< Back to Glossary

What is Payment Fraud?

Last updated: 26 October 2026

What is payment fraud?

Payment fraud is the use of stolen, false or manipulated information to make unauthorized payments or to trick someone into authorizing them. It covers card fraud, account takeover, scams that persuade victims to send money themselves, and abuse of the payment systems that move funds between accounts.

Retail businesses, financial institutions, healthcare companies and hospitality are especially exposed, as are firms in trading. Weak prevention can lead to direct losses, regulatory fines, reputational damage and operational disruption.

Payment fraud and money laundering are closely connected. Fraud generates illicit funds, and those funds must then be moved and disguised, often through money mule accounts. This overlap is why many institutions now combine their efforts under FRAML, bringing fraud and anti-money laundering controls together.

What types of payment fraud exist?

Here are 11 common types of financial fraud and how they work:

Type How it works
Debit card fraud A criminal uses stolen card details or a stolen card to make purchases or withdraw cash
Credit card fraud Stolen or fabricated credit card information is used to buy goods or obtain credit
Bank fraud Fraudulent transfers, forged instructions or account manipulation to take money from a bank or its customers
Check fraud Altered, forged or counterfeit checks, or deposits of checks that will not clear
Merchant fraud A dishonest merchant, or a criminal posing as one, processes fake transactions or misuses customer data
Mobile payment fraud Stolen credentials, SIM swapping or compromised devices used to take over mobile wallets and apps
Account takeover A criminal gains control of a genuine account and makes payments from it
Authorized push payment (APP) fraud A victim is deceived into sending money themselves, for example through an impersonation or investment scam
Synthetic identity fraud A fabricated identity, built from real and fake data, is used to open accounts and make payments
First-party fraud A genuine customer misrepresents facts or disputes valid payments, such as chargeback abuse
Business email compromise A criminal impersonates a supplier or executive to redirect a payment

APP fraud has grown in importance because the victim authorizes the payment, which makes traditional controls less effective. In the FinCrime Frontier 2026-27 report, APP fraud was the risk most often cited as increasing in importance (59.9% of respondents), followed by fraud-AML convergence (48.8%). Synthetic identity and deepfakes were cited by 29%. These are indicators from 202 respondents, not statistically representative.

What are the types of payment transaction?

  • Card-present transactions take place with the physical card or device, using a chip, magnetic stripe or an in-person mobile wallet such as Apple Pay or Google Pay.
  • Card-not-present transactions take place without the card, for example for subscriptions, phone orders, online and in-app purchases and utility payments. They carry higher fraud risk, because the merchant cannot physically verify the card or customer.

Both can be exploited, and the growth of instant, account-to-account payments adds a further risk: funds move in seconds, with little chance to recall them.

How does payment fraud occur?

Criminals first obtain personal or account information, often through social engineering, which means manipulating people into giving up data or making payments. Common methods include:

  • Skimming: capturing card data with a device on a terminal or ATM.
  • Phishing and smishing: fake emails, texts and calls that harvest credentials.
  • Chargeback abuse: disputing a legitimate purchase to recover the funds.
  • Identity theft: using stolen personal information to open accounts or authorize payments.
  • Hacking: breaching systems, devices or accounts directly.
  • Data breaches: stolen customer data sold and reused.
  • SIM swapping: taking over a phone number to intercept authentication codes.
  • Deepfakes and voice cloning: impersonating a customer or executive to authorize a payment.

How does payment fraud relate to money laundering?

Fraud is a predicate offense for money laundering, meaning the proceeds of fraud are illicit funds that must be laundered. The EU’s Directive (EU) 2018/1673 (often called the 6th Anti-Money Laundering Directive) defines 22 predicate offenses, including fraud, cybercrime and corruption, and member states may add others. It also includes crimes such as human trafficking, where tracing the flow of money can help stop the crime. Understanding the link between fraud and money laundering helps institutions share intelligence and spot mule networks sooner.

How to protect against payment fraud

  • Use strong authentication, including multi-factor and step-up checks for higher risk payments.
  • Choose secure payment processors that meet security standards.
  • Deploy fraud prevention software that scores payments in real time.
  • Connect fraud with AML transaction monitoring, so signals are shared instead of siloed. Read how fraud and scam prevention is evolving as scams become faster and more sophisticated.
  • Resolve identities across systems with entity resolution, to link accounts, devices and contact details.
  • Detect mule accounts, which are the exit route for most fraud proceeds. See how to enhance money mule detection.
  • Educate staff and customers on scams, particularly impersonation and investment fraud.
  • Limit data access to those who need it, and monitor for misuse.
  • Balance security and experience, by applying friction only when the risk justifies it.

How is AI changing payment fraud detection?

Rules-based fraud systems catch known patterns but struggle with new scams and create friction for legitimate customers. Machine learning models score each payment against the customer’s behavior, device and context, and adapt as fraud tactics change. Agentic AI can gather evidence across fraud and AML data and draft a documented recommendation for the investigator. Explainability and human oversight remain important, particularly for decisions that affect customers directly.

Behavioral intelligence, which analyzes how a customer normally types, navigates and transacts, is a growing part of this, and helps detect account takeover and scams that pass traditional checks. Watch the webinar on protecting customers from fraud with advanced behavioral intelligence to see how it works in practice.

Deploy a proven payment fraud solution with SymphonyAI

SymphonyAI’s payment fraud software uses predictive analytics, risk indicators and machine learning to detect fraud, block in-flight payments and apply step-up authentication only when needed, keeping the experience smooth for genuine customers. It is part of our financial crime prevention portfolio and works alongside AML transaction monitoring on Symphony Risk Intelligence. Learn more about SymphonyAI Payment Fraud.

FAQs

What is payment fraud?
Payment fraud is the use of stolen, false or manipulated information to make unauthorized payments, or to trick someone into authorizing them. It includes card fraud, account takeover and scams such as authorized push payment fraud.

What are the most common types of payment fraud?
Card fraud, account takeover, authorized push payment fraud, synthetic identity fraud and chargeback abuse are among the most common. Scams that exploit instant payments are growing.

What is authorized push payment (APP) fraud?
APP fraud is when a victim is tricked into sending money to a criminal, for example by impersonation or an investment scam. Because the victim authorizes the payment, traditional controls often miss it.

What is the difference between payment fraud and money laundering?
Fraud is the crime that generates the money, and money laundering is the process of disguising its source. They are closely linked, which is why institutions combine fraud and AML under FRAML.

How can businesses prevent payment fraud?
Use strong authentication, real-time fraud detection, secure processors, staff and customer education, and connect fraud and AML data to detect mule networks.

How does AI help detect payment fraud?
AI scores each payment against behavior and context in real time, adapts to new tactics and reduces friction for genuine customers, with human oversight for important decisions.