Payment fraud detection and prevention is a complex challenge that requires a dynamic set of interlocking solutions. It's important for businesses to educate themselves about it to protect their financial assets, maintain customer confidence, and anticipate changing threats. In 2025, 3 million fraud reports were filed with the Federal Trade Commission (FTC), representing US$15.9 billion in losses.

Below, we'll discuss the impact of payment fraud, the different types, and some best practices businesses can use to combat them.

What's in this article?

• What is payment fraud?
  
• The impact of payment fraud on businesses
  
• Types of payment fraud and how to prevent them
  
• How to create a unique payment fraud plan for your business
  
• How Stripe Radar can help
  

What is payment fraud?

Payment fraud is any dishonest or illegal activity that takes advantage of payment systems to gain unauthorised access to funds or financial information. This includes stealing someone's identity, making unauthorised purchases, and tricking a company into refunding money.

The impact of payment fraud on businesses

Payment fraud has severe consequences for individuals, businesses, and the economy as a whole. These are the primary impacts of payment fraud:

• Financial losses: Fraudulent transactions can lead to significant monetary losses for individuals, businesses, and financial institutions. In 2024, online payment fraud alone caused over US$44 billion in global e-commerce losses and that figure is expected to grow to US$107 billion in 2029.

• Identity theft: Payment fraud often involves the theft and misuse of personal and financial information, causing long-lasting harm to victims and making it difficult for them to restore their identities and credit.

• Business reputation: Companies that fall victim to payment fraud might suffer damage to their reputations and lose customer trust, which can lead to decreased sales, higher customer churn, and increased operational costs. Fraud can also erode trust in payment systems.

• Legal and regulatory consequences: Organisations that fail to comply with antifraud regulations or don't adequately protect customer information might face legal penalties, fines, and increased regulatory scrutiny.

• Increased operational costs: Payment fraud detection and prevention requires significant investment in technology, personnel, and resources, which can strain an organisation's budget and operational efficiency.

By addressing payment fraud, businesses and financial institutions can minimise the risks and negative consequences associated with fraudulent activities, ensure the integrity and security of payment systems, and maintain trust in the larger financial system.

Types of payment fraud and how to prevent them

Because fraudulent actors use a variety of methods to exploit vulnerabilities in payment systems, payment fraud comes in many forms.

Card-not-present (CNP) fraud

CNP fraud occurs when bad actors use stolen credit card credentials to make unauthorised purchases online, over the phone, or through mobile apps where the physical card cannot be examined. Because physical security features such as Europay, Mastercard, and Visa (EMV) chips cannot be checked, CNP fraud represents the majority of digital commerce fraud.

Here's how to detect and prevent CNP fraud:

• Verify cardholder data: Enforce address verification service (AVS) and card verification value (CVV) checks at checkout to confirm the buyer has physical possession of the card details and billing address.

• Deploy dynamic 3D Secure authentication (3DS): Use 3DS protocols to mandate authentication (via one-time passcodes or biometrics) only on high-risk transactions, shifting dispute liability to the card issuer under Strong Customer Authentication (SCA) mandates.

• Use AI-based risk scoring: Implement real-time fraud detection engines like Stripe Radar to evaluate hundreds of transaction attributes – including device fingerprinting, proxy usage, and payment patterns across businesses – to block fraudulent attempts before authorisation.

• Adopt network tokenisation: Replace raw primary account numbers (PANs) with secure, card brand tokens to prevent stored credentials from being compromised in data breaches.

First-party fraud

First-party fraud occurs when legitimate cardholders or opportunistic buyers exploit business policies and payment mechanisms for financial gain:

• Chargeback fraud ("friendly fraud"): A customer makes a legitimate purchase, then falsely claims to their bank that the transaction was unauthorised, the package never arrived, or the product was defective. They seek to force a refund while keeping the goods.

• Refund abuse and policy gaming: Distinct from chargebacks, refund abuse is when customers exploit return policies directly with the business. For instance, they might return used clothing ("wardrobing"), return empty boxes, claim items were missing from a package, or repeatedly claim orders never arrived to receive duplicate shipments or cash refunds.

Here's how to detect and prevent first-party fraud:

• Maintain detailed fulfilment documentation: Collect verifiable proof of delivery, including carrier tracking numbers, GPS delivery tags, photos of dropped packages, and signature confirmations.

