Types of Payment Fraud: Why Is APP Fraud Hardest to Prevent

Instant transfers, real-time payments, and mobile-first banking have created more opportunities for fraudsters to exploit urgency, impersonation, and weak points in the payment journey.

For banks, it means they have to defend against both unauthorized transactions and authorized push payment (APP) fraud. Because the latter are approved by the customer, they are much more difficult to detect and prevent.

Banks have to detect high-risk recipient accounts, scam behavior, and mule activity early enough to intervene before the payment is completed.

Read on to learn more about the types of payment fraud and why moving to account-level intelligence is essential for detecting and preventing fraud schemes.

Key Takeaways

• Payment fraud comes in many forms, and each requires a different prevention approach
  Card fraud, account takeover, BEC, instant payment fraud, and APP fraud exploit different weaknesses, making layered detection strategies essential for banks.
• APP fraud is especially challenging because customers authorize the payments themselves
  Unlike unauthorized fraud, APP scams bypass traditional controls by manipulating victims into approving transactions that appear legitimate.
• Transaction monitoring alone can’t reveal the full fraud picture
  The most important warning signals often sit beyond the payment itself, including risky recipient accounts, mule activity, and connections to wider fraud networks.
• Account intelligence helps banks detect fraud risks before payments are completed
  By analyzing customer behavior, account relationships, and cross-institution fraud signals, banks can identify suspicious activity earlier and intervene before funds leave the account.

• Acoru helps banks move from reactive fraud detection to proactive APP fraud prevention
  Acoru combines scam prediction, mule classification, holistic fraud prevention, and consortium intelligence to help financial institutions identify risky accounts, assess sender and recipient risk, and stop fraud before payments are completed.

What Is Payment Fraud?

Payment fraud is an illegal attempt to steal money by manipulating or exploiting payment systems.

Fraudsters may target consumers, businesses, or financial institutions through bank transfers, payment cards, digital wallets, mobile payments, or real-time payment networks.

Regardless of the target or method, payment fraud has the same objective: moving money into accounts controlled by criminals.

7 Types of Payment Fraud Every Bank Should Know About

Below are the most common types of payment fraud.

1. Card Fraud

Card fraud happens when criminals use stolen payment card information to make unauthorized purchases or withdraw funds.

The most common examples include:

• Card-not-present (CNP) fraud: Uses stolen card details to make unauthorized online, phone, or mail purchases without the physical card
• Stolen or lost card fraud: Uses a misplaced or stolen physical card to make unauthorized purchases or cash withdrawals
• Card skimming: Copies card information from compromised ATMs or payment terminals to use the data for cloning or online fraud
• Card cloning: Duplicates card data onto a counterfeit card to make unauthorized purchases or withdraw cash

Banks often identify card fraud by looking for unusual spending behavior, unexpected payment locations, fast purchase attempts, or suspicious merchant activity.

2. Identity Fraud

Identity fraud involves using stolen or fabricated personal information to impersonate someone and run fraudulent activities including:

• New account fraud: Uses stolen personal information to open bank accounts, credit cards, or access other financial products
• Synthetic identity fraud: Combines real and fabricated personal information to create fake identities that appear legitimate
• Identity theft: Uses stolen identities to fraudulently obtain loans, credit, or other financial services

3. Account Takeover Fraud

Account takeover (ATO) is a type of identity theft in which criminals gain unauthorized access to a legitimate customer's banking account.

Attackers usually get login credentials through:

• Phishing emails and fake websites
• Credential stuffing using leaked passwords
• Malware
• Social engineering
• SIM swapping

Once inside the account, fraudsters may change contact information, add new recipients, transfer funds, or lock the legitimate customer out.

Another reason why ATO represents a big challenge for banks is that it causes customer churn. According to Javelin Strategy & Research, in the USA in 2024, 42% of ATO victims closed the accounts after a fraud because of a lack of trust in the bank’s protection.

4. Business Email Compromise Fraud

Business email compromise (BEC) is a type of fraud where fraudsters impersonate executives, suppliers, or trusted business partners and convince employees to authorize fraudulent payments.

