Key takeaways:
Payment fraud is the unauthorized use of an individual’s financial information to conduct illegal transactions. The overall strategy is to deceive individuals into sharing their financial and other sensitive information using hardware and software hijacking technology.
Payment fraud happens when devices such as scanners, keystroke loggers, and malware capture manually entered data to divert the information back to the perpetrators. Businesses invest significantly in payment fraud prevention tools to counter these attacks.
With today’s technology, every payment method is unfortunately at risk of fraud. We discuss them briefly below:
According to a 2025 Nilson Report, global payment card fraud losses reached $33.83 billion in 2023, with the US bearing approximately 42% of these losses. The most prevalent type of credit card fraud happens remotely: card-not-present (CNP) fraud, which occurs when stolen card information is used to make purchases online or over the phone.
While EMV chip technology has reduced card-present fraud, criminals still find ways to exploit merchant vulnerabilities, often involving cloning, where criminals copy card details onto a blank magnetic stripe card or stolen cards used before the victim notices and reports them.
Example: In November 2024, a UK resident’s replacement credit card was intercepted and used fraudulently before she received it, underscoring the vulnerabilities in card issuance and delivery processes.
See: Detecting Credit Card Fraud by Decision Trees and Support Vector Machines
Debit card fraud involves the unauthorized withdrawal of funds directly from the victim’s bank account. This happens via physical theft of the card, skimming devices capturing card details, or data breaches exposing card information. Unlike credit card fraud, victims of debit card fraud may experience immediate financial loss as funds are withdrawn directly from their accounts.
Example: In October 2024, a UK resident discovered unauthorized transactions exceeding £100 on their Uber and Uber Eats accounts linked to their debit card. Uber refunded the fraudulent charges, but it was unclear where the unauthorized transactions came from.
Mobile payment fraud occurs when fraudsters exploit mobile payment systems, apps, or devices to make unauthorized transactions or steal financial information. One way this is done is through SIM swapping, where an attacker gains control of a victim’s phone number to access their accounts, or through malware that infects a device to intercept sensitive information like payment credentials.
Example: In November 2024, three Indiana residents were charged in connection with a nationwide SIM-swapping conspiracy. The defendants managed to steal funds and personal data through the mobile numbers connected to the victims’ email, social media, and cryptocurrency accounts.
See: Mobile Device Security Policy
Wire fraud involves schemes conducted via phone calls, emails, or online messaging platforms, often using false representations or promises to defraud individuals or organizations of money or property. Fraudsters trick victims into transferring funds to accounts they control, leading to substantial financial losses.
Example: In July 2024, individuals based in Michigan, Illinois, and Texas pleaded guilty to conspiracy in international mail and wire fraud, defrauding victims of at least $2 million from 2017 to 2022.
Despite declining check usage due to digital payment methods, check fraud remains common. This involves illegal activities such as forging signatures, altering check details, or depositing counterfeit checks.
Example: In late 2024, JPMorgan Chase filed lawsuits against customers who exploited a viral “money glitch” by depositing large, fake checks via ATMs and withdrawing funds before the checks cleared. This scheme resulted in over $660,000 in losses for the bank.
Bank fraud involves schemes to steal cash and other bank assets, such as loan fraud, account takeover, fraudulent wire transfers, and embezzlement. Criminals may carry out these types of fraud using stolen identities, forged documents, or insider access.
Example: In December 2024, reports emerged of low-level bank employees selling client data to online scammers, facilitating sophisticated financial fraud schemes. Staffers in various banks made copies of customer financial information, which they then sold to buyers on Telegram.
The different types of payment fraud involve various deceptive practices aimed at stealing financial data for unauthorized use. Here are seven of the most common ways payment fraud happens:
Phishing is when scammers impersonate legitimate entities to trick individuals into revealing sensitive information. This deception is often carried out using fake emails, text messages, or websites that appear legitimate.
