How antifraud systems work

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Anti-Fraud is a system or set of technologies that are used to prevent fraudulent activities in financial transactions, online shopping, banking operations and other areas. The main goal of anti-fraud systems is to identify suspicious actions and block them before they lead to losses. Let's look at how anti-fraud works and what methods are used to protect against fraudsters.

1. Basic principles of antifraud systems​

Anti-fraud systems work based on data analysis, user behavior, and checking for compliance with certain rules. Here are the main principles:

• Real Time: Most anti-fraud systems operate in real time to instantly detect suspicious activity.
• Automation: Systems use machine learning and artificial intelligence algorithms to analyze data and make decisions.
• Multi-level protection: Anti-fraud systems combine various verification methods, such as behavior analysis, device verification, geolocation and much more.

2. Methods used by antifraud systems​

a) Checking card details

• CVV/CVC: The correctness of the card security code (three digits on the back) is checked.
• Card expiration date: The system checks if the card has expired.
• BIN code: The first six digits of the card number (BIN) indicate the issuing bank and country of issue. If the BIN does not match the expected data, the transaction may be blocked.

b) IP address analysis

• Geography: The system checks whether the user's IP address matches the address specified when registering the card. For example, if the card is registered in Russia and the transaction occurs from another country, this raises suspicion.
• Proxies and Tor: Using anonymizers such as Tor or proxy servers is often seen as suspicious behavior.

c) Checking the device

• Device Fingerprinting: The system creates a "fingerprint" of the device (browser, operating system, screen resolution, installed plugins, etc.). If the device has not been used for card transactions before, this may be a flag for additional verification.
• Biometrics: Some systems use biometrics (such as face or voice scanning) to verify identity.

d) User behavior analysis

• Data entry speed: Suspiciously fast or slow data entry may indicate automated attacks.
• Behavioral patterns: The system tracks user habits (time of day, frequency of transactions, amounts). Deviations from normal behavior may be a sign of fraud.
• Clickstreaming: Analysis of the sequence of clicks on a website. Fraudsters often act according to a pre-prepared scenario, which differs from the behavior of real users.

e) Address verification

• Billing Address vs Shipping Address: The system compares the billing address with the shipping address. If they do not match, this may be a flag for verification.
• AVS (Address Verification System): Some countries use AVS, which checks whether the address specified during payment matches the bank details.

f) Transaction monitoring

• Transaction frequency: Excessively frequent transactions over a short period of time may be a sign of fraud.
• Transaction amounts: Unusually large or small amounts raise suspicion.
• Product Type: Buying items that are easy to resell (electronics, gift cards) can be a flag to check.

g) Two-factor authentication (2FA)

• To confirm a transaction, the system may request an additional factor, such as:
  • SMS code.
  • Push notification via mobile application.
  • One-Time Password (OTP) via email or a special application.

h) Artificial Intelligence and Machine Learning

• Big Data Analysis: Machine learning algorithms analyze huge amounts of data to identify anomalies and predict fraudulent activity.
• Historical learning: The system learns from past fraudulent activity and adapts to new threats.

3. How does the anti-fraud system make a decision?​

Anti-fraud systems use several levels of analysis to make a decision to block or approve a transaction:

• Rules-Based Systems:The system checks a transaction against pre-defined rules. For example:
  • Transaction over $1000 from another country is blocked.
  • A transaction from a new device requires additional verification.
• Risk Scoring: Each transaction is assigned a "risk score" based on data analysis. If the score exceeds a certain threshold, the transaction is blocked.
• Exceptions (Whitelisting/Blacklisting): The system can use lists of trusted (whitelist) or unsafe (blacklist) IP addresses, devices or users.

4. Examples of using antifraud systems​

a) Banking sector

• Banks use antifraud to monitor card transactions and detect suspicious operations.
• Example: If the card is used to make a purchase in an online store, but the owner is in another city, the system may request confirmation via SMS.

b) E-commerce

• Online stores are implementing anti-fraud to protect against fraudsters using stolen cards.
• Example: When trying to purchase an expensive item, the system checks whether the delivery address matches the cardholder's address.

c) Payment systems

• Payment systems (PayPal, Stripe, Wise) use antifraud to protect their users from fraudulent transactions.
• Example: If an account has been hacked, the system may temporarily block it for verification.

5. Advantages of antifraud systems​

• Fraud protection: Reduces the risk of financial losses for companies and customers.
• Automation: Many processes are performed without human intervention, which saves time.
• Adaptability: Systems continually learn and adapt to new threats.

6. Disadvantages of antifraud systems​

• False Positives: Sometimes legitimate transactions are blocked due to being incorrectly classified as fraudulent.
• Data Dependency: The effectiveness of a system depends on the quality of the data it analyzes.
• Difficulty of setup: For correct operation, it is necessary to set up rules and train algorithms.

7. How to protect yourself from false blocking?​

If your transaction was blocked by the anti-fraud system, follow these steps:

• Contact your bank or payment system: Explain the situation and provide evidence of the legality of the transaction.
• Use trusted devices: Try to make transactions from the same devices that you usually use.
• Enable two-factor authentication: This reduces the chance of being blocked.

Conclusion​

Anti-fraud systems play a key role in protecting against fraud in the modern world. They combine data analysis, machine learning, and behavioral analytics to identify suspicious activity. However, it is important to remember that such systems are not perfect and can sometimes make mistakes. To minimize risks, always monitor your financial transactions and report suspicious activity to your bank or payment system.

If you have questions about specific aspects of anti-fraud systems, clarify them and I will help!