Here are the most frequent types of BEC fraud:

• Fake supplier invoices: Deceive employees into paying fraudulent invoices that appear to come from legitimate vendors
• CEO impersonation requests: Trick employees into transferring funds by posing as a senior executive making an urgent request
• Payroll diversion scams: Deceive payroll teams into sending employee salaries to bank accounts controlled by fraudsters
• Invoice redirection fraud: Tricks businesses into sending legitimate invoice payments to fraudulent bank accounts

Because these payments often appear legitimate, organizations may not discover the fraud until long after the money has been transferred.

5. ACH and Transfer Fraud

ACH and transfer fraud happens when criminals manipulate electronic bank transfers to move money into accounts they control. This often involves compromised accounts, fraudulent payment instructions, or mule accounts that quickly receive and move stolen funds.

Because the payment itself may appear legitimate, traditional transaction monitoring can struggle to detect the fraud.

Banks need visibility into the receiving account, including whether:

• It displays suspicious behavior
• It is newly opened
• It has connections to known fraudulent accounts or mule networks

6. Instant Payment Fraud

Instant payment fraud involves real-time payment systems, where criminals exploit the speed of near-instant transfers to move money into accounts they control.

Unlike traditional payments, which may allow more time for review or intervention, instant payments are completed within seconds. As a consequence, they leave very little time to intervene once a transaction has begun.

Because customers often authorize these payments themselves, traditional fraud monitoring may not identify them as suspicious. In addition, traditional fraud controls that rely on analyzing transactions after they happen usually identify risks too late, especially when the payment itself appears consistent with normal customer behavior.

7. Authorized Push Payment Fraud

Unlike unauthorized payment fraud, authorized push payment (APP) fraud happens when customers willingly authorize a payment after being manipulated by criminals through impersonation, urgency, and emotional pressure.

Victims may believe they are:

• Paying a legitimate supplier
• Investing in a genuine opportunity
• Helping a family member
• Speaking with their bank
• Responding to law enforcement
• Purchasing goods from a trusted seller

By the time the victim realizes they have been deceived, the funds have often been transferred through multiple accounts.

Why Is APP Fraud so Hard to Stop?

While every type of payment fraud poses risks, APP fraud is particularly challenging because it exploits human trust rather than technical vulnerabilities, making it much harder to detect and prevent.

Below are the main reasons that make detection difficult.

1. The Payment Is Legitimate

Most fraud detection systems were designed to stop unauthorized transactions. They look for indicators such as:

• Invalid authentication
• Stolen credentials
• Suspicious devices
• Unusual login locations
• Abnormal transaction velocity

However, in APP fraud, none of these warning signs may be present.

The customer logs in to their account, completes multifactor authentication, enters the recipient details, and approves the payment themselves. From a traditional transaction monitoring perspective, everything appears legitimate.

2. Fraud Happens Before the Payment

Criminals often spend days or even weeks manipulating victims before any money is transferred. This process involves building trust and creating urgency, so by the time the payment is made, the victim believes they are sending money to a trusted recipient.

3. Traditional Fraud Detection Has Limited Visibility

Since traditional fraud detection platforms primarily focus on individual transactions, they can’t see the broader context, such as whether the recipient account has displayed suspicious behavior across previous interactions.

These hidden signals often provide a much stronger indication of fraud than the payment itself. Without additional context about that recipient, the bank may have little reason to intervene.

How Account Intelligence Changes APP Fraud Detection

Account-level fraud detection gives banks a more complete view of risk, making it possible to intervene earlier, before money leaves the sender’s account.

It enables banks to:

Monitor Customer Behavior Continuously

Customer behavior often changes before fraud becomes visible through transaction analysis.

A customer may contact support to ask about increasing their credit limit or how quickly they can obtain a loan. They may move large portions of their savings into a current account, suddenly change their usual login patterns, or behave differently within the banking app.

On their own, these actions may appear completely legitimate and may not provide enough evidence for a bank to intervene.

However, connecting these signals into a timeline provides important context about what may be happening behind the scenes and gives the bank evidence to act.

Monitoring transaction patterns can reveal unusual activity such as new payment habits, unfamiliar recipients, or deviations from common customer behavior.

By establishing a baseline of normal customer activity, banks can more easily identify subtle changes that may indicate a scam is underway.

