Payment fraud red flags are the warning signs and unusual patterns that help banks and financial institutions identify potentially fraudulent payments or accounts before a transaction is initiated.
According to the European Banking Authority (EBA) and the European Central Bank (ECB), payment fraud continues to evolve, with total fraud losses across the European Economic Area rising to €4.2 billion in 2024.
For fraud teams at banks and financial institutions, spotting these red flags early is the difference between blocking a payment and chasing funds that have already left the account.
In this article, we'll explain what the most common red flags for payment fraud are, why they often go unnoticed, and how you can identify them before funds are lost.
Payment fraud typically develops over time, which can be seen through changes in customer behavior and account activity. Looking at the full sequence of events instead of individual payments helps detect fraud earlier.
Sudden changes in payment habits, inactive accounts becoming active, multiple profile updates, or a series of small test transactions can all indicate preparation for fraud.
Monitoring recipient accounts for signs of money mule activity and using counterparty intelligence can help identify high-risk payment destinations before funds are transferred.
Static rules often struggle to keep up with evolving fraud tactics and real-time payments. Continuously analyzing account intelligence, pre-fraud signals, and cross-channel activity gives fraud teams more time to identify threats before losses occur.
Acoru helps financial institutions detect payment fraud earlier by combining data across existing systems, continuously classifying accounts, evaluating both senders and recipients, and using AI and consortium intelligence to uncover fraud patterns that traditional transaction monitoring may miss.
Payment fraud refers to financial transactions carried out through unauthorized access to a customer's account or by deceiving customers into authorizing payments themselves.
In some cases, fraudsters take control of an account and initiate the payment without the customer's knowledge. In others, they use scams or social engineering to convince customers to willingly approve the transaction.
Some of the most common types of payment fraud include:
Despite the availability of many fraud‑detection tools, most red flags often slip past detection systems and fraud teams. Several factors contribute to this problem:
Most fraud detection systems rely on predefined rules, such as flagging large payments or transfers to a new beneficiary.
While these rules are useful, they often generate a large number of alerts, many of which are legitimate activity. As a result, fraud teams spend valuable time reviewing false positives, making it easier for genuine threats to be overlooked.
Fraudsters constantly change their tactics to avoid detection, while rule-based systems are typically updated only after fraud teams identify new attack patterns, create new rules, and test them before deployment. By the time these updates are in place, fraudsters may have already changed their approach by:
This makes it difficult for static rule-based systems to keep up.
Fraud signals are often spread across different systems and departments, which makes it challenging to see the full picture.
One team may detect unusual account activity while another investigates suspicious payments, but without sharing data, those signals remain disconnected. Consequently, it becomes much harder to identify fraud that develops across multiple channels or over time.
Worth knowing:
Acoru replaces fragmented fraud detection by unifying data across:
By bringing together signals from multiple channels, systems, and data sources into a single account-centric risk view, Acoru enables you to identify patterns and connections that siloed solutions are more likely to miss.
With real-time payment systems, money can move in seconds, leaving very little time to detect and stop fraud. This is especially challenging in scams like APP fraud, where customers authorize payments themselves after being manipulated by fraudsters.
By the time anyone realizes something is wrong, recovering the money becomes extremely difficult or impossible.
Worth knowing:
Unlike solutions that evaluate risk at the moment a payment is initiated, Acoru continuously monitors account behavior and risk over time.
By identifying gradual changes in account activity long before a payment is made, it gives you time to investigate suspicious behavior and intervene before a fraudulent payment is authorized.
Payment fraud rarely happens without warning. Here are some of the most common red flags and the strategies you can use to identify them:
A sudden shift in how a customer makes payments can be an early sign of fraud. For example, someone who normally uses their account just for bills may unexpectedly send a large international wire or make several unusually high-value payments.
While these changes may have legitimate explanations, they should be reviewed when they don't align with the customer's typical activities.
How to spot it early:
Worth knowing:
Acoru's AI Workforce continuously monitors account activity for signs of developing fraud. When it identifies potential fraud-preparation indicators, it can automatically investigate the event and initiate approved mitigation actions, all in accordance with your institution's policies and controls.
When an inactive account suddenly becomes active, particularly with large transfers, new counterparties, or multiple transactions in a short period, it is a notable change that deserves closer review.
Such activity may indicate an account takeover or the use of the account to move fraudulent funds.
How to spot it early:
Fraudsters often change customer information after gaining access to an account to maintain control. Updates to phone numbers, email addresses, devices, or authentication methods may be legitimate on their own, but multiple changes within a short period can indicate account takeover.
How to spot it early:
If multiple account changes occur together, assign a higher risk score and trigger additional review or verification steps.
Fraudsters often make a series of small transactions before attempting a larger payment. Sometimes these transactions are used to test whether a stolen card or compromised account is active.
In other cases, fraudsters split a larger amount into multiple smaller transactions to avoid reporting thresholds and detection rules.
These low-value transactions may appear harmless on their own, but together they can be an early indicator of fraud preparation.
How to spot it early:
Sending money to an account that shows signs of money mule activity is a key red flag for payment fraud. Although fraud monitoring often focuses on the sender, the receiving account may already have a history of suspicious behavior.
Considering both sides of the transaction helps identify risky payments that might otherwise appear legitimate.
How to spot it early:
Worth knowing:
Acoru's Consortium Manager helps financial institutions identify suspicious recipient accounts beyond their own customer base through a real-time, privacy-preserving intelligence network. Rather than relying on static blacklists, it continuously shares actionable fraud intelligence without exposing customer data.
It provides visibility across:
1. Your own accounts
2. External accounts your customers transact with
3. External accounts with no direct relationship to your institution through optional consortium sharing
This helps financial institutions:
In APP fraud, victims are often coached in real time over the phone or through messaging apps while logging in, adding a new payee, or approving a payment.
This pressure can change how they interact with their device, creating early behavioral signals before the payment is completed.
How to spot it early:
Many payment fraud schemes don't begin with the fraudulent payment. Risk often develops gradually through changes in customer behavior, account activity, and counterparties, along with other warning signs that appear before a suspicious payment is made.
Acoru helps you identify payment fraud earlier by showing how risk develops over time.
Rather than analyzing only individual transactions, it continuously evaluates account behavior, pre-fraud signals, and counterparty activity to help you detect scams, money mule activity, and money-laundering patterns before they lead to significant losses.
With Acoru, you can:
Request a demo today and see how Acoru helps you uncover the hidden patterns and pre-fraud signals that traditional fraud detection systems often miss.
Money mule accounts are often used to receive and move stolen funds on behalf of fraudsters, making the money harder to trace and recover. Some mule account holders knowingly participate in criminal activity, while others are recruited through fake job offers or online scams, unaware they're helping launder stolen money.
Preventing APP fraud is challenging because customers authorize payments themselves after being manipulated by a scammer. Because the customer initiates the payment, there are often no stolen credentials or clear signs that the account has been compromised, making behavioral signals and scam indicators essential for early detection.
Banks can detect payment fraud earlier by monitoring how account risk develops over time rather than evaluating individual transactions in isolation. Connecting signals across payment behavior, customer profile changes, device activity, counterparty intelligence, and multiple banking channels gives fraud teams the full context needed to identify suspicious patterns early.