The following information is intended to help raise awareness and prevention of credit card fraud risks. Do not use it for illegal activities. Understanding this information can help financial institutions, merchants and consumers better identify abnormal behavior and take preventive measures. The following content is mainly based on a summary of public literature, industry reports and cybersecurity practices: ─────────────────────────────── 【Common credit card fraud methods】 1. Targeting "non-cardholder transactions" (Card-Not-Present Fraud) • Description: Criminals use card numbers, expiration dates and CVV data obtained through phishing, data leaks or malware to commit fraud when shopping online or over the phone. • Characteristics: No physical card transactions, the verification method mainly relies on the input card information, and sometimes bypasses measures such as the address verification system (AVS). 2. Card copying/counterfeit (Counterfeit Card Fraud) • Description: Criminals use "illegal card readers" installed in places such as ATMs, hotels or gas stations to read magnetic stripe data, and use card writers to copy card information and then conduct fraudulent transactions. • Characteristics: Appears in physical transactions. Usually, the counterfeit card has no obvious difference in appearance from the cardholder's real card. 3. Illegal use of lost or stolen cards • Description: After the cardholder loses or the card is stolen, the criminals use the obtained card to directly consume at the POS (point of sale) or withdraw cash at the ATM (Automatic Teller Machine). • Characteristics: The transaction location and usage scenario may not be consistent with the cardholder's normal behavior, and the stolen card may be used multiple times in a short period of time. 4. Application Fraud • Description: Apply for a credit card by forging identity documents, forging income certificates or using stolen personal information, and then consume or cash out after obtaining the credit limit. • Characteristics: There is a risk of fraud in the application process, and the application information does not match the cardholder's normal credit record. 5. Account Takeover (ATO) • Description: The attacker obtains the cardholder's account number and password through phishing, social engineering or data leakage, and then modifies the account information to conduct transactions without authorization. • Characteristics: The behavior may be manifested as account changes, password resets, and abnormal login locations or times that the cardholder is not aware of. 6. “Friendly Fraud” • Description: After actually receiving the goods or services, the consumer takes the initiative to file a dispute with the credit card institution, claiming that he did not authorize the transaction. • Characteristics: The transaction actually occurred, but there are subjective identification issues during the dispute handling, which can easily lead to the merchant taking risks. ──────────────────────────────── 【Methods for identifying potential fraud and crime patterns】 1. Data analysis and anomaly detection • Establish a baseline: Establish a baseline model of the user's normal consumption behavior through big data analysis, and compare indicators such as transaction amount, frequency, location, and time. • Anomaly detection: Use statistical methods and machine learning algorithms to identify anomalies in transaction patterns that are inconsistent with historical behavior (such as sudden large transactions, multiple small transactions in a short period of time, cross-regional changes, etc.). 2. Real-time monitoring and alarm • Automated system: Apply risk assessment models in real time during the transaction process to intercept suspected high-risk transactions or trigger secondary verification (such as SMS, two-factor authentication). • Network sharing: Financial institutions share information about abnormal transactions with cybersecurity agencies and anti-fraud centers to update and correct models in a timely manner. 3. Multi-layer identity authentication • Dynamic authentication: Add additional authentication steps for sensitive transactions, such as using one-time passwords (OTPs) and biometrics. • Risk guidance: Actively guide users to perform dynamic identity authentication for attempts to access accounts from new devices and new locations. 4. Behavioral analysis and social engineering detection • Identify abnormal behaviors: For example, changes in login devices and geographic locations, consumption in unusual shopping categories, etc., which may indicate that an account is being abused. • Social media and public information monitoring: Pay attention to phishing, fraud reports on the Internet, and public reports of similar cases, which can help predict or identify new fraud methods in advance. 5. Regular security reviews and employee training • Internal audits: Conduct penetration tests and security audits on internal systems regularly to ensure that the monitoring system is always up to date. • Training and awareness raising: Strengthen employee training on identifying fraud methods such as phishing emails and social engineering, while raising users' security awareness to prevent information leakage. ──────────────────────────────── 【Summary】 The various fraud methods listed above are all widely documented cases in the public domain. Identifying and preventing these risks requires cross-institutional cooperation, technology upgrades and continuous risk assessments. Financial institutions, merchants, law enforcement agencies and consumers themselves should be vigilant and adopt scientific data analysis methods and strict verification processes to reduce losses caused by credit card fraud. Please remember that the purpose of this answer is to prevent and identify fraud, not to provide guidance on engaging in illegal activities. If you have more in-depth security concerns, it is recommended to consult a professional cybersecurity or financial risk control expert.