These behavioral signals often appear before traditional transaction-based alerts, giving fraud teams time to investigate or intervene.

Combined with other account intelligence signals, behavior monitoring can help banks distinguish legitimate customer activity from payments influenced by fraudsters.

Connect Intelligence Across Financial Institutions

Fraud rarely remains within a single financial institution. Criminal networks often move funds across multiple banks using numerous intermediary accounts.

When financial institutions securely share fraud intelligence, they can identify patterns and connections between accounts that appear unrelated, which would otherwise remain invisible within their own data.

This broader view increases the ability to detect mule accounts, emerging scam networks, and repeat fraudsters earlier.

Detect Emerging Fraud Patterns with AI

AI helps banks identify complex fraud patterns that traditional rules may overlook. Instead of relying solely on predefined thresholds, AI models can recognize subtle behavior changes, new fraud techniques, and hidden connections between accounts.

These models can adapt as fraud tactics change, helping financial institutions identify new scam patterns without constantly rewriting detection rules.

AI can also reduce the time required to investigate fraud cases. Instead of requiring analysts to manually review large volumes of transactions, account activity, and related signals, AI can bring relevant evidence together and identify connections across accounts in minutes instead of days.

In addition, AI agents can work alongside fraud teams to assess alerts and improve decision accuracy.

Used alongside account intelligence and behavioral analytics, it enables more proactive fraud prevention while reducing unnecessary alerts for legitimate customers.

How to Strengthen APP Fraud Detection with Acoru

Acoru is an AI-native fraud prevention platform that combines account intelligence, predictive signals, and collaborative fraud insights to help financial institutions:

• Detect scams
• Classify risky accounts
• Prevent fraudulent activity before payments are initiated

For APP fraud, moving to account intelligence is necessary because the fraudster’s real weakness is often not the payment itself but the account receiving it.

Acoru enables banks to improve APP fraud detection by:

• Predicting scams before transactions happen: The system identifies pre-fraud signals and suspicious account behavior to detect potential scam activity before funds are transferred.
• Classifying accounts based on fraud risk: The solution dynamically assesses accounts to identify potential victims, money mules, and fraudulent accounts involved in scam activity.
• Monitoring account activity across the customer journey: The system continuously evaluates account behavior and relationships instead of relying only on individual payment events.
• Unifying fraud prevention across channels: The solution combines signals from fraud detection, AML, device intelligence, behavioral analytics, and other sources into a single fraud prevention approach.
• Assessing both sender and recipient risk: The system analyzes account relationships and destination account behavior to identify suspicious payments before money leaves the institution.
• Sharing fraud intelligence securely across institutions: Banks can collaborate through privacy-focused intelligence sharing while keeping sensitive customer data protected.
• Improving fraud decisions with AI-driven insights: Banks can use AI and predictive analytics to spot hidden patterns, adapt to evolving scam techniques, and support faster investigations.

Request a demo today to see how you can identify risks earlier and reduce losses and APP fraud reimbursements.

See Acoru in Action

Fraud in Latin America is moving fast, and the institutions keeping pace are the ones rethinking how they detect, share, and act on intelligence. If the challenges discussed in this episode sound familiar, we would be glad to show you how Acoru works in practice. 

FAQ:

1. What Is APP Fraud and Why Is It So Hard to Stop?

APP fraud is a type of payment fraud in which a victim is tricked into sending money to a criminal while believing the payment is legitimate.

It is hard to stop because the customer authorizes the transfer themselves, so the payment can look valid at the moment it is made, even though the request came through deception.

2. Why Is Account-Level Fraud Detection A Key Complement to Transaction-Level Fraud Detection?

Account-level fraud detection is effective because it builds a fuller risk picture from signals across channels and data sources, not just the payment event at the moment it happens. This risk picture covers both the sender and the destination accounts, including those that sit outside your financial institution.

This helps banks spot mule accounts, suspicious account activity, and scam-linked activity earlier in the payment journey, which is especially important for APP fraud where the transaction may otherwise appear legitimate.

3. What Are the Most Common Types of Payment Fraud in Banking?

The most common types of payment fraud in banking include card fraud, account takeover fraud, identity fraud, and APP fraud.