Reducing payment fraud risk requires giving existing fraud controls enough context to distinguish higher-risk interactions from routine activity, rather than applying more checks to every customer.
That distinction matters. UK Finance reported that criminals stole almost £1.3 billion through authorized and unauthorized fraud in the UK during 2025. Authorized push payment fraud alone accounted for £576.4 million, up 19% year over year. Yet adding blanket warnings, challenges, access restrictions, and payment declines can obstruct legitimate customers without addressing how the risk developed.
The issue is not simply how much friction an institution applies, but when the risk becomes visible and what the institution knows when it must decide whether to trust, challenge, restrict, or decline an interaction.
What is payment fraud risk?
Payment fraud risk is the likelihood that a payment will be initiated, redirected, or completed through criminal activity. It includes unauthorized payments made after an account or payment instrument is compromised, as well as authorized payments made after the customer is deceived or manipulated.
Account takeover is therefore one route to payment fraud, not a synonym for it. Not every account takeover results in a fraudulent payment, and many payment scams succeed without an attacker taking control of the customer’s account.
This distinction affects which evidence an institution needs. Stolen credentials, attacker-controlled devices, impersonation exposure, customer manipulation, and unusual payment activity describe different attack conditions. They should not automatically produce the same response.
Why payment fraud risk creates customer friction
Customer friction increases when fraud controls must make decisions using incomplete context.
A login can come from a recognized device, use valid credentials, and satisfy the required security checks, yet still follow exposure to digital impersonation, a scammer-led interaction, or a reverse-proxy phishing flow.
Alternatively, an attacker may replay stolen credentials from a different device. The login system can see that the device is unfamiliar, but it may not know whether the credentials were recently submitted to an impersonating site.
Without that earlier context, institutions face two imperfect options. They can allow an interaction that appears normal, or challenge a broader population of legitimate customers because the available evidence is inconclusive.
Earlier context enables targeted intervention.
When fraud controls know what happened before access was attempted, they can respond to the relevant sequence rather than treating every unfamiliar or higher-value interaction as equally suspicious.
Most fraud controls are optimized for the wrong stage
Many controls first evaluate the customer at a login, account, or payment checkpoint. That is where a decision must be made, but it may not be where the risk originated.
Conventional controls remain essential. Authentication verifies that required factors have been presented. Fraud engines evaluate known risk indicators. Transaction-monitoring systems inspect payment behavior and transaction characteristics.
However, these systems may not know that the customer previously encountered an impersonating experience, submitted credentials to it, or interacted with attacker-controlled infrastructure. Efforts to detect account takeover in real time are therefore constrained when the relevant evidence becomes available only after the login attempt reaches downstream controls.
The problem extends beyond credential theft. According to UK Finance’s 2026 Annual Fraud Report, 66% of authorized push payment fraud cases reported during 2025 originated online, while 17% originated through telecommunications channels.
The issue is not the absence of signals, but when those signals are evaluated.
What is actually happening before payment?
Payment fraud can emerge through several different sequences. The path from brand impersonation to account takeover is one of them, but it is not the only route institutions must consider.
Credential theft creates hidden access risk
A customer may enter credentials into a credential-harvesting page that imitates a legitimate service. Those credentials can then be reused at the genuine login page.
The resulting access attempt is visible to authentication and fraud systems. The preceding exposure may not be.
Without that connection, the institution sees valid credentials being used, but not the event that changed their trustworthiness.
Reverse-proxy phishing weakens the meaning of successful authentication
In a reverse-proxy or adversary-in-the-middle phishing flow, attackers relay information between the customer and the genuine service in real time. This can allow them to intercept session information even when the customer completes the expected authentication steps.
A successful authentication event confirms that the required factors were presented. It does not necessarily confirm that the entire journey was trustworthy. Understanding how to detect man-in-the-middle attacks therefore requires evidence beyond the final authentication result.
Customer manipulation can leave the account uncompromised
In authorized payment fraud, the genuine customer may access the account and approve the payment. Credentials may remain uncompromised, and the device may be familiar.
A consumer remote-access scam can create a similar problem. The legitimate customer may be operating the device while following an attacker’s instructions or while the attacker exercises remote control.
These distinctions matter because payment fraud prevention is broader than account takeover protection. The appropriate intervention depends on whether the institution is dealing with stolen credentials, an attacker-controlled device, a compromised session, or a manipulated customer.
Which signals support targeted decisions?
Useful fraud risk signals add verifiable context to an interaction.
A generic alert that an impersonating site exists does not identify customers exposed to brand impersonation attacks or establish whether that exposure created downstream account risk.
Key risk signals include:
- confirmed customer exposure to an impersonating experience
- decoy or compromised credential use at the genuine login
- device continuity between earlier activity and a later access attempt
- user and device risk scores supported by the underlying evidence
No single signal should be treated as decisive in every scenario. Its value depends on timing, confidence, attack type, and how it combines with other evidence.