• Clarify billing descriptors and return policies: Use recognisable trading names on credit card billing descriptors and provide prominent, easy-to-read refund terms at checkout to minimise customer confusion.

• Track customer behaviour and abuse patterns: Monitor customer accounts for patterns of excessive refund requests, frequent missing-item claims, or repeated chargebacks, and restrict payment methods or require signature on delivery for flagged profiles.

• Automate dispute evidence submission: Use automated dispute management tools to compile transaction logs, customer communications, proof of delivery, and terms-of-service acceptance to contest fraudulent chargebacks.

Business email compromise (BEC) and AI-generated social engineering

BEC is a sophisticated form of fraud where bad actors impersonate company executives, trusted vendors, or legal partners to deceive employees into wiring funds or redirecting invoice payouts.

The rise of generative AI has escalated this threat: attackers use large language models to generate hyper-realistic, error-free spear phishing emails and deploy deepfakes during voice and video calls to bypass traditional verbal approval checks.

Here's how to detect and prevent BEC and AI-driven fraud:

• Implement strict multiperson approval workflows: Require dual authorisation from separate managers for any funds transfers, payroll updates, or changes to vendor bank account details.

• Establish out-of-band verification: Mandate that employees verify any request to change payment instructions or banking details by calling the vendor or executive directly using a pre-established, trusted phone number – never the contact details provided in the change request email.

• Enforce advanced email authentication protocols: Deploy Sender Policy Framework (SPF), DomainKeys Identified Mail (DKIM), and Domain-based Message Authentication, Reporting, and Conformance (DMARC) to prevent domain spoofing and block unauthorised senders.

• Train staff on AI-based social engineering: Train finance and procurement teams to recognise AI-generated spear phishing cues, deepfaked audio tactics, and urgent transfer demands that don't follow established processes.

Identity theft and synthetic identity fraud

Identity fraud involves the use of compromised personally identifiable information (PII) – such as Social Security numbers (SSNs), dates of birth, and home addresses – to open fraudulent accounts, obtain credit, or make purchases:

• Traditional identity theft: Fraudulent actors impersonate real individuals using complete sets of stolen personal data.

• Synthetic identity fraud: Attackers combine real stolen PII (often SSNs belonging to children, deceased individuals, or inactive credit profiles) with entirely fabricated names and addresses. They nurture these synthetic identities over months or years to build legitimate-looking credit scores before they max out credit limits and abandon the accounts (known as "busting out").

Here's how to detect and prevent identity fraud:

• Multilayered identity verification: Require multipoint identity verification for high-risk transactions or account creation, combining government-issued ID document scanning with biometric liveness checks.

• Cross-reference identity databases: Verify applicant data against credit bureau registries, telecom databases, and government records to detect discrepancies between names, birth dates, and SSNs.

• Analyse behavioural signals: Track behavioural biometrics (e.g., typing cadence, copy-paste activity in form fields, device navigation) to distinguish automated bots and fraudulent form-fillers from authentic users.

• Enforce multifactor authentication (MFA): Require phishing-resistant MFA (e.g., FIDO2 passkeys, authenticator apps) to block account takeover attacks that stem from credential stuffing.

Real-time payment (RTP) fraud and instant payment exploitation

With the rapid expansion of instant, around-the-clock payment networks, such as the Clearing House's RTP network and the Federal Reserve's FedNow Service in the US, cybercriminals increasingly target account-to-account transfers.

Because RTPs settle within seconds and are irrevocable, bad actors use authorised push payment scams or account takeovers to trick victims into sending instant transfers. They then rapidly disperse the stolen funds across networks of "mule" accounts before banks or businesses can freeze the funds.

Here's how to detect and prevent real-time payment fraud:

• Implement pre-execution risk scoring: Evaluate transaction risk in milliseconds before you release an instant transfer, analysing sender device integrity, session anomalies, and historical transfer patterns.

• Use Verification of Payee: Verify that the recipient's registered account name matches the name entered by the sender before you execute the transfer, flagging potential mule accounts.

• Enforce dynamic limits and cooling-off periods: Apply temporary value caps or short settlement delays on instant transfers directed to newly added beneficiaries or unfamiliar accounts.

• Monitor outbound payment patterns: Flag high-frequency or sudden high-value transfers that originate from recently modified user profiles or accounts accessed from new internet protocol (IP) addresses.