Watch out for unsolicited communications requesting personal information, generic greetings, grammatical errors, and URLs that deviate slightly from authentic addresses.
Implementing email filtering solutions can help identify and isolate potential phishing attempts. Multi-factor authentication (MFA) adds an extra layer of security, and employees should be trained to recognize phishing emails.
Skimming is when criminals install devices on ATMs or point-of-sale terminals to illicitly capture card information during legitimate transactions. These devices read the magnetic stripe data, enabling the creation of counterfeit cards for fraudulent use.
Signs of skimming devices include loose or misaligned card slots, unfamiliar attachments on payment terminals, or visible adhesive residues.
Upgrade to payment terminals that support EMV chip technology, which is more secure than magnetic stripe systems. Additionally, install tamper-evident seals and conduct routine checks on all payment devices.
Identity theft involves the unauthorized access and use of someone’s personal information — such as Social Security numbers, bank account details, or credit card numbers — to commit fraud or theft.
Consider installing monitoring services that can identify unusual account activities, such as unrecognized transactions, changes in account details, or unexpected credit inquiries.
Implement layers of identity verification processes,, such as biometric data and MFA. Update and patch systems regularly to protect against data breaches. Train employees to safeguard personal information and recognize social engineering tactics.
See: What Are Biometric Payments & How Do They Work?
Chargeback fraud, or friendly fraud, occurs when a customer makes a purchase and then disputes the charge with their bank, claiming the transaction was unauthorized or that they did not receive the product.
Patterns such as frequent disputes from the same customer, high-value chargebacks, or discrepancies between shipping and billing addresses can indicate chargeback fraud. Analyzing transaction histories and customer behavior helps identify potential fraudsters.
Maintain detailed records of all transactions, including communication logs and delivery confirmations, to provide evidence during disputes. Clearly communicate your return and refund policies to customers. Utilize fraud detection tools that assess the risk level of transactions in real time.
Fraudsters set up fake e-commerce stores that appear legitimate, offering products at highly discounted prices. The fraudster is able to steal the customer’s credit card information when a customer places an order.
Monitor transaction patterns like multiple orders from different customers using the same shipping address or rapid transactions using different payment details. You will likely receive customer complaints of unauthorized charges while still receiving products.
Implement strong authentication protocols for customer accounts to prevent unauthorized use of stolen credit cards. Use AI-driven fraud detection services that can flag inconsistencies in customer profiles and payment methods.
This type of fraud uses bots that rapidly test thousands of stolen or randomly generated card numbers on e-commerce sites or payment gateways by making small, inconspicuous transactions to avoid detection before making larger fraudulent purchases to find valid ones.
Look for unusual spikes in small transactions, especially from the same IP address or device. Multiple failed payment attempts followed by a successful one often indicate fraudsters testing different card details. Unfamiliar device fingerprints, geolocation mismatches, and excessive transaction attempts in a short period are also red flags.
Implementing CAPTCHA and bot detection solutions can block automated scripts used for card testing. Set velocity rules and transaction limits to prevent excessive payment attempts from a single user or device. Use AI-driven fraud detection tools that can analyze suspicious transaction patterns and automatically block suspicious activities before they escalate.
Authorized Push Payment (APP) fraud occurs when fraudsters deceive victims into willingly transferring money to fraudulent accounts. According to Alloy’s 2024 State of Fraud Benchmark Report, 22% of surveyed organizations identified APP fraud as their top fraud type by case volume.
Monitor transaction patterns for unusual or high-value payments sent to new or unverified beneficiaries. Use behavioral analytics and anomaly detection to flag suspicious payment requests, particularly those involving urgent or last-minute account changes.
Verifying payment details with a second communication method (e.g., phone calls instead of email) can help prevent APP fraud. Implement MFA and transaction verification steps to confirm the identity of payment requestors.
