral biometrics are another critical tool in identifying fraud patterns, building unique customer profiles based on signals such as typing rhythm, mouse movement, and even interaction speed during digital banking sessions. When an instant payment is initiated, behavioral biometric models compare live data against the customer’s established baseline profile in real time. Subtle deviations increase risk scores and prompt action before an instant payment is authorized.
As criminals take aim at instant payments, it’s clear that banks need advanced tools to identify and stop fraud. Finastra’s collaboration with FraudAverse brings an advanced, AI-driven fraud prevention solution to its Financial Messaging customers, delivering real-time protection against emerging threats and reducing operational costs. As payment volumes grow and fraud tactics become more sophisticated, financial institutions must tap into robust, cloud-ready prevention solutions, optimized for today’s fast-moving payments landscape.
This article was previously published by Financial IT: Innovations in Fintech (Summer Issue 2026).
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