Point-of-sale (POS) skimming and hardware tampering

Skimming involves installing covert physical devices or malicious software on card readers at POS terminals, automated teller machines (ATMs), or fuel pumps. When a customer swipes their card, the skimmer copies the unencrypted data stored on the magnetic stripe, while hidden pinhole cameras or fake keypads record the customer's personal identification number (PIN). Fraudulent actors then clone the magnetic stripe onto counterfeit cards to make in-store purchases or cash withdrawals.

Here's how to detect and prevent skimming:

• Transition to EMV chip and contactless payments: Use readers that can accept EMV chip-and-PIN payments and digital wallets powered by contactless or near-field communication (NFC) technology. EMV chips and tokenised NFC generate dynamic, one-time cryptograms that cannot be cloned or reused from magstripe data.

• Inspect hardware regularly: Conduct daily, documented physical inspections of all payment terminals, checking for loose overlays, broken tamper seals, mismatched plastic casing, or unapproved cable attachments.

• Deploy point-to-point encryption (P2PE): Use PCI-validated P2PE solutions that encrypt cardholder data directly inside the secure cryptographic reading device before you transmit the data across your network.

• Secure terminal access: Restrict physical access to payment equipment, lock down unused ports, and verify the identities of any third-party maintenance technicians before you allow them access to POS hardware.

How to create a unique payment fraud plan for your business

To create a payment fraud plan suited to their unique needs and risks, you'll want to follow a systematic approach that involves assessment, prioritisation, implementation, and continuous improvement.

Here's a step-by-step guide that you can use to develop and mobilise a payment fraud strategy:

• Assess your risk: Conduct a complete risk assessment to identify the types of payment fraud most relevant to your business, based on its industry, size, customer base, and transaction methods. Assess the existing systems, processes, and controls to identify vulnerabilities and potential areas for improvement.

• Prioritise the biggest threats: Based on the risk assessment, prioritise the most significant threats and vulnerabilities, taking into account the potential financial impact, reputational damage, and likelihood of occurrence. This will help determine which fraud prevention measures should be implemented first.

• Build your strategy: Outline a clear strategy that addresses the prioritised risks and vulnerabilities, incorporating a mix of preventive, detective, and responsive measures. Customise the strategy to the unique needs and risks of the business, and include both short-term and long-term objectives.

• Allocate resources: Allocate the necessary resources – including personnel, budget, and technology – to implement the chosen tactics and best practices. Assign clear roles and responsibilities to team members, and establish a strong governance structure to oversee the implementation and ongoing management of the strategy.

• Implement the plan: Introduce the chosen tactics and best practices, ensuring they're integrated into existing systems and processes. This might involve updating policies and procedures, investing in new technologies, or conducting training and awareness programmes for employees.

• Monitor and evaluate results: Continuously monitor the effectiveness of the implemented measures, using key performance indicators (KPIs) and metrics to track progress. Conduct regular audits to identify areas for improvement and ensure compliance with industry standards and regulations.

• Adapt and improve over time: Based on the monitoring and evaluation results, refine and adjust the strategy as needed. Incorporate new tactics to address emerging threats or changing business needs. Maintain a proactive approach to payment fraud prevention, staying informed about the latest trends, technologies, and best practices in the field.

Working with a provider of fraud prevention and mitigation services can amplify your efforts to fight fraud. And depending on which solutions you use to power your payments infrastructure and processing, you might already be equipped with fraud protection.

How Stripe Radar can help

Stripe Radar uses AI models to detect and prevent fraud, trained on data from Stripe's global network. It continuously updates these models based on the latest fraud trends, protecting your business as fraud evolves.

Stripe also offers Radar for Fraud Teams, which allows users to add custom rules addressing fraud scenarios specific to their businesses and access advanced fraud insight.

Radar can help your business:

• Prevent fraud losses: Stripe processes over US$1.9 trillion in payments annually. This scale uniquely enables Radar to help detect and prevent fraud, saving you money.

• Increase revenue: Radar's AI models are trained on actual dispute data, customer information, browsing data and more. This enables Radar to identify risky transactions and reduce false positives, boosting your revenue.

• Save time: Radar is built into Stripe and requires zero lines of code to set up. You can also monitor your fraud performance, write rules and more in a single platform, increasing efficiency.

Learn more about Stripe Radar or get started today.