The use of AI has significantly increased the complexity of payment fraud. In Trustpair’s latest fraud report, generative AI tactics such as deepfakes and deepaudio grew by 118% in 2024. Criminals can create sophisticated scams that are harder to detect and often bypass traditional security measures.
Examples include:
Related reading:
That said, AI is also widely used to enhance payment security, reduce fraud, and improve the overall customer experience. Below are some of the industry leaders in the fight against payment fraud:
Visa Advanced Authorization is a system that analyzes transactions in real time, evaluating over 500 risk factors to assess the likelihood of fraud. It leverages machine learning models trained on a vast dataset of global transactions to identify unusual spending patterns, merchant inconsistencies, and geolocation anomalies. When a transaction is deemed high-risk, Visa can block it or alert the merchant for further verification before processing.
Mastercard’s real-time authorization decisioning solution utilizes AI to analyze thousands of data points and behavioral analytics to evaluate the risk associated with each transaction before approval. It constructs a risk score based on historical transaction data, merchant categories, and device information to distinguish between legitimate and fraudulent activities. Mastercard Decision Intelligence aids issuers in reducing false declines and effectively blocking high-risk payments.
See: Credit Card Fraud Detection Using Rough Sets and Artificial Neural Network
Signifyd provides a machine learning platform that examines millions of data points from transactions across various merchants to assess the likelihood of fraud. It assigns a risk score to each order based on user behavior, device data, and purchasing history, facilitating instant approval or decline decisions.
Riskified’s fraud prevention platform uses AI in mitigating chargebacks, account takeovers, and refund fraud for ecommerce businesses. Its behavioral analytics and machine learning feature verifies customer identities, flags high-risk transactions, and automates fraud detection.
See: Protecting Payments in an Era of Deepfakes and Advanced AI
It’s clear how payment fraud affects consumers with stolen financial information, but it’s not often discussed how businesses that end up accepting funds from compromised accounts are equally disadvantaged.
The best fraud prevention strategy is unique to every business, so instead, it’s important to focus on the best practices that can help you develop payment fraud detection methods customized to your business needs.
A comprehensive risk assessment will help you identify vulnerabilities in your business payment processes before fraudsters can exploit it. Begin by analyzing transaction data to find your high-risk payment methods. Don’t forget to include business partners with platform integrations in your investigation to cover all your bases. Then, review past fraud incidents to recognize any patterns of access. AI analytics and fraud detection software will be useful at this stage.
Once risks are identified, you should have all the information you need to choose among proven fraud prevention techniques that can develop a customized fraud prevention strategy.
Work with a payment security consultant that supports the right combination of multi-factor authentication, tokenization, end-to-end encryption, and AI-driven fraud detection based on your industry and payment methods. Doing so will also help employees, customers, and financial partners understand their roles in preventing fraud.
Your payment fraud detection and prevention plan should provide real-time transaction monitoring, biometric verification, behavioral analytics, and automated fraud scoring that can help detect and block suspicious activities. Launch your employee training program on fraud awareness and your information campaign, educating customers about phishing and scams.
Make sure your business is regularly evaluated for PCI compliance to reinforce your protection from payment fraud.
In addition to a prevention strategy, ensure that you have a well-defined incident response plan in case of successful unauthorized access. Create fraud detection teams, set up automated alerts for suspicious transactions, and have clear escalation protocols to minimize losses. Identify reporting lines, such as banks, cybersecurity firms, and law enforcement, that can help with the rapid recovery of stolen funds and legal action against fraudsters.
Last but not least, maintain a detailed documentation of your fraud prevention efforts for consistency, compliance, and continuous improvement. Track security updates, log all fraud incidents, analyze emerging threats, and update policies as needed. Regular audits and industry collaboration can help refine strategies to stay ahead of evolving fraud attacks.
See our guide to PCI compliance and learn how regulatory standards protect your business from payment fraud.
Kaynak: https://www.techrepublic.com/article/payment-fraud-detection-prevention-guide/
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