For example, an exposed customer returning on a normal device may require a different response from an unknown device attempting to use credentials associated with an earlier impersonation event.
The governing principle is to respond to specific evidence of risk, rather than treating unfamiliarity alone as proof of fraud.
What earlier risk context changes
Earlier context improves the precision of existing decisions. It does not convert every exposure event into confirmed fraud.
Exposure to an impersonating experience does not prove that credentials were submitted. A familiar device does not automatically make an interaction safe. A risk score without the signals behind it may not give fraud teams enough information to determine the appropriate response.
The objective is to connect upstream evidence with downstream controls while meaningful options remain available. This changes the decision from:
“Should every customer meeting this broad rule be challenged?”
to:
“What happened in this customer’s journey, and which response is proportionate to that evidence?”
That shift can reduce reliance on blanket challenges, broad credential resets, unnecessary access restrictions, and avoidable payment declines.
The customer-experience consequences are material. Research commissioned by Checkout.com and conducted by Oxford Economics surveyed 8,000 consumers and 1,500 businesses in 2023. It found that 45% of consumers would not retry after a false payment decline, while 42% would not return to the same website.
Unnecessary friction therefore affects more than completion rates. It can also weaken customer confidence and long-term retention.
What should fraud and risk teams do differently?
Teams should stop treating customer friction solely as a challenge-threshold problem.
Threshold tuning cannot compensate for missing context. Lower thresholds can expose institutions to more fraud, while higher thresholds can increase false positives and unnecessary customer challenges.
The more important question is how early reliable evidence enters the decision process.
Enterprise buyers should ask:
- Which events can the solution observe before login or payment?
- Can those events be connected to a specific user, credential, or device?
- How quickly can the evidence reach existing authentication and fraud controls?
- Can decision-makers inspect the signals behind a risk score?
- Which system retains responsibility for access and payment decisions?
- Which attack paths are supported, and which remain outside the solution’s scope?
A solution that adds another checkpoint may increase friction. A solution that improves the evidence available to existing checkpoints can help institutions make more selective decisions.
How Memcyco adds context before access
Memcyco surfaces earlier-stage impersonation exposure, credential-use, user, device, and pre-access risk signals. It can deliver real-time user and device risk scores, along with the signals behind them, to existing login and fraud systems before access is granted.
Those systems retain responsibility for deciding whether to trust, challenge, restrict, or decline the interaction. Memcyco does not replace authentication systems, fraud engines, or post-login transaction monitoring.
The purpose is not to eliminate every form of friction. It is to help institutions apply friction more selectively by giving their existing controls earlier, more specific evidence.
In one deployment for a major global bank, Memcyco helped reduce account takeover by 65%. The bank had been experiencing approximately 18,500 account takeover cases annually, with more than $27 million in refund and case-handling costs.
That result relates specifically to account takeover, not every form of payment fraud. It demonstrates how earlier risk visibility can strengthen the controls responsible for downstream access and fraud decisions. Earlier context enables more targeted intervention because controls can respond to the attack sequence, not merely the final event.
Book a demo and see how Memcyco can deliver earlier user, device, credential, and impersonation-risk signals to your existing controls.
Read More
- How to Reduce Time-to-Detect Fraud
- Regulation E and Digital Banking Fraud: A Financial Institution’s Guide
- Brand Impersonation Protection Software: What to Look for Beyond Domain Takedown
Frequently asked questions
How can banks reduce payment fraud risk without adding customer friction?
Banks can reduce unnecessary friction by giving existing authentication and fraud systems earlier context about impersonation exposure, credential risk, users, and devices. This allows controls to target higher-risk interactions instead of challenging every customer who meets a broad rule.
Is payment fraud the same as account takeover?
No. Account takeover is one route to payment fraud. Some account takeovers never result in fraudulent payments, while many authorized payment scams occur without an attacker taking control of the customer’s account.
Why can stronger authentication still miss payment fraud?
Authentication confirms that the required factors were presented. It may not reveal whether credentials were stolen, a phishing proxy relayed the authentication journey, a session was compromised, or the genuine customer was manipulated into approving a payment.
What causes fraud controls to create unnecessary friction?
Unnecessary friction often occurs when controls have incomplete evidence and must use broad indicators, such as an unfamiliar device or payment value, as proxies for risk. Earlier and more specific evidence enables narrower intervention.
What should enterprise buyers look for in a payment fraud risk solution?
Buyers should assess which attack stages the solution observes, how events are linked to users and devices, how quickly signals reach existing controls, whether the evidence behind risk scores is available, and which system retains the final decision.
Do risk-based access controls replace transaction monitoring?
No. Risk-based access controls and transaction monitoring operate at different stages. Earlier access-risk signals can inform login and fraud decisions, while transaction-monitoring systems continue to evaluate activity after access and during payment processing.
